Publications

The issue of failed weaning is a critical concern in the intensive care unit (ICU) setting. This scenario occurs when a patient experiences difficulty maintaining spontaneous breathing and ensuring a patent airway within the first 48 hours after the withdrawal of mechanical ventilation. Approximately 20% of ICU patients experience this phenomenon, which has severe repercussions on their health. It also has a substantial impact on clinical evolution and mortality, which can increase by 25% to 50%. To address this issue, we propose a medical support system that uses a convolutional neural network (CNN) to assess a patient's suitability for disconnection from a mechanical ventilator after a spontaneous breathing test (SBT). During SBT, respiratory flow and electrocardiographic activity were recorded and after processed using time-frequency analysis (TFA) techniques. Two CNN architectures were evaluated in this study: one based on ResNet50, with parameters tuned using a Bayesian optimization algorithm, and another CNN designed from scratch, with its structure also adapted using a Bayesian optimization algorithm. The WEANDB database was used to train and evaluate both models. The results showed remarkable performance, with an average accuracy 98 +/- 1.8% when using CNN from scratch. This model has significant implications for the ICU because it provides a reliable tool to enhance patient care by assisting clinicians in making timely and accurate decisions regarding weaning. This can potentially reduce the adverse outcomes associated with failed weaning events.

JTD Keywords: Bayesian optimization algorithm (boa, Continuous wavelet transform (cwt), Convolutional, Extubation, Failur, Intensive-care-unit, Neural network (cnn) from scratch, Respiratory-distress-syndrome, Time-frequency analysis (tfa), Weaning

Antimicrobial resistance (AMR) poses a significant threat to human health. Although vaccines have been developed to combat AMR, it has proven challenging to associate specific vaccine antigens with AMR. Bacterial plasmids play a crucial role in the transmission of AMR. Our recent research has identified a group of bacterial plasmids (specifically, IncHI plasmids) that encode large molecular mass proteins containing bacterial immunoglobulin-like domains. These proteins are found on the external surface of the bacterial cells, such as in the flagella or conjugative pili. In this study, we show that these proteins are antigenic and can protect mice from infection caused by an AMR Salmonella strain harboring one of these plasmids. Furthermore, we successfully generated nanobodies targeting these proteins, that were shown to interfere with the conjugative transfer of IncHI plasmids. Considering that these proteins are also encoded in other groups of plasmids, such as IncA/C and IncP2, targeting them could be a valuable strategy in combating AMR infections caused by bacteria harboring different groups of AMR plasmids. Since the selected antigens are directly linked to AMR itself, the protective effect extends beyond specific microorganisms to include all those carrying the corresponding resistance plasmids.

JTD Keywords: Antibodies, Beta-lactamase, Cell, Enterica, Escherichia-coli, Expression, Genes, Infection, Intimin, Mous, Mutational analysis, Pcr, Salmonella, Var typhimurium

[No abstract available]

JTD Keywords: Alpha synuclein, Animal cell, Article, Astrocyte, Brain blood flow, Capillary endothelial cell, Cardiovascular system, Cell interaction, Coculture, Degenerative disease, Differential expression analysis, Endothelium cell, Entactin, Extracellular matrix, Fibronectin, Gene expression, Human, Human cell, Huntington chorea, Hydroxyapatite, In vitro study, Induced pluripotent stem cell, Laminin, Macrophage, Maturity, Microglia, Nervous system, Nervous system inflammation, Neuroprotection, Neurotoxicity, Nonhuman, Parkinson disease, Pericyte, Perivascular space, Personalized medicine, Shear stress, Smooth muscle cell, Three dimensional printing

Human mesenchymal stromal cells (hMSCs) seeded on calcium phosphate (CaP) bioceramics are extensively explored in bone tissue engineering and have recently shown effective clinical outcomes. In previous pre-clinical studies, hMSCs-CaP-mediated bone formation was preceded by osteoclastogenesis at the implantation site. The current study evaluates to what extent phase composition of CaPs affects the osteoclast response and ultimately influence bone formation. To this end, four different CaP bioceramics were used, hydroxyapatite (HA), beta-tricalcium phosphate (beta-TCP) and two biphasic composites of HA/beta- TCP ratios of 60/40 and 20/80 respectively, for in vitro osteoclast differentiation and correlation with in vivo osteoclastogenesis and bone formation. All ceramics allowed osteoclast formation in vitro from mouse and human precursors, except for pure HA, which significantly impaired their maturation. Ectopic implantation alongside hMSCs in subcutis sites of nude mice revealed new bone formation at 8 weeks in all conditions with relative amounts for beta-TCP > biphasic CaPs > HA. Surprisingly, while hMSCs were essential for osteoinduction, their survival did not correlate with bone formation. By contrast, the degree of early osteoclastogenesis (2 weeks) seemed to define the extent of subsequent bone formation. Together, our findings suggest that the osteoclastic response could be used as a predictive marker in hMSC-CaPbased bone regeneration and strengthens the need to understand the underlying mechanisms for future biomaterial development. Statement of significance The combination of mesenchymal stromal cells (MSCs) and calcium phosphate (CaP) materials has demonstrated its safety and efficacy for bone regeneration in clinical trials, despite our insufficient understanding of the underlying biological mechanisms. Osteoclasts were previously suggested as key mediators between the early inflammatory phase following biomaterial implantation and the subsequent bone formation. Here we compared the affinity of osteoclasts for various CaP materials with different ratios of hydroxyapatite to beta-tricalcium phosphate. We found that osteoclast formation, both in vitro and at early stages in vivo, correlates with bone formation when the materials were implanted alongside MSCs in mice. Surprisingly, MSC survival did not correlate with bone formation, suggesting that the number or phenotype of osteoclasts formed was more important. (c) 2024 The Author(s). Published by Elsevier Ltd on behalf of Acta Materialia Inc. This is an open access article under the CC BY license ( http://creativecommons.org/licenses/by/4.0/ )

JTD Keywords: Acid phosphatase tartrate resistant isoenzyme, Animal, Animal cell, Animal experiment, Animal tissue, Animals, Article, Beta-tricalcium phosphate, Bioceramics, Biocompatible materials, Biomaterial, Bone, Bone development, Bone formation, Bone regeneration, Calcium phosphate, Calcium phosphate materials, Calcium phosphates, Cd14 antigen, Cell differentiation, Cell engineering, Cell maturation, Cell survival, Ceramics, Chemical composition, Controlled study, Correlation analysis, Correlation coefficient, Data correlation, Durapatite, Engraftment, Flowcharting, Human, Human cell, Human mesenchymal stromal cell, Human mesenchymal stromal cells, Humans, Hydroxyapatite, Hydroxyapatites, In vitro study, In vivo study, In-vitro, In-vivo, Mammals, Marrow stromal cells, Material composition, Material compositions, Mesenchymal stroma cell, Mesenchymal stromal cells, Mice, Mice, nude, Monocyte, Mouse, Nonhuman, Nude mouse, Ossification, Osteoclast, Osteoclastogenesis, Osteoclasts, Osteogenesis, Osteoinduction, Phase composition, Regeneration strategies, Resorption, Scaffolds, Stem-cells, Subcutaneous tissue, Tissue engineering, Transmission control protocol, Tri-calcium phosphates, Vimentin

The accurate spatial segregation into distinct phases within cell membranes coordinates vital biochemical processes and functionalities in living organisms. One of nature's strategies to localize reactivity is the formation of dynamic raft domains. Most raft models rely on liquid-ordered L-0 phases in a liquid-disordered L-d phase lacking correlation and remaining static, often necessitating external agents for phase separation. Here, we introduce a synthetic system of bicomponent glycodendrimersomes coassembled from Janus dendrimers and Janus glycodendrimers (JGDs), where lactose-lactose interactions exclusively drive lateral organization. This mechanism results in modulated phases across two length scales, yielding raft-like microdomains featuring nanoarrays at the nanoscale. By varying the density of lactose and molecular architecture of JGDs, the nanoarray type and size, shape, and spacing of the domains were controlled. Our findings offer insight into the potential primordial origins of rudimentary raft domains and highlight the crucial role of glycans within the glycocalyx.

JTD Keywords: Article, Artificial cells, Atomic force microscopy, Bicomponents, Bilayer, Bilayer membrane, Biochemical functionality, Biochemical process, Biological-membranes, Cell component, Cell membrane, Cellular parameters, Chemical interaction, Chemical structure, Chemistry, Cytology, Defined janus glycodendrimers, Dehydration, Dendrimer, Dendrimers, Dilution, Dimer, External agents, Fourier transform, Giant vesicles, Glycan, Glycans, Glycocalyx, Glycodendrimers, Janus dendrimer, Janus glycodendrimer, Lactose, Lateral organization, Lectin, Lipid rafts, Living organisms, Membrane damage, Membrane microdomain, Membrane microdomains, Membrane structure, Metabolism, Modulated phases, Molecule, Monomer, Nanoarrays, Oligosaccharide, Organization, Periodicity, Phase separation, Phase-separation, Phospholipids, Polysaccharide, Polysaccharides, Raft like domain, Relative humidity, Spatial segregation, Structure analysis, Sugars, Synthetic systems, Tetramer, Unclassified drug, Unilamellar vesicles, Water

Human pluripotent stem cell -derived kidney organoids offer unprecedented opportunities for studying polycystic kidney disease (PKD), which still has no effective cure. Here, we developed both in vitro and in vivo organoid models of PKD that manifested tubular injury and aberrant upregulation of renin-angiotensin aldosterone system. Single -cell analysis revealed that a myriad of metabolic changes occurred during cystogenesis, including defective autophagy. Experimental activation of autophagy via ATG5 overexpression or primary cilia ablation significantly inhibited cystogenesis in PKD kidney organoids. Employing the organoid xenograft model of PKD, which spontaneously developed tubular cysts, we demonstrate that minoxidil, a potent autophagy activator and an FDA -approved drug, effectively attenuated cyst formation in vivo. This in vivo organoid model of PKD will enhance our capability to discover novel disease mechanisms and validate candidate drugs for clinical translation.

JTD Keywords: Adenylate kinase, Adult, Animal cell, Animal experiment, Animal model, Animal tissue, Article, Autophagosome, Autophagy, Autophagy (cellular), Autosomal-dominant, Calcium homeostasis, Cilia, Cilium, Cohort analysis, Controlled study, Cyclic amp, Disease, Dominant polycystic kidney, Enzyme linked immunosorbent assay, Epithelium, Exon, Expression, Female, Food and drug administration, Framework, Generation, Growth, Hepatitis a virus cellular receptor 1, Human, Human cell, Humans, Immunohistochemistry, In vitro study, In vivo study, Kidney, Kidney organoid, Kidney polycystic disease, Male, Minoxidil, Mouse, Mutations, Nonhuman, Organoid, Organoids, Platelet derived growth factor beta receptor, Pluripotent stem-cells, Polycystic kidney diseases, Protein kinase lkb1, Renin, Sequestosome 1, Single cell analysis, Single cell rna seq, Small nuclear rna, Tunel assay, Upregulation, Western blotting, Whole exome sequencing

Laser surface micropatterning of dental-grade zirconia (3Y-TZP) was explored with the objective of providing defined linear patterns capable of guiding bone-cell response.A nanosecond (ns-) laser was employed to fabricate microgrooves on the surface of 3Y-TZP discs, yielding three different groove periodicities (i.e., 30, 50 and 100 µm). The resulting topography and surface damage were characterized by confocal laser scanning microscopy (CLSM) and scanning electron microscopy (SEM). X-Ray diffraction (XRD) and Raman spectroscopy techniques were employed to assess the hydrothermal degradation resistance of the modified topographies. Preliminary biological studies were conducted to evaluate adhesion (6 h) of human mesenchymal stem cells (hMSC) to the patterns in terms of cell number and morphology. Finally, Staphylococcus aureus adhesion (4 h) to the microgrooves was investigated.The surface analysis showed grooves of approximately 1.8 µm height that exhibited surface damage in the form of pile-up at the edge of the microgrooves, microcracks and cavities. Accelerated aging tests revealed a slight decrease of the hydrothermal degradation resistance after laser patterning, and the Raman mapping showed the presence of monoclinic phase heterogeneously distributed along the patterned surfaces. An increase of the hMSC area was identified on all the microgrooved surfaces, although only the 50 µm periodicity, which is closer to the cell size, significantly favored cell elongation and alignment along the grooves. A decrease in Staphylococcus aureus adhesion was observed on the investigated micropatterns.The study suggests that linear microgrooves of 50 µm periodicity may help in promoting hMSC adhesion and alignment, while reducing bacterial cell attachment.Copyright © 2023 The Authors. Published by Elsevier Inc. All rights reserved.

JTD Keywords: abutment material, alumina toughened zirconia, antibacterial, bacterial adhesion, biofilm growth, cell adhesion, dental implants, hydrothermal degradation, implant surfaces, in-vitro, laser patterning, osseointegration, osteogenic differentiation, part 1, surface topography, y-tzp ceramics, Antibacterial, Antibacterials, Bacteria, Bone, Cell adhesion, Cell culture, Cells adhesion, Ceramics, Chemistry, Degradation resistance, Dental implants, Dental material, Dental materials, Dental prostheses, Human, Human mesenchymal stem cells, Humans, Hydrothermal degradation, Laser patterning, Laser surface, Lasers, Low-temperature degradation, Materials testing, Microscopy, electron, scanning, Nanosecond lasers, Osseointegration, Piles, Scanning electron microscopy, Staphylococcus aureus, Stem cells, Surface analysis, Surface damages, Surface properties, Surface property, Surface topography, Topography, Yttrium, Zirconia, Zirconium

Gas-Chromatography coupled to Ion Mobility Spectrometry (GC-IMS) based metabolomics is an emerging technique for obtaining fast, reliable untargeted metabolic fingerprints of biofluids. The generated raw data is highly dimensional and complex, suffers from baseline problems, misalignments, long peak tails and strong nonlinearities that must be corrected to extract chemically relevant features from samples. In this work, we present our GCIMS R package, which includes spectra loading, metadata handling, denoising, baseline correction, spectral and chromatographic alignment, peak detection, integration, and peak clustering to produce a peak table ready for multivariate data analysis. We discuss package design decisions, and, for illustration purposes, we show a case study of sex discrimination on the basis of the volatile compounds in urine samples. The GCIMS package provides a user-friendly workflow for non-code developers to process their raw data samples.

JTD Keywords: Breath analysis, Headspace, Ims, Urine

Introduction: There is evidence that sample treatment of blood-based biosamples may affect integral signals in nuclear magnetic resonance-based metabolomics. The presence of macromolecules in plasma/serum samples makes investigating low-molecular-weight metabolites challenging. It is particularly relevant in the targeted approach, in which absolute concentrations of selected metabolites are often quantified based on the area of integral signals. Since there are a few treatments of plasma/serum samples for quantitative analysis without a universally accepted method, this topic remains of interest for future research. Methods: In this work, targeted metabolomic profiling of 43 metabolites was performed on pooled plasma to compare four methodologies consisting of Carr-Purcell-Meiboom-Gill (CPMG) editing, ultrafiltration, protein precipitation with methanol, and glycerophospholipid solid-phase extraction (g-SPE) for phospholipid removal; prior to NMR metabolomics analysis. The effect of the sample treatments on the metabolite concentrations was evaluated using a permutation test of multiclass and pairwise Fisher scores. Results: Results showed that methanol precipitation and ultrafiltration had a higher number of metabolites with coefficient of variation (CV) values above 20%. G-SPE and CPMG editing demonstrated better precision for most of the metabolites analyzed. However, differential quantification performance between procedures were metabolite-dependent. For example, pairwise comparisons showed that methanol precipitation and CPMG editing were suitable for quantifying citrate, while g-SPE showed better results for 2-hydroxybutyrate and tryptophan. Discussion: There are alterations in the absolute concentration of various metabolites that are dependent on the procedure. Considering these alterations is essential before proceeding with the quantification of treatment-sensitive metabolites in biological samples for improving biomarker discovery and biological interpretations. The study demonstrated that g-SPE and CPMG editing are effective methods for removing proteins and phospholipids from plasma samples for quantitative NMR analysis of metabolites. However, careful consideration should be given to the specific metabolites of interest and their susceptibility to the sample treatment procedures. These findings contribute to the development of optimized sample preparation protocols for metabolomics studies using NMR spectroscopy.Copyright © 2023 Madrid-Gambin, Oller, Marco, Pozo, Andres-Lacueva and Llorach.

JTD Keywords: binding, h-1-nmr spectroscopy, human serum, lactate, metabolites, nuclear magnetic resonance, plasma, protein, quantification, quantitative analysis, sample treatment, Metabolomics, Nuclear magnetic resonance, Nuclear-magnetic-resonance, Plasma, Quantification, Quantitative analysis, Sample treatment

(Phospho)proteomics of old-aged subjects without cognitive or behavioral symptoms, and without AD-neuropathological changes and lacking any other neurodegenerative alteration will increase understanding about the physiological state of human brain aging without associate neurological deficits and neuropathological lesions.(Phospho)proteomics using conventional label-free- and SWATH-MS (Sequential window acquisition of all theoretical fragment ion spectra mass spectrometry) has been assessed in the frontal cortex (FC) of individuals without NFTs, senile plaques (SPs) and age-related co-morbidities classified by age (years) in four groups; group 1 (young, 30-44); group 2 (middle-aged: MA, 45-52); group 3 (early-elderly, 64-70); and group 4 (late-elderly, 75-85).Protein levels and deregulated protein phosphorylation linked to similar biological terms/functions, but involving different individual proteins, are found in FC with age. The modified expression occurs in cytoskeleton proteins, membranes, synapses, vesicles, myelin, membrane transport and ion channels, DNA and RNA metabolism, ubiquitin-proteasome-system (UPS), kinases and phosphatases, fatty acid metabolism, and mitochondria. Dysregulated phosphoproteins are associated with the cytoskeleton, including microfilaments, actin-binding proteins, intermediate filaments of neurons and glial cells, and microtubules; membrane proteins, synapses, and dense core vesicles; kinases and phosphatases; proteins linked to DNA and RNA; members of the UPS; GTPase regulation; inflammation; and lipid metabolism. Noteworthy, protein levels of large clusters of hierarchically-related protein expression levels are stable until 70. However, protein levels of components of cell membranes, vesicles and synapses, RNA modulation, and cellular structures (including tau and tubulin filaments) are markedly altered from the age of 75. Similarly, marked modifications occur in the larger phosphoprotein clusters involving cytoskeleton and neuronal structures, membrane stabilization, and kinase regulation in the late elderly.Present findings may increase understanding of human brain proteostasis modifications in the elderly in the subpopulation of individuals not having AD neuropathological change and any other neurodegenerative change in any telencephalon region.

JTD Keywords: (phospho)proteomics, cortex, cytoskeleton, hippocampus, kinases, membranes, mitochondria, mitochondrial-function, pathological process, phosphoproteome analysis, phosphorylation, proteome, quantitative proteomics, synapsis, tau-protein, therapeutic target, (phospho)proteomics, Brain aging, Cytoskeleton, Kinases, Membranes, Mitochondria, Neurodegenerative diseases, Proteome, Synapsis

Microcantilever-based platforms are presented as versatile lab-on-chip devices for advanced applications spanning from material characterization and environmental monitoring to energy.

JTD Keywords: mechanical-properties, micromechanical cantilever, photothermal spectroscopy, sensitive detection, silicon cantilevers, solid-liquid interface, surface-stress, thin-films, vapor detection, Nanomechanical thermal-analysis

Microfluidics represents a very promising technological solution for conducting massive biological experiments. However, the difficulty of managing the amount of information available often precludes the wide potential offered. Using machine learning, we aim to accelerate microfluidics uptake and lead to quantitative and reliable findings. In this work, we propose complementing microfluidics with machine learning (MLM) approaches to enhance the diagnostic capability of lab-on-chip devices. The introduction of data analysis methodologies within the deep learning framework corroborates the possibility of encoding cell morphology beyond the standard cell appearance. The proposed MLM platform is used in a diagnostic test for blood diseases in murine RBC samples in a dedicated microfluidics device in flow. The lack of plasticity of RBCs in Pyruvate Kinase Disease (PKD) is measured massively by recognizing the shape deformation in RBCs walking in a forest of pillars within the chip. Very high accuracy results, far over 85 %, in recognizing PKD from control RBCs either in simulated and in real experiments demonstrate the effectiveness of the platform.

JTD Keywords: Blood disease, Deep transfer learning, Deficiency, Deformability, Machine learning microfluidics, Video analysis

Microglia are very sensitive to changes in the environment and respond through morphological, functional and metabolic adaptations. To depict the modifications microglia undergo under healthy and pathological conditions, we developed free access image analysis scripts to quantify microglia morphologies and phagocytosis. Neuron-glia cultures, in which microglia express the reporter tdTomato, were exposed to excitotoxicity or excitotoxicity + inflammation and analysed 8 h later. Neuronal death was assessed by SYTOX staining of nucleus debris and phagocytosis was measured through the engulfment of SYTOX+ particles in microglia. We identified seven morphologies: round, hypertrophic, fried egg, bipolar and three 'inflamed' morphologies. We generated a classifier able to separate them and assign one of the seven classes to each microglia in sample images. In control cultures, round and hypertrophic morphologies were predominant. Excitotoxicity had a limited effect on the composition of the populations. By contrast, excitotoxicity + inflammation promoted an enrichment in inflamed morphologies and increased the percentage of phagocytosing microglia. Our data suggest that inflammation is critical to promote phenotypical changes in microglia. We also validated our tools for the segmentation of microglia in brain slices and performed morphometry with the obtained mask. Our method is versatile and useful to correlate microglia sub-populations and behaviour with environmental changes.

JTD Keywords: classification, identification, image analysis, injury, morphometry, neuroinflammation, neurotoxicity, phagocytosis, Classification, Image analysis, Microglia, Morphometry, Neuroinflammation, Nitric-oxide, Phagocytosis

The ability to engineer complex multicellular systems has enormous potential to inform our understanding of biological processes and disease and alter the drug development process. Engineering living systems to emulate natural processes or to incorporate new functions relies on a detailed understanding of the biochemical, mechanical, and other cues between cells and between cells and their environment that result in the coordinated action of multicellular systems. On April 3-6, 2022, experts in the field met at the Keystone symposium "Engineering Multicellular Living Systems" to discuss recent advances in understanding how cells cooperate within a multicellular system, as well as recent efforts to engineer systems like organ-on-a-chip models, biological robots, and organoids. Given the similarities and common themes, this meeting was held in conjunction with the symposium "Organoids as Tools for Fundamental Discovery and Translation".

JTD Keywords: computational, engineered living, engineered organs, multicellular, Brain organoids, Cell diversity, Computational, Dynamics, Engineered living, Engineered organs, Heart, Maturation, Model, Multicellular, Mycobacterium-tuberculosis, Quantitative-analysis, Systems, Tissue deformation

Around 30-40% of patients with colorectal cancer (CRC) undergoing curative resection of the primary tumour will develop metastases in the subsequent years1. Therapies to prevent disease relapse remain an unmet medical need. Here we uncover the identity and features of the residual tumour cells responsible for CRC relapse. An analysis of single-cell transcriptomes of samples from patients with CRC revealed that the majority of genes associated with a poor prognosis are expressed by a unique tumour cell population that we named high-relapse cells (HRCs). We established a human-like mouse model of microsatellite-stable CRC that undergoes metastatic relapse after surgical resection of the primary tumour. Residual HRCs occult in mouse livers after primary CRC surgery gave rise to multiple cell types over time, including LGR5+ stem-like tumour cells2-4, and caused overt metastatic disease. Using Emp1 (encoding epithelial membrane protein 1) as a marker gene for HRCs, we tracked and selectively eliminated this cell population. Genetic ablation of EMP1high cells prevented metastatic recurrence and mice remained disease-free after surgery. We also found that HRC-rich micrometastases were infiltrated with T cells, yet became progressively immune-excluded during outgrowth. Treatment with neoadjuvant immunotherapy eliminated residual metastatic cells and prevented mice from relapsing after surgery. Together, our findings reveal the cell-state dynamics of residual disease in CRC and anticipate that therapies targeting HRCs may help to avoid metastatic relapse.© 2022. The Author(s), under exclusive licence to Springer Nature Limited.

JTD Keywords: colonization, defines, human colon, mutations, plasticity, retrieval, stem-cells, subtypes, underlie, Animal, Animal cell, Animal experiment, Animal model, Animal tissue, Animals, Article, Cancer, Cancer growth, Cancer immunotherapy, Cancer inhibition, Cancer recurrence, Cancer staging, Cell, Cell adhesion, Cell migration, Cell population, Cell surface receptor, Cohort analysis, Colorectal cancer, Colorectal neoplasms, Colorectal tumor, Comprehensive molecular characterization, Controlled study, Crispr-cas9 system, Cytoskeleton, Disease exacerbation, Disease progression, Dynamics, Emp1 gene, Epithelial membrane protein-1, Extracellular matrix, Flow cytometry, Fluorescence intensity, Gene expression, Genetics, Human, Human cell, Humans, Immune response, Immunofluorescence, In situ hybridization, Marker gene, Metastasis potential, Mice, Minimal residual disease, Mouse, Neoplasm proteins, Neoplasm recurrence, local, Neoplasm, residual, Nonhuman, Pathology, Phenotype, Prevention and control, Protein, Receptors, cell surface, Single cell rna seq, Tumor, Tumor protein, Tumor recurrence

About 50% of human epidermal growth factor receptor 2 (HER2)+ breast cancer patients do not benefit from HER2-targeted therapy and almost 20% of them relapse after treatment. Here, we conduct a detailed analysis of two independent cohorts of HER2+ breast cancer patients treated with trastuzumab to elucidate the mechanisms of resistance to anti-HER2 monoclonal antibodies. In addition, we develop a fully humanized immunocompetent model of HER2+ breast cancer recapitulating ex vivo the biological processes that associate with patients’ response to treatment. Thanks to these two approaches, we uncover a population of TGF-beta-activated cancer-associated fibroblasts (CAF) specific from tumors resistant to therapy. The presence of this cellular subset related to previously described myofibroblastic (CAF-S1) and podoplanin+ CAF subtypes in breast cancer associates with low IL2 activity. Correspondingly, we find that stroma-targeted stimulation of IL2 pathway in unresponsive tumors restores trastuzumab anti-cancer efficiency. Overall, our study underscores the therapeutic potential of exploiting the tumor microenvironment to identify and overcome mechanisms of resistance to anti-cancer treatment.

JTD Keywords: activation, cells, efficacy, enrichment analysis, expression, infiltrating lymphocytes, survival, therapy, trastuzumab, Her2-positive breast-cancer

The neocortex of P301S mice, used as a model of fronto-temporal lobar degeneration linked to tau mutation (FTLD-tau), and wild-type mice, both aged 9 months, were analyzed with conventional label-free phosphoproteomics and SWATH-MS (sequential window acquisition of all theoretical fragment ion spectra mass spectrometry) to assess the (phospho)proteomes. The total number of identified dysregulated phosphoproteins was 328 corresponding to 524 phosphorylation sites. The majority of dysregulated phosphoproteins, most of them hyperphosphorylated, were proteins of the membranes, synapses, membrane trafficking, membrane vesicles linked to endo- and exocytosis, cytoplasmic vesicles, and cytoskeleton. Another group was composed of kinases. In contrast, proteins linked to DNA, RNA metabolism, RNA splicing, and protein synthesis were hypophosphorylated. Other pathways modulating energy metabolism, cell signaling, Golgi apparatus, carbohydrates, and lipids are also targets of dysregulated protein phosphorylation in P301S mice. The present results, together with accompanying immunohistochemical and Western-blotting studies, show widespread abnormal phosphorylation of proteins, in addition to protein tau, in P301S mice. These observations point to dysregulated protein phosphorylation as a relevant contributory pathogenic component of tauopathies.

JTD Keywords: (phospho)proteomics, cytoskeleton, kinases, membranes, tau, (phospho)proteomics, Cytoskeleton, Kinases, Membranes, Networks, Oxidative stress, Pathology, Phosphoproteome analysis, Tau, Tauopathy

Supramolecular chemistry is the quintessential backbone of all biological processes. It encompasses a wide range from the metabolic network to the self-assembled cytoskeletal network. Combining the chemical diversity with the plethora of functional depth that biological systems possess is a daunting task for synthetic chemists to emulate. The only route for approaching such a challenge lies in understanding the complex and dynamic systems through advanced analytical techniques. The supramolecular complexity that can be successfully generated and analyzed is directly dependent on the analytical treatment of the system parameters. In this review, we illustrate advanced analytical techniques that have been used to investigate various supramolecular systems including complex mixtures, dynamic self-assembly, and functional nanomaterials. The underlying theme of such an overview is not only the exceeding detail with which traditional experiments can be probed but also the fact that complex experiments can now be attempted owing to the analytical techniques that can resolve an ensemble in astounding detail. Furthermore, the review critically analyzes the current state of the art analytical techniques and suggests the direction of future development. Finally, we envision that integrating multiple analytical methods into a common platform will open completely new possibilities for developing functional chemical systems.

JTD Keywords: analytical techniques, dynamic self-assembly, high-speed afm, liquid cell tem, Analytical technique, Analytical techniques, Biological process, Chemical analysis, Chemical diversity, Complex networks, Cytoskeletal network, Dynamic self-assembly, High-speed afm, Hydrogels, In-situ, Liquid cell tem, Metabolic network, Microscopy, Nanoscale, Proteins, Self assembly, Supramolecular chemistry, Supramolecular systems, System chemistry, Systems chemistry

Biosensors represent a powerful analytical tool for analyzing biomolecular interactions with the potential to achieve real-time quantitative analysis with high accuracy using low sample volumes, minimum sample pretreatment with high potential for the development of in situ and highly integrated monitoring platforms. Considering these advantages, their use in cell-culture systems has increased over the last few years. Between the different technologies for cell culture, organs-on-a-chip (OOCs) represent a novel technology that tries to mimic an organ's functionality by combining tissue engineering/organoid with microfluidics. Although there are still challenges to achieving OOC models with high organ mimicking relevance, these devices can offer effective models for drug treatment development by identifying drug targets, screening toxicity, and determining the potential effects of drugs in living beings. Consequently, in the future, we might replace animal studies by offering more ethical test models. Considering the relevance that different physiological and biochemical parameters have in the correct functionality of cells, sensing and biosensing platforms can offer an effective way for the real-time monitoring of physiological parameters and, in our opinion, more relevant, the secretion of biomarkers such as cytokines, growth factors, and others related with the influence of drugs or other types of stimulus in cell metabolism. Keeping this concept in mind, in this chapter, we focus on describing the potential use of sensors and biosensors in OOC devices to achieve fully integrated platforms that monitor physiological parameters and cell metabolism.© 2022. The Author(s), under exclusive license to Springer Nature Switzerland AG.

JTD Keywords: alignment, biosensors, cell, crystal microbalance biosensor, electrochemical biosensors, future, graphene oxide, label-free detection, organ-on-a-chip, oxygen, pre-clinical platforms, real-time analysis, screening, Biosensors, Organ-on-a-chip, Pre-clinical platforms, Screening, Sensors, Surface-plasmon resonance

Tuning of the crosslink density (CLD) in the rubber compounds is very crucial for optimizing the physical and mechanical properties of the ultimate rubber products. Conventionally, CLD can be measured via rheological methods such as moving die rheometer (MDR), via mechanical tests such as temperature scanning stress relaxation analysis (TSSR), or via direct swelling experiments using Flory–Rehner approach. In the current study, two novel techniques, focused ion beam - scanning electron microscopy (FIB-SEM) processing, with simultaneous energy dispersive X-ray spectrometry (EDS) mapping analysis and scanning acoustic microscopy (SAM) were combined and correlated to conventional methods on a model recipe of ethylene propylene diene monomer (EPDM) compound having different sulphur contents. Depending on the applied technique, the increase in the crosslink density with sulphur content was found to be 1.7 fold for the Flory–Rehner approach and 1.2 fold for both TSSR and MDR. It is directly monitored from the FIB-SEM-EDS analysis that the sulphur distribution and agglomeration behavior increased in line with ZnO content, which is an indirect indication of the rise in crosslink density. The impedance maps of the crosslinked samples obtained through SAM analysis revealed that the impedance of the samples increased with the increasing sulphur content, which can be attributed to higher level of crosslink density. A quantified correlation was obtained between SAM images and the crosslink density of the samples. It was shown that SAM is a promising tool for practical and non-destructive analysis for determining the formation of crosslink density of the rubbers. © The Author(s) 2022.

JTD Keywords: blends, compressibility, crosslink density, cure characteristics, ethylene propylene diene monomer, focused ion beam, mechanical-properties, morphology, natural-rubber, particles, scanning acoustic microscopy, scanning electron microscopy, sulfur, thermal-stability, vulcanization, Composite soft materials, Cross-link densities, Crosslink density, Crosslinking, Density (specific gravity), Ethylene, Ethylene propylene diene monomer, Flory-rehner, Focused ion beam - scanning electron microscopy, Focused ion beam-scanning electron microscopies, Ii-vi semiconductors, Monomers, Moving die rheometers, Physical and mechanical properties, Propylene, Relaxation analysis, Rubber, Scanning acoustic microscopy, Scanning electron microscopy, Stress relaxation, Sulfur contents, Temperature scanning stress relaxations, Zinc oxide

Altered protein phosphorylation is a major pathologic modification in tauopathies and Alzheimer's disease (AD) linked to abnormal tau fibrillar deposits in neurofibrillary tangles (NFTs) and pre-tangles and beta-amyloid deposits in AD. hTau transgenic mice, which express 3R and less 4R human tau with no mutations in a murine knock-out background, show increased tau deposition in neurons but not NFTs and pre-tangles at the age of nine months. Label-free (phospho)proteomics and SWATH-MS identified 2065 proteins in hTau and wild-type (WT) mice. Only six proteins showed increased levels in hTau; no proteins were down-regulated. Increased tau phosphorylation in hTau was detected at Ser199, Ser202, Ser214, Ser396, Ser400, Thr403, Ser404, Ser413, Ser416, Ser422, Ser491, and Ser494, in addition to Thr181, Thr231, Ser396/Ser404, but not at Ser202/Thr205. In addition, 4578 phosphopeptides (corresponding to 1622 phosphoproteins) were identified in hTau and WT mice; 64 proteins were differentially phosphorylated in hTau. Sixty proteins were grouped into components of membranes, membrane signaling, synapses, vesicles, cytoskeleton, DNA/RNA/protein metabolism, ubiquitin/proteasome system, cholesterol and lipid metabolism, and cell signaling. These results showed that over-expression of human tau without pre-tangle and NFT formation preferentially triggers an imbalance in the phosphorylation profile of specific proteins involved in the cytoskeletal-membrane-signaling axis.

JTD Keywords: cytoskeleton, htau, membrane, phosphorylation, synapsis, tau, Aggregation, Alzheimers-disease, Animal-models, Cytoskeleton, Htau, Membrane, Mice, Networks, Pathology, Phosphoproteome analysis, Phosphorylation, Synapsis, Tau, Tauopathies, Tauopathy

The influence of the properties of different solid substrates on the tethering of two antibodies, IgG1-CR3022 and IgG1-S309, which were specifically engineered for the detection of SARS-CoV-2, has been examined at the molecular level using conventional and accelerated Molecular Dynamics (cMD and aMD, respectively). Two surfaces with very different properties and widely used in immunosensors for diagnosis, amorphous silica and the most stable facet of the face-centered cubic gold structure, have been considered. The effects of such surfaces on the structure and orientation of the immobilized antibodies have been determined by quantifying the tilt and hinge angles that describe the orientation and shape of the antibody, respectively, and the dihedrals that measure the relative position of the antibody arms with respect to the surface. Results show that the interactions with amorphous silica, which are mainly electrostatic due to the charged nature of the surface, help to preserve the orientation and structure of the antibodies, especially of the IgG1-CR3022, indicating that the primary sequence of those antibodies also plays some role. Instead, short-range van der Waals interactions with the inert gold surface cause a higher degree tilting and fraying of the antibodies with respect to amorphous silica. The interactions between the antibodies and the surface also affect the correlation among the different angles and dihedrals, which increases with their strength. Overall, results explain why amorphous silica substrates are frequently used to immobilize antibodies in immunosensors. © 2022 The Authors

JTD Keywords: amorphous silica, antibody immobilization, enzyme, gol d, gold, immobilization, immunosensor, molecu l a r dynamics, molecular dynamics, protein adsorption, sars-cov-2 immunosensor, simulations, spike protein, surface interactions, target, vaccine, Amorphous silica, Antibodies, Antibody engineering, Antibody immobilization, Antibody structure, Article, Chemical detection, Computer model, Controlled study, Dihedral angle, Gold, In-silico, Molecular dynamics, Molecular levels, Molecular-dynamics, Nonhuman, Property, Sars, Sars-cov-2 immunosensor, Severe acute respiratory syndrome coronavirus 2, Silica, Silico studies, Silicon dioxide, Solid substrates, Structure analysis, Substrate chemistry, Substrates, Van der waals forces, Virus detection

There has been a renewed interest in the potential use of psychedelics for the treatment of psychiatric conditions. Nevertheless, little is known about the mechanism of action and molecular pathways influenced by ayahuasca use in humans. Therefore, for the first time, our study aims to investigate the human metabolomics signature after consumption of a psychedelic, ayahuasca, and its connection with both the psychedelic-induced subjective effects and the plasma concentrations of ayahuasca alkaloids. Plasma samples of 23 individuals were collected both before and after ayahuasca consumption. Samples were analysed through targeted metabolomics and further integrated with subjective ratings of the ayahuasca experience (i.e., using the 5-Dimension Altered States of Consciousness Rating Scale [ASC]), and plasma ayahuasca-alkaloids using integrated network analysis. Metabolic pathways enrichment analysis using diffusion algorithms for specific KEGG modules was performed on the metabolic output. Compared to baseline, the consumption of ayahuasca increased N-acyl-ethanolamine endocannabinoids, decreased 2-acyl-glycerol endocannabinoids, and altered several large-neutral amino acids (LNAAs). Integrated network results indicated that most of the LNAAs were inversely associated with 9 out of the 11 subscales of the ASC, except for tryptophan which was positively associated. Several endocannabinoids and hexosylceramides were directly associated with the ayahuasca alkaloids. Enrichment analysis confirmed dysregulation in several pathways involved in neurotransmission such as serotonin and dopamine synthesis. In conclusion, a crosstalk between the circulating LNAAs and the subjective effects is suggested, which is independent of the alkaloid concentrations and provides insights into the specific metabolic fingerprint and mechanism of action underlying ayahuasca experiences. © 2022 The Authors

JTD Keywords: anxiety, ayahuasca, dimethyltryptamine, integrative network analysis, metabolism, metabolomics, psychedelics, rats, subjective effects, system, tryptophan, Ayahuasca, Dimethyltryptamine, Integrative network analysis, Metabolomics, Psychedelics, Serotonin 5-ht2a, Subjective effects

Transmission of a plasmid from one bacterial cell to another, in several instances, underlies the dissemination of antimicrobial resistance (AMR) genes. The process requires well-characterized enzymatic machinery that facilitates cell-to-cell contact and the transfer of the plasmid.

JTD Keywords: antimicrobial resistance, bacterial ig-like proteins, bacterial lg-like proteins, chromosomal genes, identification, inca/c, mutational analysis, plasmid conjugation, products, r-factors, resistance plasmids, salmonella-enterica, sequence, Antimicrobial resistance, Bacterial ig-like proteins, Escherichia-coli, Plasmid conjugation

The mechanical signals sensed by the alveolar cells through the changes in the local matrix stiffness of the extracellular matrix (ECM) are determinant for regulating cellular functions. Therefore, the study of the mechanical response of lung tissue becomes a fundamental aspect in order to further understand the mechanosensing signals perceived by the cells in the alveoli. This study is focused on the development of a finite element (FE) model of a decellularized rat lung tissue strip, which reproduces accurately the mechanical behaviour observed in the experiments by means of a tensile test. For simulating the complex structure of the lung parenchyma, which consists of a heterogeneous and non-uniform network of thin-walled alveoli, a 3D model based on a Voronoi tessellation is developed. This Voronoi-based model is considered very suitable for recreating the geometry of cellular materials with randomly distributed polygons like in the lung tissue. The material model used in the mechanical simulations of the lung tissue was characterized experimentally by means of AFM tests in order to evaluate the lung tissue stiffness on the micro scale. Thus, in this study, the micro (AFM test) and the macro scale (tensile test) mechanical behaviour are linked through the mechanical simulation with the 3D FE model based on Voronoi tessellation. Finally, a micro-mechanical FE-based model is generated from the Voronoi diagram for studying the stiffness sensed by the alveolar cells in function of two independent factors: the stretch level of the lung tissue and the geometrical position of the cells on the extracellular matrix (ECM), distinguishing between pneumocyte type I and type II. We conclude that the position of the cells within the alveolus has a great influence on the local stiffness perceived by the cells. Alveolar cells located at the corners of the alveolus, mainly type II pneumocytes, perceive a much higher stiffness than those located in the flat areas of the alveoli, which correspond to type I pneumocytes. However, the high stiffness, due to the macroscopic lung tissue stretch, affects both cells in a very similar form, thus no significant differences between them have been observed. © 2021 The Authors

JTD Keywords: rat, scaffolds, stiffness, Afm, Animal cell, Animal experiment, Animal model, Animal tissue, Article, Biological organs, Cell function, Cells, Computational geometry, Cytology, Extracellular matrices, Extracellular matrix, Extracellular-matrix, Geometry, High stiffness, Human, Lung alveolus cell type 1, Lung alveolus cell type 2, Lung parenchyma, Lung tissue, Male, Mechanical behavior, Mechanical modeling, Mechanical simulations, Mechanosensing, Model-based opc, Nonhuman, Physical model, Rat, Rigidity, Stiffness, Stiffness matrix, Tensile testing, Thin walled structures, Three dimensional finite element analysis, Tissue, Type ii, Voronoi tessellations

Background and aims: In this work, breath samples from clinically stable bronchiectasis patients with and without bronchial infections by Pseudomonas Aeruginosa- PA) were collected and chemically analysed to determine if they have clinical value in the monitoring of these patients. Materials and methods: A cohort was recruited inviting bronchiectasis patients (25) and controls (9). Among the former group, 12 members were suffering PA infection. Breath samples were collected in Tedlar bags and analyzed by e-nose and Gas Chromatography-Mass Spectrometry (GC-MS). The obtained data were analyzed by chemometric methods to determine their discriminant power in regards to their health condition. Results were evaluated with blind samples. Results: Breath analysis by electronic nose successfully separated the three groups with an overall classification rate of 84% for the three-class classification problem. The best discrimination was obtained between control and bronchiectasis with PA infection samples 100% (CI95%: 84–100%) on external validation and the results were confirmed by permutation tests. The discrimination analysis by GC-MS provided good results but did not reach proper statistical significance after a permutation test. Conclusions: Breath sample analysis by electronic nose followed by proper predictive models successfully differentiated between control, Bronchiectasis and Bronchiectasis PA samples. © 2021 The Author(s)

JTD Keywords: biomarkers, breath analysis, bronchiectasis, diagnosis, e-nose, fingerprints, gc-ms, identification, lung-cancer, partial least-squares, pseudomonas-aeruginosa, signal processing, validation, volatile organic-compounds, Airway bacterial-colonization, Breath analysis, Bronchiectasis, E-nose, Gc-ms, Signal processing

The impact of diet and digestive disorders in flatus composition remains largely unexplored. This is partially due to the lack of standardized sampling collection methods, and the easy atmospheric contamination. This paper describes a method to quantitatively determine the major gases in flatus and their application in a nutritional intervention. We describe how to direct sample flatus into Tedlar bags, and simultaneous analysis by gas chromatography–thermal conductivity detection (GC–TCD). Results are analyzed by univariate hypothesis testing and by multilevel principal component analysis. The reported methodology allows simultaneous determination of the five major gases with root mean measurement errors of 0.8% for oxygen (O2), 0.9% for nitrogen (N2), 0.14% for carbon dioxide (CO2), 0.11% for methane (CH4), and 0.26% for hydrogen (H2). The atmospheric contamination was limited to 0.86 (95% CI: [0.7–1.0])% for oxygen and 3.4 (95% CI: [1.4–5.3])% for nitrogen. As an illustration, the method has been successfully applied to measure the response to a nutritional intervention in a reduced crossover study in healthy subjects. © 2022 by the authors. Licensee MDPI, Basel, Switzerland.

JTD Keywords: breath, colonic microbiota, diet effect on flatus, disorders, evacuation, excretion, flatulence, hydrogen gas, major flatus gas components, multilevel principal component analysis, rectal gas collection, systems, volume, Atmospheric contamination, Carbon dioxide, Conductivity detection, Diet effect on flatus, Gas chromatography, Gas collections, Gas component, Gases, Major flatus gas component, Major flatus gas components, Multilevel principal component analyse, Multilevel principal component analysis, Multilevels, Nitrogen, Nutrition, Oxygen, Principal component analysis, Principal-component analysis, Rectal gas collection, Volatile organic-compounds

Thermogravimetric (TG) technique combined with partial least squares discriminant analysis (PLS-DA) was applied to distinguish five pilsner beers from different brands (Antarctica, Bohemia, Brahma, Budweiser and Imperio). Herein, we develop a TG methodology that use a small volume (40 µL), and an analysis time of 25 min. The major gases evolved during the thermal decomposition were water, ethanol and carbon dioxide. Energy-dispersive X-ray spectrometer of the ashes detected the major constituents: oxygen, sodium, magnesium, silicon, phosphorus, sulfur, chlorine, potassium and calcium. TG and PLS-DA technique together were able to classify the five brands with a classification rate for the model of 97% with a confidence interval of 92–99%, achieving high sensitivity and specificity between the calibration, cross-validation and predicted results.

JTD Keywords: chemometrics, thermal analysis, Beer, Chemometrics, Thermal analysis

Influenza recombinant proteins and virus-like particles (VLPs) play an important role in vaccine development (e.g., CadiFluS). However, their production from mammalian cells suffers from low yields and lack of control of the final VLPs. To improve these issues, characterization techniques able to visualize and quantify the different steps of the process are needed. Fluorescence microscopy represents a powerful tool able to image multiple protein targets; however, its limited resolution hinders the study of viral constructs. Here, we propose the use of super-resolution microscopy and in particular of DNA-point accumulation for imaging in nanoscale topography (DNA-PAINT) microscopy as a characterization method for recombinant viral proteins on both cells and VLPs. We were able to quantify the amount of the three main influenza proteins (hemagglutinin (HA), neuraminidase (NA), and ion channel matrix protein 2 (M2)) per cell and per VLP with nanometer resolution and single-molecule sensitivity, proving that DNA-PAINT is a powerful technique to characterize recombinant viral constructs.

JTD Keywords: dna-paint, hemagglutinin, influenza, neuraminidase, paint, recombinant proteins, single-molecule localization microscopy, single-particle analysis, virus-like particles, Dna-paint, Hemagglutinin, Influenza, Neuraminidase, Paint, Recombinant proteins, Single particle analysis, Single-molecule localization microscopy, Single-particle analysis, Super-resolution microscopy, Superresolution microscopy, Virus-like particles

With the currently available materials and technologies it is difficult to mimic the mechanical properties of soft living tissues. Additionally, another significant problem is the lack of information about the mechanical properties of these tissues. Alternatively, the use of phantoms offers a promising solution to simulate biological bodies. For this reason, to advance in the state-of-the-art a wide range of organs (e.g., liver, heart, kidney as well as brain) and hydrogels (e.g., agarose, polyvinyl alcohol –PVA–, Phytagel –PHY– and methacrylate gelatine –GelMA–) were tested regarding their mechanical properties. For that, viscoelastic behavior, hardness, as well as a non-linear elastic mechanical response were measured. It was seen that there was a significant difference among the results for the different mentioned soft tissues. Some of them appear to be more elastic than viscous as well as being softer or harder. With all this information in mind, a correlation between the mechanical properties of the organs and the different materials was performed. The next conclusions were drawn: (1) to mimic the liver, the best material is 1% wt agarose; (2) to mimic the heart, the best material is 2% wt agarose; (3) to mimic the kidney, the best material is 4% wt GelMA; and (4) to mimic the brain, the best materials are 4% wt GelMA and 1% wt agarose. Neither PVA nor PHY was selected to mimic any of the studied tissues. © 2022 by the authors. Licensee MDPI, Basel, Switzerland.

JTD Keywords: brain, composite hydrogel, dynamic mechanical analysis, elastography, hardness, hydrogels, in-vitro, liver, materials, mechanical-properties, mimicking, soft tissues, tissue scaffolding, viscoelasticity, warner-braztler shear test, warner–braztler shear test, Dynamic mechanical analysis, Hardness, Hydrogels, Materials, Mimicking, Soft tissues, Tissue scaffolding, Viscoelastic characterization, Viscoelasticity, Warner–braztler shear test

Different copolymers incorporating terpene oxide units (e.g., limonene oxide) have been evaluated considering thermal properties, degradability, and biocompatibility. Thus, polycarbonates and polyesters derived from aromatic, monocyclic and bicyclic anhydrides have been considered. Furthermore, ring substitution with myrcene terpene has been evaluated. All polymers were amorphous when evaluated directly from synthesis. However, spherulites could be observed after the slow evaporation of diluted chloroform solutions of polylimonene carbonate, with all isopropene units possessing an R configuration. This feature was surprising considering the reported information that suggested only the racemic polymer was able to crystallize. All polymers were thermally stable and showed a dependence of the maximum degradation rate temperature (from 242 °C to 342 °C) with the type of terpene oxide. The graduation of glass transition temperatures (from 44 °C to 172 °C) was also observed, being higher than those corresponding to the unsubstituted polymers. The chain stiffness of the studied polymers hindered both hydrolytic and enzymatic degradation while a higher rate was detected when an oxidative medium was assayed (e.g., weight losses around 12% after 21 days of exposure). All samples were biocompatible according to the adhesion and proliferation tests performed with fibroblast cells. Hydrophobic and mechanically consistent films (i.e., contact angles between 90° and 110°) were obtained after the evaporation of chloroform from the solutions, having different ratios of the studied biobased polyterpenes and poly(butylene succinate) (PBS). The blend films were comparable in tensile modulus and tensile strength with the pure PBS (e.g., values of 330 MPa and 7 MPa were determined for samples incorporating 30 wt.% of poly(PA-LO), the copolyester derived from limonene oxide and phthalic anhydride. Blends were degradable, biocompatible and appropriate to produce oriented-pore and random-pore scaffolds via a thermally-induced phase separation (TIPS) method and using 1,4-dioxane as solvent. The best results were attained with the blend composed of 70 wt.% PBS and 30 wt.% poly(PA-LO). In summary, the studied biobased terpene derivatives showed promising properties to be used in a blended form for biomedical applications such as scaffolds for tissue engineering.

JTD Keywords: alternating copolymerization, biobased materials, biodegradability, composites, crystallization, cyclohexene oxide, induced phase-separation, limonene oxide, mechanical-properties, polyesters, scaffolds, spherulites, terpene derivatives, thermal properties, thermally-induced phase separation, Acetone, Bio-based, Bio-based materials, Biobased materials, Biocompatibility, Biodegradability, Butenes, Cell culture, Chlorine compounds, Degradation, Evaporation, Glass transition, Limonene oxide, Monoterpenes, Phase separation, Poly (butylenes succinate), Polybutylene succinate, Property, Ring-opening copolymerization, Scaffolds, Spheru-lites, Tensile strength, Terpene derivatives, Thermal properties, Thermally induced phase separation, Thermally-induced phase separation, Thermally?induced phase separation, Thermodynamic properties, Thermogravimetric analysis

Introduction: After a stroke, a wide range of deficits can occur with varying onset latencies. As a result, assessing impairment and recovery are enormous challenges in neurorehabilitation. Although several clinical scales are generally accepted, they are time-consuming, show high inter-rater variability, have low ecological validity, and are vulnerable to biases introduced by compensatory movements and action modifications. Alternative methods need to be developed for efficient and objective assessment. In this study, we explore the potential of computer-based body tracking systems and classification tools to estimate the motor impairment of the more affected arm in stroke patients. Methods: We present a method for estimating clinical scores from movement parameters that are extracted from kinematic data recorded during unsupervised computer-based rehabilitation sessions. We identify a number of kinematic descriptors that characterise the patients' hemiparesis (e.g., movement smoothness, work area), we implement a double-noise model and perform a multivariate regression using clinical data from 98 stroke patients who completed a total of 191 sessions with RGS. Results: Our results reveal a new digital biomarker of arm function, the Total Goal-Directed Movement (TGDM), which relates to the patients work area during the execution of goal-oriented reaching movements. The model's performance to estimate FM-UE scores reaches an accuracy of R-2: 0.38 with an error (sigma: 12.8). Next, we evaluate its reliability (r = 0.89 for test-retest), longitudinal external validity (95% true positive rate), sensitivity, and generalisation to other tasks that involve planar reaching movements (R-2: 0.39). The model achieves comparable accuracy also for the Chedoke Arm and Hand Activity Inventory (R-2: 0.40) and Barthel Index (R-2: 0.35). Conclusions: Our results highlight the clinical value of kinematic data collected during unsupervised goal-oriented motor training with the RGS combined with data science techniques, and provide new insight into factors underlying recovery and its biomarkers.

JTD Keywords: interactive feedback, motion classification, motion sensing, multivariate regression, posture monitoring, rehabilitation, stroke, Adult, Aged, Analytic method, Arm movement, Article, Barthel index, Brain hemorrhage, Cerebrovascular accident, Chedoke arm and hand activity inventory, Clinical protocol, Cognitive defect, Computer analysis, Controlled study, Convergent validity, Correlation coefficient, Disease severity, External validity, Female, Fugl meyer assessment for the upper extremity, Functional assessment, Functional status assessment, General health status assessment, Hemiparesis, Human, Interactive feedback, Ischemic stroke, Kinematics, Major clinical study, Male, Mini mental state examination, Motion classification, Motion sensing, Motor analog scale, Movement, Multivariate regression, Muscle function, Posture monitoring, Probability, Recovery, Rehabilitation, Reliability, Retrospective study, Stroke, Stroke patient, Test retest reliability, Therapy, Total goal directed movement, Upper extremities, Upper limb, Upper-limb, Wolf motor function test

Under intrauterine growth restriction (IUGR), abnormal attainment of the nutrients and oxygen by the fetus restricts the normal evolution of the prenatal causing in many cases high morbidity being one of the top-ten causes of neonatal death. The current gold standards in hospitals to detect this relevant problem is the clinical observation by echography, cardiotocography and Doppler. These qualitative techniques are not conclusive and requires risky invasive fetal scalp blood testing and/or amniocentesis. We developed micro-implantable multiparametric electrochemical sensors for measuring ischemia in real time in fetal tissue and vascular. This implantable technology is designed to continuous monitoring for an early detection of ischemia to avoid potential fetal injury. Two miniaturized electrochemical sensors were developed based on oxygen and pH detection. The sensors were optimized in vitro under controlled concentration, to assess the selectivity and sensitivity required. The sensors were then validated in vivo in the ewe fetus model, by means of their insertion in the muscle leg and inside the iliac artery of the fetus. Ischemia was achieved by gradually obstructing the umbilical cord to regulate the amount of blood reaching the fetus. An important challenge in fetal monitoring is the detection of low levels of oxygen and pH changes under ischemic conditions, requiring high sensitivity sensors. Significant differences were observed in both; pH and pO(2) sensors under changes from normoxia to hypoxia states in the fetus tissue and vascular with both sensors. Herein, we demonstrate the feasibility of the developed sensors for future fetal monitoring in medical applications.

JTD Keywords: electrochemical biosensor, implantable sensor, in vivo validation, ischemia detection, tissue and vascular monitoring, Animal experiment, Animal model, Animal tissue, Article, Blood-gases, Brain, Classification, Controlled study, Diagnosis, Doppler, Early diagnosis, Electrochemical analysis, Electrochemical biosensor, Ewe, Feasibility study, Female, Fetus, Fetus disease, Fetus monitoring, Gestational age, Hypoxemia, Iliac artery, Implantable sensor, In vivo validation, Intrauterine growth restriction, Intrauterine growth retardation, Ischemia detection, Leg muscle, Management, Nonhuman, Oxygen consumption, Ph, Ph and oxygen detection, Ph measurement, Process optimization, Sheep, Tissue and vascular monitoring, Umbilical-cord occlusion

Cardiomyopathies diseases affects a great number of the elderly population. An adequate identification of the etiology of a cardiomyopathy patient is still a challenge. The aim of this study was to classify patients by their etiology in function of indexes extracted from the characterization of the pulse transit time (PTT). This time series represents the time taken by the pulse pressure to propagate through the length of the arterial tree and corresponding to the time between R peak of ECG and the mid-point of the diastolic to systolic slope in the blood pressure signal. For each patient, the PTT time series was extracted. Thirty cardiomyopathy patients (CMP) classified as ischemic (ICM - 15 patients) and dilated (DCM - 15 patients) were analyzed. Forty-three healthy subjects (CON) were used as a reference. The PTT time series was characterized through statistical descriptive indices and the joint symbolic dynamics method. The best indices were used to build support vector machine models. The optimal model to classify ICM versus DCM patients achieved 89.6% accuracy, 78.5% sensitivity, and 100% specificity. When comparing CMP patients and CON subjects, the best model achieved 91.3% accuracy, 91.3% sensitivity, and 88.3% specificity. Our results suggests a significantly lower pulse transit time in ischemic patients.Clinical relevance - This study analyzed the suitability of the pulse transit time for the classification of ICM and DCM patients. © 2021 IEEE.

JTD Keywords: Aged, Blood pressure, Cardiomyopathies, Cardiomyopathy, Cardiomyopathy, dilated, Congestive cardiomyopathy, Human, Humans, Pulse wave, Pulse wave analysis, Support vector machine

In clinical practice, when a patient is undergoing mechanical ventilation, it is important to identify the optimal moment for extubation, minimizing the risk of failure. However, this prediction remains a challenge in the clinical process. In this work, we propose a new protocol to study the extubation process, including the electromyographic diaphragm signal (diaEMG) recorded through 5-channels with surface electrodes around the diaphragm muscle. First channel corresponds to the electrode on the right. A total of 40 patients in process of withdrawal of mechanical ventilation, undergoing spontaneous breathing tests (SBT), were studied. According to the outcome of the SBT, the patients were classified into two groups: successful (SG: 19 patients) and failure (FG: 21 patients) groups. Parameters extracted from the envelope of each channel of diaEMG in time and frequency domain were studied. After analyzing all channels, the second presented maximum differences when comparing the two groups of patients, with parameters related to root mean square (p = 0.005), moving average (p = 0.001), and upward slope (p = 0.017). The third channel also presented maximum differences in parameters as the time between maximum peak (p = 0.004), and the skewness (p = 0.027). These results suggest that diaphragm EMG signal could contribute to increase the knowledge of the behaviour of respiratory system in these patients and improve the extubation process.Clinical Relevance - This establishes the characterization of success and failure patients in the extubation process. © 2021 IEEE.

JTD Keywords: classification, recognition, Airway extubation, Artificial ventilation, Clinical practices, Clinical process, Diaphragm, Diaphragm muscle, Diaphragms, Electrodes, Electromyographic, Extubation, Frequency domain analysis, Human, Humans, Maximum differences, Mechanical ventilation, New protocol, Respiration, artificial, Respiratory system, Risk of failure, Spontaneous breathing, Surface electrode, Surface emg signals, Thorax, Ventilation, Ventilator weaning

Formalin-fixed paraffin embedding (FFPE) is the most widespread long-term tissue preservation approach. Here, we report a procedure to perform genome-wide spatial analysis of mRNA in FFPE-fixed tissue sections, using well-established, commercially available methods for imaging and spatial barcoding using slides spotted with barcoded oligo(dT) probes to capture the 3' end of mRNA molecules in tissue sections. We applied this method for expression profiling and cell type mapping in coronal sections from the mouse brain to demonstrate the method's capability to delineate anatomical regions from a molecular perspective. We also profiled the spatial composition of transcriptomic signatures in two ovarian carcinosarcoma samples, exemplifying the method's potential to elucidate molecular mechanisms in heterogeneous clinical samples. Finally, we demonstrate the applicability of the assay to characterize human lung and kidney organoids and a human lung biopsy specimen infected with SARS-CoV-2. We anticipate that genome-wide spatial gene expression profiling in FFPE biospecimens will be used for retrospective analysis of biobank samples, which will facilitate longitudinal studies of biological processes and biomarker discovery.© 2021 The Authors.

JTD Keywords: colonic transit, gut, intestinal motility, ld score regression, metaanalysis, nervous-system, neurotrophic factor, population, severity, Covid-19, Ffpe, Genome-wide, Irritable-bowel-syndrome, Mouse brain, Organoids, Ovarian carcinosarcoma, Pfa, Sars-cov-2, Spatial transcriptomics, Visium

Most lectins bind carbohydrate ligands with relatively low affinity, making the identification of optimal ligands challenging. Here we introduce a point accumulation in nanoscale topography (PAINT) super-resolution microscopy method to capture weak glycan-lectin interactions at the single-molecule level in living cells (Glyco-PAINT). Glyco-PAINT exploits weak and reversible sugar binding to directly achieve single-molecule detection and quantification in cells and is used to establish the relative kon and koff rates of a synthesized library of carbohydrate-based probes, as well as the diffusion coefficient of the receptor-sugar complex. Uptake of ligands correlates with their binding affinity and residence time to establish structure-function relations for various synthetic glycans. We reveal how sugar multivalency and presentation geometry can be optimized for binding and internalization. Overall, Glyco-PAINT represents a powerful approach to study weak glycan-lectin interactions on the surface of living cells, one that can be potentially extended to a variety of lectin-sugar interactions.© 2021. The Author(s), under exclusive licence to Springer Nature America, Inc.

JTD Keywords: dc-sign, density, dimerization, endocytosis, lateral mobility, ligand-binding, mannose receptor, proteins, recognition, Animal, Animals, Cell membrane, Cell membrane permeability, Chemistry, Cho cell line, Cho cells, Cricetulus, Cysteine-rich domain, Kinetics, Lectin, Lectins, Ligand, Ligands, Molecular library, Multivariate analysis, Polysaccharide, Polysaccharides, Procedures, Protein binding, Single molecule imaging, Small molecule libraries, Structure activity relation, Structure-activity relationship

High ambient temperature and humidity greatly increase the risk of hyperthermia and mortality, particularly in infants, who are especially prone to dehydration. World areas at high risk of heat stress include many of the low-and middle-income countries (LMICs) where most of their inhabitants have no access to air conditioning. This study aimed to design, evaluate, and test a novel low-cost and easy-to-assemble device aimed at preventing the risk of infant hyperthermia in LMICs. The device is based on optimizing negative heat transfer from a small amount of ice and transferring it directly to the infant by airflow of refrigerated air. As a proof of concept, a device was assembled mainly using recycled materials, and its performance was assessed under laboratory-controlled conditions in a climatic chamber mimicking realistic stress conditions of high temperature and humidity. The device, which can be assembled by any layperson using easily available materials, provided sufficient refrigerating capacity for several hours from just 1–2 kg of ice obtained from a domestic freezer. Thus, application of this novel device may serve to attenuate the adverse effects of heat stress in infants, particularly in the context of the evolving climatic change trends. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.

JTD Keywords: air conditioning, ambient-temperature, death, heat, heat index, heat shock, heatwave, high ambient temperature, hyperthermia, low-cost refrigeration, low-middle income countries, mortality, negative heat transfer, Air conditioning, Algorithm, Article, Climate change, Cost benefit analysis, Environmental temperature, Heat index, Heat shock, Heat stress, Heat transfer, Heating, Heatwave, High ambient temperature, High temperature, Humidity, Hyperthermia, Low income country, Low-cost refrigeration, Low-middle income countries, Middle income country, Middle-income countries, Negative heat transfer, Prevention study, Refrigeration, Temperature stress, Thawing

Peptide-based supramolecular systems chemistry seeks to mimic the ability of life forms to use conserved sets of building blocks and chemical reactions to achieve a bewildering array of functions. Building on the design principles for short peptide-based nanomaterials with properties, such as self-assembly, recognition, catalysis, and actuation, are increasingly available. Peptide-based supramolecular systems chemistry is starting to address the far greater challenge of systems-level design to access complex functions that emerge when multiple reactions and interactions are coordinated and integrated. We discuss key features relevant to systems-level design, including regulating supramolecular order and disorder, development of active and adaptive systems by considering kinetic and thermodynamic design aspects and combinatorial dynamic covalent and noncovalent interactions. Finally, we discuss how structural and dynamic design concepts, including preorganization and induced fit, are critical to the ability to develop adaptive materials with adaptive and tunable photonic, electronic, and catalytic properties. Finally, we highlight examples where multiple features are combined, resulting in chemical systems and materials that display adaptive properties that cannot be achieved without this level of integration.

JTD Keywords: aromatic peptide, biological-properties, chemical control, conformational-analysis, electronic transport, mechanical-properties, perylene bisimide, pro-hyp sequences, residues determine, Self-assembling peptide

In many physiological situations, BAR proteins reshape membranes with pre-existing curvature (templates), contributing to essential cellular processes. However, the mechanism and the biological implications of this reshaping process remain unclear. Here we show, both experimentally and through modelling, that BAR proteins reshape low curvature membrane templates through a mechanochemical phase transition. This phenomenon depends on initial template shape and involves the co-existence and progressive transition between distinct local states in terms of molecular organization (protein arrangement and density) and membrane shape (template size and spherical versus cylindrical curvature). Further, we demonstrate in cells that this phenomenon enables a mechanotransduction mode, in which cellular stretch leads to the mechanical formation of membrane templates, which are then reshaped into tubules by BAR proteins. Our results demonstrate the interplay between membrane mechanics and BAR protein molecular organization, integrating curvature sensing and generation in a comprehensive framework with implications for cell mechanical responses.

JTD Keywords: aggregation, amphiphysin, domains, vesicles, Article, Cell, Cell component, Curvature, Detection method, Geomembrane, Mechanotransduction, Membrane, Molecular analysis, Phase transition, Physiology, Protein, Self organization

The identification of key components relevant to sensory perception of quality from commercial chocolate samples was accomplished after chemometric processing of GC×GC-MS (Comprehensive Two-dimensional Gas Chromatography with Mass Spectrometric Detection) profiles corresponding to HS-SPME (Headspace Solid Phase Microextraction) extracts of the samples. Descriptive sensory evaluation of samples was carried out using Optimized Descriptive Profile (ODP) procedures, where sensory attributes of 24 commercial chocolate samples were used to classify them in two classes (low and high chocolate flavor). 2D Fisher Ratio analysis was applied to four-way chromatographic data tensors (1st dimension retention time 1tR × 2nd dimension retention time 2tR × m/z × sample), to identify the crucial areas on the chromatograms that resulted on ODP class separation on Principal Component Analysis (PCA) scores plot. Comparing the relevant sections of the chromatograms to the analysis of the corresponding mass spectra, it was possible to assess that most of the information regarding the sample main sensory attributes can be related to only 14 compounds (2,5-dimethylpyrazine, 2,6-dimethyl-4-heptanol, 1-octen-3-ol, trimethylpyrazine, β-pinene, o-cimene, 2-ethyl-3,5-dimethylpyrazine, tetramethylpyrazine, benzaldehyde, 1,3,5-trimethylbenzene, 6-methyl-5-hepten-2-one, limonene, benzeneethanol and 1,1-dimethylbutylbenzene) among the complex blend of volatiles found on these extremely complex samples.

JTD Keywords: classification, cocoa, dark chocolate, feature-selection, fisher ratio, gcxgc-ms, impact, olfactometry, principal component analysis, sensorial analysis, Chocolate flavor, Fisher ratio, Flight mass-spectrometry, Gc×gc-ms, Principal component analysis, Sensorial analysis

Gas chromatography—ion mobility spectrometry (GC-IMS) allows the fast, reliable, and inexpensive chemical composition analysis of volatile mixtures. This sensing technology has been successfully employed in food science to determine food origin, freshness and preventing alimentary fraud. However, GC-IMS data is highly dimensional, complex, and suffers from strong non-linearities, baseline problems, misalignments, peak overlaps, long peak tails, etc., all of which must be corrected to properly extract the relevant features from samples. In this work, a pipeline for signal pre-processing, followed by four different approaches for feature extraction in GC-IMS data, is presented. More precisely, these approaches consist of extracting data features from: (1) the total area of the reactant ion peak chromatogram (RIC); (2) the full RIC response; (3) the unfolded sample matrix; and (4) the ion peak volumes. The resulting pipelines for data processing were applied to a dataset consisting of two different quality class Iberian ham samples, based on their feeding regime. The ability to infer chemical information from samples was tested by comparing the classification results obtained from partial least-squares discriminant analysis (PLS-DA) and the samples’ variable importance for projection (VIP) scores. The choice of a feature extraction strategy is a trade-off between the amount of chemical information that is preserved, and the computational effort required to generate the data models.

JTD Keywords: authenticity, classification, electronic-nose, feature extraction, food analysis, gc-ims, headspace, least-squares, models, pld-da, pre-processing, quality, sensory analysis, wine, Feature extraction, Food analysis, Gc-ims, Hs-gc-ims, Pld-da, Pre-processing

The human olfactory system remains one of the most challenging biological systems to replicate. Humans use it without thinking, where it can equally offer protection from harm and bring enjoyment in equal measure. It is the system’s ability to detect and analyze complex odors, without the need for specialized infra-structure, that is the envy of many scientists. The field of artificial olfaction has recruited and stimulated interdisciplinary research and commercial development for several applications that include malodor measurement, medical diagnostics, food and beverage quality, environment and security. Over the last century, innovative engineers and scientists have been focused on solving a range of problems associated with measurement and control of odor. The IEEE Sensors Journal has published Special Issues on olfaction in 2002 and 2012. Here we continue that coverage. In this article, we summarize early work in the 20th Century that served as the foundation upon which we have been building our odor-monitoring instrumental and measurement systems. We then examine the current state of the art that has been achieved over the last two decades as we have transitioned into the 21st Century. Much has been accomplished, but great progress is needed in sensor technology, system design, product manufacture and performance standards. In the final section, we predict levels of performance and ubiquitous applications that will be realized during in the mid to late 21st Century.

JTD Keywords: air-quality, breath analysis, calibration transfer, chemical sensor arrays, chemosensor arrays, drift compensation, electronic nose, gas sensors, headspace sampling, machine learning, machine olfaction, odor detection, plume structure, voc analysis, Artificial olfaction, Electrodes, Electronic nose, Electronic nose technology, Headspace sampling, Instruments, Machine learning, Machine olfaction, Monitoring, Odor detection, Olfactory, Sensor phenomena and characterization, Sensors, Temperature sensors, Voc analysis

To increase compliance with colorectal cancer screening programs and to reduce the recommended screening age, cheaper and easy non‐invasiveness alternatives to the fecal immunochemical test should be provided. Following the PRISMA procedure of studies that evaluated the metabolome and volatilome signatures of colorectal cancer in human urine samples, an exhaustive search in PubMed, Web of Science, and Scopus found 28 studies that met the required criteria. There were no restrictions on the query for the type of study, leading to not only colorectal cancer samples versus control comparison but also polyps versus control and prospective studies of surgical effects, CRC staging and comparisons of CRC with other cancers. With this systematic review, we identified up to 244 compounds in urine samples (3 shared compounds between the volatilome and metabolome), and 10 of them were relevant in more than three articles. In the meta-analysis, nine studies met the criteria for inclusion, and the results combining the case‐control and the pre‐/post‐surgery groups, eleven compounds were found to be relevant. Four upregulated metabolites were identified, 3‐hydroxybutyric acid, L‐dopa, L‐histidinol, and N1, N12‐ diacetylspermine and seven downregulated compounds were identified, pyruvic acid, hydroquinone, tartaric acid, and hippuric acid as metabolites and butyraldehyde, ether, and 1,1,6‐ trimethyl‐1,2‐dihydronaphthalene as volatiles.

JTD Keywords: biomarkers, breast, chromatography, colorectal cancer, diagnosis, markers, meta-analysis, metabolomics, metabonomics, n-1,n-12-diacetylspermine, nucleosides, systematic review, urine, validation, volatilomics, Colorectal cancer, Early-stage, Metabolomics, Meta‐analysis, Systematic review, Urine, Volatilomics

Organ-on-a-chip (OOC) devices offer new approaches for metabolic disease modeling and drug discovery by providing biologically relevant models of tissues and organs in vitro with a high degree of control over experimental variables for high-content screening applications. Yet, to fully exploit the potential of these platforms, there is a need to interface them with integrated non-labeled sensing modules, capable of monitoring, in situ, their biochemical response to external stimuli, such as stress or drugs. In order to meet this need, we aim here to develop an integrated technology based on coupling a localized surface plasmon resonance (LSPR) sensing module to an OOC device to monitor the insulin in situ secretion in pancreatic islets, a key physiological event that is usually perturbed in metabolic diseases such as type 2 diabetes (T2D). As a proof of concept, we developed a biomimetic islet-on-a-chip (IOC) device composed of mouse pancreatic islets hosted in a cellulose-based scaffold as a novel approach. The IOC was interfaced with a state-of-the-art on-chip LSPR sensing platform to monitor the in situ insulin secretion. The developed platform offers a powerful tool to enable the in situ response study of microtissues to external stimuli for applications such as a drug-screening platform for human models, bypassing animal testing.

JTD Keywords: biosensor, cytoarchitecture, dna hybridization, gelatin, in situ insulin monitoring, langerhans, lspr sensors, microfluidic device, organ-on-a-chip, parallel, platform, scaffold, Animals, Biosensing techniques, Diabetes mellitus, type 2, Drug discovery, Drug evaluation, preclinical, Human pancreatic-islets, Humans, In situ insulin monitoring, Insulin secretion, Insulins, Lab-on-a-chip devices, Lspr sensors, Oligonucleotide array sequence analysis, Organ-on-a-chip, Surface plasmon resonance

Background & Aims: MicroRNAs (miRNAs) circulate in several body fluids and can be useful biomarkers. The aim of this study was to identify blood-circulating miRNAs associated with cirrhosis progression and acute-on-chronic liver failure (ACLF). Methods: Using high-throughput screening of 754 miRNAs, serum samples from 45 patients with compensated cirrhosis, decompensated cirrhosis, or ACLF were compared with those from healthy individuals (n = 15). miRNA levels were correlated with clinical parameters, organ failure, and disease progression and outcome. Dysregulated miRNAs were evaluated in portal and hepatic vein samples (n = 33), liver tissues (n = 17), and peripheral blood mononuclear cells (PBMCs) (n = 16). Results: miRNA screening analysis revealed that circulating miRNAs are dysregulated in cirrhosis progression, with 51 miRNAs being differentially expressed among all groups of patients. Unsupervised clustering and principal component analysis indicated that the main differences in miRNA expression occurred at decompensation, showing similar levels in patients with decompensated cirrhosis and those with ACLF. Of 43 selected miRNAs examined for differences among groups, 10 were differentially expressed according to disease progression. Moreover, 20 circulating miRNAs were correlated with model for end-stage liver disease and Child-Pugh scores. Notably, 11 dysregulated miRNAs were associated with kidney or liver failure, encephalopathy, bacterial infection, and poor outcomes. The most severely dysregulated miRNAs (i.e. miR-146a5p, miR-26a-5p, and miR-191-5p) were further evaluated in portal and hepatic vein blood and liver tissue, but showed no differences. However, PBMCs from patients with cirrhosis showed significant downregulation of miR-26 and miR-146a, suggesting a extrahepatic origin of some circulating miRNAs. Conclusions: This study is a repository of circulating miRNA data following cirrhosis progression and ACLF. Circulating miRNAs were profoundly dysregulated during the progression of chronic liver disease, were associated with failure of several organs and could have prognostic utility. Lay summary: Circulating miRNAs are small molecules in the blood that can be used to identify or predict a clinical condition. Our study aimed to identify miRNAs for use as biomarkers in patients with cirrhosis or acute-on-chronic liver failure. Several miRNAs were found to be dysregulated during the progression of disease, and some were also related to organ failure and disease-related outcomes. (C) 2021 The Author(s). Published by Elsevier B.V. on behalf of European Association for the Study of the Liver (EASL).

JTD Keywords: aclf, acute-on-chronic liver failure, alt, alanine aminotransferase, ast, aspartate aminotransferase, biomarkers, chronic liver disease, cxcl10, c-x-c motif chemokine ligand 10, ef clif, european foundation for the study of chronic liver failure, foxo, forkhead box o, inr, international normalised ratio, ldh, lactate dehydrogenase, liver decompensation, mapk, mitogen-activated protein kinase, meld, model for end-stage liver disease, nash, non-alcoholic steatohepatitis, non-coding rnas, pbmcs, peripheral blood mononuclear cells, pca, principal component analysis, tgf, transforming growth factor, tips, transjugular intrahepatic portosystemic shunt, Biomarkers, Chronic liver disease, Expression, Liver decompensation, Markers, Mir-146a, Non-coding rnas, Qpcr, quantitative pcr

Plaques of the amyloid beta (A beta) peptide are a pathological hallmark of Alzheimer's disease (AD), the most common form of dementia. Mutations in A beta also cause familial forms of AD (fAD). Here, we use deep mutational scanning to quantify the effects of >14,000 mutations on the aggregation of A beta. The resulting genetic landscape reveals mechanistic insights into fibril nucleation, including the importance of charge and gatekeeper residues in the disordered region outside of the amyloid core in preventing nucleation. Strikingly, unlike computational predictors and previous measurements, the empirical nucleation scores accurately identify all known dominant fAD mutations in A beta, genetically validating that the mechanism of nucleation in a cell-based assay is likely to be very similar to the mechanism that causes the human disease. These results provide the first comprehensive atlas of how mutations alter the formation of any amyloid fibril and a resource for the interpretation of genetic variation in A beta.

JTD Keywords: aggregation, kinetics, oligomers, onset, rates, state, Aggregation, Alzheimer disease, Alzheimer's, Amyloid, Amyloid beta-peptides, Computational biology, Deep mutagenesis, Dna mutational analysis, Genetics, Genomics, High-throughput nucleotide sequencing, Kinetics, Mutation, Nucleation, Oligomers, Onset, Plasmids, Precursor protein, Rates, S. cerevisiae, Saccharomyces cerevisiae, State, Systems biology

Alzheimer's disease (AD) is a neurodegenerative disorder, characterized by a functional deterioration of the brain. Currently, there are selected biomarkers for its diagnosis in cerebrospinal fluid. However, its extraction has several disadvantages for the patient. Therefore, there is an urgent need for a detection method using sensitive and selective blood-based biomarkers. Kynurenic acid (KYNA) is a potential biomarker candidate for this purpose. The alteration of the KYNA levels in blood has been related with inflammatory processes in the brain, produced as a protective function when neurons are damaged. This paper describes a novel electrochemical immunosensor for KYNA detection, based on successive functionalization multi-electrode array. The resultant sensor was characterized by cyclic voltammetry (CV), chronoamperometry (CA), and electrochemical impedance spectroscopy (EIS). The proposed biosensor detects KYNA within a linear calibration range from 10 pM to 100 nM using CA and EIS, obtaining a limit of detection (LOD) of 16.9 pM and 37.6 pM in buffer, respectively, being the lowest reported LOD for this biomarker. Moreover, to assess our device closer to the real application, the developed immunosensor was also tested under human serum matrix, obtaining an LOD of 391.71 pM for CA and 278.8 pM for EIS with diluted serum.

JTD Keywords: alzheimer’s disease (ad), blood analysis, chronoamperometry (ca), electrochemical biosensor, electrochemical impedance spectroscopy (eis), immunosensor, in vitro diagnosis (ivd), kynurenic acid (kyna), Alzheimer’s disease (ad), Blood analysis, Chronoamperometry (ca), Electrochemical biosensor, Electrochemical impedance spectroscopy (eis), Immunosensor, In vitro diagnosis (ivd), Kynurenic acid (kyna), Point of care diagnosis (poc)

Goel and colleagues show that CDK4/6 inhibition induces global chromatin changes mediated by AP-1 factors, which mediate key biological and clinical effects in breast cancer. Pharmacologic inhibitors of cyclin-dependent kinases 4 and 6 (CDK4/6) were designed to induce cancer cell cycle arrest. Recent studies have suggested that these agents also exert other effects, influencing cancer cell immunogenicity, apoptotic responses and differentiation. Using cell-based and mouse models of breast cancer together with clinical specimens, we show that CDK4/6 inhibitors induce remodeling of cancer cell chromatin characterized by widespread enhancer activation, and that this explains many of these effects. The newly activated enhancers include classical super-enhancers that drive luminal differentiation and apoptotic evasion, as well as a set of enhancers overlying endogenous retroviral elements that are enriched for proximity to interferon-driven genes. Mechanistically, CDK4/6 inhibition increases the level of several activator protein-1 transcription factor proteins, which are in turn implicated in the activity of many of the new enhancers. Our findings offer insights into CDK4/6 pathway biology and should inform the future development of CDK4/6 inhibitors.

JTD Keywords: Abemaciclib, Androgen receptor, Animal experiment, Animal model, Animal tissue, Apoptosis, Article, Breast cancer, C-jun, Cancer cell, Carcinoembryonic antigen related cell adhesion molecule 1, Caspase 3, Cell cycle arrest, Cells, Chromatin, Chromatin immunoprecipitation, Controlled study, Cyclin dependent kinase 4, Cyclin dependent kinase 6, Dna damage, Epidermal growth factor receptor 2, Estrogen receptor, Female, Flow cytometry, Fulvestrant, Hla drb1 antigen, Human, Human cell, Immunoblotting, Immunogenicity, Immunoprecipitation, Interferon, Luciferase assay, Mcf-7 cell line, Mda-mb-231 cell line, Microarray analysis, Morphogenesis, Mouse, Nonhuman, Palbociclib, Protein, Protein expression, Rb, Resistance, Rna polymerase ii, Rna sequence, Selective-inhibition, Senescence, Short tandem repeat, Signal transduction, Tamoxifen, Transcription elongation, Transcription factor, Transcription factor ap 1, Transcriptome, Tumor biopsy, Tumor differentiation, Tumor spheroid, Tumor xenograft, Vinculin, Whole exome sequencing

Conventional drug solubilization strategies limit the understanding of the full potential of poorly water-soluble drugs during drug screening. Here, we propose a screening approach in which poorly water-soluble drugs are entrapped in poly(2-(methacryloyloxyethyl phosphorylcholine)-poly(2-(diisopropylaminoethyl methacryate) (PMPC-PDPA) polymersomes (POs) to enhance drug solubility and facilitate intracellular delivery. By using a human pediatric glioma cell model, we demonstrated that PMPC-PDPA POs mediated intracellular delivery of cytotoxic and epigenetic drugs by receptor-mediated endocytosis. Additionally, when delivered in combination, drug-loaded PMPC-PDPA POs triggered both an enhanced drug efficacy and synergy compared to that of a conventional combinatorial screening. Hence, our comprehensive synergy analysis illustrates that our screening methodology, in which PMPC-PDPA POs are used for intracellular codelivery of drugs, allows us to identify potent synergistic profiles of anticancer drugs.

JTD Keywords: Combination therapy, Drug screening, Drug solubilization, Intracellular drug delivery, Polymeric nanoparticles, Synergy analysis

Intratumour heterogeneity due to cancer cell clonal evolution and microenvironment composition and tumor differences due to genetic variations between patients suffering of the same cancer pathology play a crucial role in patient response to therapies. This study is oriented to show that matrix-assisted laser-desorption ionization-Mass spectrometry imaging (MALDI-MSI), combined with an advanced multivariate data processing pipeline can be used to discriminate subtle variations between highly similar colorectal tumors. To this aim, experimental tumors reproducing the emergence of drug-resistant clones were generated in athymic mice using subcutaneous injection of different mixes of two isogenic cell lines, the irinotecan-resistant HCT116-SN50 (R) and its sibling human colon adenocarcinoma sensitive cell line HCT116 (S). Because irinotecan-resistant and irinotecan-sensitive are derived from the same original parental HCT116 cell line, their genetic characteristics and molecular compositions are closely related. The multivariate data processing pipeline proposed relies on three steps: (a) multiset multivariate curve resolution (MCR) to separate biological contributions from background; (b) multiset K-means segmentation using MCR scores of the biological contributions to separate between tumor and necrotic parts of the tissues; and (c) partial-least squares discriminant analysis (PLS-DA) applied to tumor pixel spectra to discriminate between R and S tumor populations. High levels of correct classification rates (0.85), sensitivity (0.92) and specificity (0.77) for the PLS-DA classification model were obtained. If previously labelled tissue is available, the multistep modeling strategy proposed constitutes a good approach for the identification and characterization of highly similar phenotypic tumor subpopulations that could be potentially applicable to any kind of cancer tissue that exhibits substantial heterogeneity. © 2019 Elsevier B.V.

JTD Keywords: Chemometrics, Colorectal cancer, MALDI imaging, Multivariate analysis, Tumor heterogeneity

In this work, we study the mechanics of metamaterial sheets inspired by the pellicle of Euglenids. They are composed of interlocking elastic rods which can freely slide along their edges. We characterize the kinematics and the mechanics of these structures using the special Cosserat theory of rods and by assuming axisymmetric deformations of the tubular assembly. Through an asymptotic expansion, we investigate both structures that comprise a discrete number of rods and the limit case of a sheet composed by infinitely many rods. We apply our theoretical framework to investigate the stability of these structures in the presence of an axial load. Through a linear analysis, we compute the critical buckling force for both the discrete and the continuous case. For the latter, we also perform a numerical post-buckling analysis, studying the non-linear evolution of the bifurcation through finite elements simulations.

JTD Keywords: Biomimetic structures, Elastic structures, Helical rods, Mechanical instabilities, Metamaterials, Post-buckling analysis

Heart diseases are the leading cause of death in developed countries. Ascertaining the etiology of cardiomyopathies is still a challenge. The objective of this study was to classify cardiomyopathy patients through cardio, respiratory and vascular variability analysis, considering the vascular activity as the input and output of the baroreflex response. Forty-one cardiomyopathy patients (CMP) classified as ischemic (ICM, 24 patients) and dilated (DCM, 17 patients) were analyzed. Thirty-nine elderly control subjects (CON) were used as reference. From the electrocardiographic, respiratory flow, and blood pressure signals, following temporal series were extracted: beat-to-beat intervals (BBI), total respiratory cycle time series (TT), and end– systolic (SBP) and diastolic (DBP) blood pressure amplitudes, respectively. Three-dimensional representation of the cardiorespiratory and vascular activities was characterized geometrically, by fitting a polygon that contains 95% of data, and by statistical descriptive indices. The best classifiers were used to build support vector machine models. The optimal model to classify ICM versus DCM patients achieved 92.7% accuracy, 94.1% sensitivity, and 91.7% specificity. When comparing CMP patients and CON subjects, the best model achieved 86.2% accuracy, 82.9% sensitivity, and 89.7% specificity. These results suggest a limited ability of cardiac and respiratory systems response to regulate the vascular variability in these patients.

JTD Keywords: Time series analysis, Support vector machines, Blood pressure, Sensitivity, Indexes, Electrocardiography, Kernel

A novel ECG-derived respiration (EDR) approach is presented to efficiently estimate the respiratory rate. It combines spatial rotations and magnitude variations of the heart's electrical vector due to respiration. Orthogonal leads X, Y and Z from 10 volunteers were analyzed during a tilt table test. The largest vector magnitude (VM) within each QRS loop was assessed, and its 3D coordinates were converted into unit quaternion qb. Angular distances between these quaternions and the axes of the reference coordinate system, θ x , θ y and θ z , were then computed as EDR signals to track their relative variations caused by respiration. The respiratory rate was estimated on the spectrum of individual EDR signals obtained from the angular distances and VM time-series, but also on EDR signals obtained by principal component analysis (PCA). Relative errors (eR) to the reference respiratory signal exhibited relatively low values. The combination of EDR signals' spectrum {θ X ,θ Y, θ Z , VM} (eR=0.63±4.15%) and individual signals derived from θ X (e R =0.46±8.22%) and PCA (eR=0.36±6.58%) achieved the overall best results. The proposed method represents a computationally efficient alternative to other EDR approaches, but its robustness should be further investigated. The method could be enhanced if combined with other features tracking morphological changes induced by respiration.

JTD Keywords: Heart, Three-dimensional displays, Quaternions, Robustness, Computational efficiency, Cardiology, Principal component analysis

Adult zebrafish, in contrast to mammals, are able to regenerate their hearts in response to injury or experimental amputation. Our understanding of the cellular and molecular bases that underlie this process, although fragmentary, has increased significantly over the last years. However, the role of the extracellular matrix (ECM) during zebrafish heart regeneration has been comparatively rarely explored. Here, we set out to characterize the ECM protein composition in adult zebrafish hearts, and whether it changed during the regenerative response. For this purpose, we first established a decellularization protocol of adult zebrafish ventricles that significantly enriched the yield of ECM proteins. We then performed proteomic analyses of decellularized control hearts and at different times of regeneration. Our results show a dynamic change in ECM protein composition, most evident at the earliest (7 days post-amputation) time-point analyzed. Regeneration associated with sharp increases in specific ECM proteins, and with an overall decrease in collagens and cytoskeletal proteins. We finally tested by atomic force microscopy that the changes in ECM composition translated to decreased ECM stiffness. Our cumulative results identify changes in the protein composition and mechanical properties of the zebrafish heart ECM during regeneration.

JTD Keywords: Animal models, Atomic force microscopy, Cardiovascular disease, Cardiovascular function or biology, Developmental biology, Extracellular matrix, Heart regeneration, Proteomic analysis

The intermittency of the instantaneous concentration of a turbulent chemical plume is a fundamental cue for estimating the chemical source distance using chemical sensors. Such estimate is useful in applications such as environmental monitoring or localization of fugitive gas emissions by mobile robots or sensor networks. However, the inherent low-pass filtering of metal oxide (MOX) gas sensors-typically used in odor-guided robots and dense sensor networks due to their low cost, weight and size-hinders the quantification of concentration intermittency. In this paper, we design a digital differentiator to invert the low-pass dynamics of the sensor response, thus obtaining a much faster signal from which the concentration intermittency can be effectively computed. Using a fast photo-ionization detector as a reference instrument, we demonstrate that the filtered signal is a good approximation of the instantaneous concentration in a real turbulent plume. We then extract transient features from the filtered signal-the so-called “bouts”-to predict the chemical source distance, focusing on the optimization of the filter parameters and the noise threshold to make the predictions robust against changing wind conditions. This represents an advantage over previous bout-based models which require wind measurements-typically taken with expensive and bulky anemometers-to produce accurate predictions. The proposed methodology is demonstrated in a wind tunnel scenario where a MOX sensor is placed at various distances downwind of an emitting chemical source and the wind speed varies in the range 10-34 cm/s. The results demonstrate that models optimized with our methodology can provide accurate source distance predictions at different wind speeds.

JTD Keywords: Gas detectors, Chemical sensors, Signal processing, Machine learning, Time series analysis

Cardiovascular diseases are one of the most common causes of death; however, the early detection of patients at high risk of sudden cardiac death (SCD) remains an issue. The aim of this study was to analyze the cardio-vascular couplings based on heart rate variability (HRV) and blood pressure variability (BPV) analyses in order to introduce new indices for noninvasive risk stratification in idiopathic dilated cardiomyopathy patients (IDC). High-resolution electrocardiogram (ECG) and continuous noninvasive blood pressure (BP) signals were recorded in 91 IDC patients and 49 healthy subjects (CON). The patients were stratified by their SCD risk as high risk (IDCHR) when after two years the subject either died or suffered life-threatening complications, and as low risk (IDCLR) when the subject remained stable during this period. Values were extracted from ECG and BP signals, the beat-to-beat interval, and systolic and diastolic blood pressure, and analyzed using the segmented Poincaré plot analysis (SPPA), the high-resolution joint symbolic dynamics (HRJSD) and the normalized short time partial directed coherence methods. Support vector machine (SVM) models were built to classify these patients according to SCD risk. IDCHR patients presented lowered HRV and increased BPV compared to both IDCLR patients and the control subjects, suggesting a decrease in their vagal activity and a compensation of sympathetic activity. Both, the cardio -systolic and -diastolic coupling strength was stronger in high-risk patients when comparing with low-risk patients. The cardio-systolic coupling analysis revealed that the systolic influence on heart rate gets weaker as the risk increases. The SVM IDCLR vs. IDCHR model achieved 98.9% accuracy with an area under the curve (AUC) of 0.96. The IDC and the CON groups obtained 93.6% and 0.94 accuracy and AUC, respectively. To simulate a circumstance in which the original status of the subject is unknown, a cascade model was built fusing the aforementioned models, and achieved 94.4% accuracy. In conclusion, this study introduced a novel method for SCD risk stratification for IDC patients based on new indices from coupling analysis and non-linear HRV and BPV. We have uncovered some of the complex interactions within the autonomic regulation in this type of patient.

JTD Keywords: Idiopathic dilated cardiomyopathy, Heart rate variability, Blood pressure variability, Coupling analysis, Sudden cardiac death, Risk stratification

Continuous adventitious sounds (CAS) are commonly observed in obstructive pulmonary diseases and are of great clinical interest. However, their evaluation is generally subjective. We have previously developed an automatic CAS segmentation and classification algorithm for CAS recorded on the chest surface. The aim of this study is to establish whether these pulmonary CAS can be identified in a similar way using a tracheal microphone. Respiratory sounds were originally recorded from 25 participants using five contact microphones, four on the chest and one on the trachea, during three progressive respiratory maneuvers. In this work CAS component detection was performed on the tracheal channel using our automatic algorithm based on the Hilbert spectrum. The tracheal CAS detected were then compared to the previously analyzed pulmonary CAS. The sensitivity of CAS identification was lower at the tracheal microphone, with CAS that appeared simultaneously in all four pulmonary recordings more likely to be identified in the tracheal recordings. These observations could be due to the CAS being obscured by the lower SNR present in the tracheal recordings or not being transmitted through the airways to the trachea. Further work to optimize the algorithm for the tracheal recordings will be conducted in the future.

JTD Keywords: Microphones, Lung, Diseases, Time-frequency analysis, Spectrogram, Sensitivity

Cardiovascular diseases are one of the most common causes of death in elderly patients. The etiology of cardiomyopathies is difficult to discern clinically. The objective of this study was to classify cardiomyopathy patients using coupling analysis, through their cardiovascular behavior and the baroreflex response. A total of thirty-eight cardiomyopathy patients (CMP) classified as ischemic (ICM, 25 patients) and dilated (DCM, 13 patients) were analyzed. Thirty elderly control subjects (CON) were used as reference. Their electrocardiographic (ECG) and blood pressure (BP) signals were studied. To characterize the cardiovascular activity, the following temporal series were extracted: beat-to-beat intervals (from the ECG signal), and end- systolic and diastolic blood pressure amplitudes (from the BP signal). Non-linear characterization techniques like high resolution joint symbolic dynamics, segmented Poincaré plot analysis, normalized shorttime partial directed coherence, and dual sequence method were used to characterize these times series. The best indices were used to build support vector machine models for classification. The optimal model for ICM versus DCM patients achieved 84.2% accuracy, 76.9% sensitivity, and 88% specificity. When CMP patients and CON subjects were compared, the best model achieved 95.5% accuracy, 97.3% sensitivity, and 93.3% specificity. These results suggest a disfunction in the baroreflex mechanism in cardiomyopathies patients.

JTD Keywords: Couplings, Time series analysis, Support vector machines, Electrocardiography, Baroreflex, Coherence, Sensitivity

Estimating the affective state of a user during a computer task traditionally relies on either subjective reports or analysis of physiological signals, facial expressions, and other measures. These methods have known limitations, can be intrusive and may require specialized equipment. An alternative would be employing a ubiquitous device of everyday use such as a standard keyboard. Here we investigate if we can infer the emotional state of a user by analyzing their typing patterns. To test this hypothesis, we asked 400 participants to caption a set of emotionally charged images taken from a standard database with known ratings of arousal and valence. We computed different keystroke pattern dynamics, including keystroke duration (dwell time) and latency (flight time). By computing the mean value of all of these features for each image, we found a statistically significant negative correlation between dwell times and valence, and between flight times and arousal. These results highlight the potential of using keystroke dynamics to estimate the affective state of a user in a non-obtrusive way and without the need for specialized devices.

JTD Keywords: Feature extraction, Correlation, Keyboards, Task analysis, Statistical analysis, Affective computing, Standards, Keystroke, Keyboard, Typing, Arousal, Valence, Affect

In this paper, a non-linear HRV analysis was performed to assess fragmentation signatures observed in heartbeat time series after intermittent hypoxia (IH). Three markers quantifying short-term fragmentation levels, PIP, IALS and PSS, were evaluated on R-R interval series obtained in a rat model of recurrent apnea. Through airway obstructions, apnea episodes were periodically simulated in six anesthetized Sprague-Dawley rats. The number of apnea events per hour (AHI index) was varied during the first half of the experiment while apnea episodes lasted 15 s. For the second part, apnea episodes lasted 5, 10 or 15 s, but the AHI index was fixed. Recurrent apnea was repeated for 15-min time intervals in all cases, alternating with basal periods of the same duration. The fragmentation markers were evaluated in segments of 5 minutes, selected at the beginning and end of the experiment. The impact of the heart and breathing rates (HR and BR, respectively) on the parameter estimates was also investigated. The results obtained show a significant increase (from 5 to 10%, p <; 0.05) in fragmentation measures of heartbeat time series after IH, indicating a clear deterioration of the initial conditions. Moreover, there was a strong linear relationship (r > 0.9) between these markers and BR, as well as with the ratio given by HR/BR. Although fragmentation may be impacted by IH, we found that it is highly dependent on HR and BR values and thus, they should be considered during its calculation or used to normalize the fragmentation estimates.

JTD Keywords: Rats, Time series analysis, Radio access technologies, Protocols, Heart beat

Mucosal administration of drugs and drug delivery systems has gained increasing interest. However, nanoparticles intended to protect and deliver drugs to epithelial surfaces require transport through the surface-lining mucus. Translation from bench to bedside is particularly challenging for mucosal administration since a variety of parameters will influence the specific barrier properties of the mucus including the luminal fluids, the microbiota, the mucus composition and clearance rate, and the condition of the underlying epithelia. Besides, after administration, nanoparticles interact with the mucosal components, forming a biomolecular corona that modulates their behavior and fate after mucosal administration. These interactions are greatly influenced by the nanoparticle properties, and therefore different designs and surface-engineering strategies have been proposed. Overall, it is essential to evaluate these biomolecule-nanoparticle interactions by complementary techniques using complex and relevant mucus barrier matrices.

JTD Keywords: Nanoparticle formulation strategies, Corona formation, Digestive tract, Respiratory tract, Luminal content, Methodologies, Analysis

Here, we present a flexible and low-cost inkjet printed electrochemical sensor for enzyme-free glucose analysis. Versatility, short fabrication time and low cost make inkjet printing a valuable alternative to traditional sensor manufacturing techniques. We fabricated electro-chemical glucose sensors by inkjet printing electrodes on a flexible polyethylene terephthalate substrate. CuO microparticles were used to modify our electrodes, leading to a sensitive, stable and cost-effective platform for non-enzymatic detection of glucose. Selectivity, reproducibility, and life-time provided by the CuO functionalization demonstrated that these sensors are reliable tools for personalized diagnostics and self-assessment of an individual's health. The detection of glucose at concentrations matching that of tear fluid allows us to envisage applications in ocular diagnostics, where painless and non-invasive monitoring of diabetes can be achieved by analyzing glucose contained in tears.

JTD Keywords: Inkjet printing, Non-enzymatic sensor, Glucose, Copper oxide, Tear analysis

Advances in analytical instrumentation have provided the possibility of examining thousands of genes, peptides, or metabolites in parallel. However, the cost and time-consuming data acquisition process causes a generalized lack of samples. From a data analysis perspective, omics data are characterized by high dimensionality and small sample counts. In many scenarios, the analytical aim is to differentiate between two different conditions or classes combining an analytical method plus a tailored qualitative predictive model using available examples collected in a dataset. For this purpose, partial least squares-discriminant analysis (PLS-DA) is frequently employed in omics research. Recently, there has been growing concern about the uncritical use of this method, since it is prone to overfitting and may aggravate problems of false discoveries. In many applications involving a small number of subjects or samples, predictive model performance estimation is only based on cross-validation (CV) results with a strong preference for reporting results using leave one out (LOO). The combination of PLS-DA for high dimensionality data and small sample conditions, together with a weak validation methodology is a recipe for unreliable estimations of model performance. In this work, we present a systematic study about the impact of the dataset size, the dimensionality, and the CV technique used on PLS-DA overoptimism when performance estimation is done in cross-validation. Firstly, by using synthetic data generated from a same probability distribution and with assigned random binary labels, we have obtained a dataset where the true classification rate (CR) is 50%. As expected, our results confirm that internal validation provides overoptimistic estimations of the classification accuracy (i.e., overfitting). We have characterized the CR estimator in terms of bias and variance depending on the internal CV technique used and sample to dimensionality ratio. In small sample conditions, due to the large bias and variance of the estimator, the occurrence of extremely good CRs is common. We have found that overfitting peaks when the sample size in the training subset approaches the feature vector dimensionality minus one. In these conditions, the models are neither under- or overdetermined with a unique solution. This effect is particularly intense for LOO and peaks higher in small sample conditions. Overoptimism is decreased beyond this point where the abundance of noisy produces a regularization effect leading to less complex models. In terms of overfitting, our study ranks CV methods as follows: Bootstrap produces the most accurate estimator of the CR, followed by bootstrapped Latin partitions, random subsampling, K-Fold, and finally, the very popular LOO provides the worst results. Simulation results are further confirmed in real datasets from mass spectrometry and microarrays.

JTD Keywords: Metabolomics, Mass spectrometry, Microarrays, Chemometrics, Data analysis, Classification, Method validation

The time delay estimation problem associated with an ensemble of misaligned, repetitive signals is revisited. Each observed signal is assumed to be composed of an unknown, deterministic signal corrupted by Gaussian, white noise. This paper shows that maximum likelihood (ML) time delay estimation can be viewed as the maximization of an eigenvalue ratio, where the eigenvalues are obtained from the ensemble correlation matrix. A suboptimal, one-step time delay estimate is proposed for initialization of the ML estimator, based on one of the eigenvectors of the inter-signal correlation matrix. With this approach, the ML estimates can be determined without the need for an intermediate estimate of the underlying, unknown signal. Based on respiratory flow signals, simulations show that the variance of the time delay estimation error for the eigenvalue-based method is almost the same as that of the ML estimator. Initializing the maximization with the one-step estimates, rather than using the ML estimator alone, the computation time is reduced by a factor of 5M when using brute force maximization (M denoting the number of signals in the ensemble), and a factor of about 1.5 when using particle swarm maximization. It is concluded that eigenanalysis of the ensemble correlation matrix not only provides valuable insight on how signal energy, jitter, and noise influence the estimation process, but it also leads to a one-step estimator which can make the way for a substantial reduction in computation time.

JTD Keywords: Biomedical signals, Time delay estimation, Eigenanalysis, Ensemble analysis

Observing biochemical processes within living cell is imperative for biological and medical research. Fluoresce imaging is widely used for intracellular sensing of cell membranes, nuclei, lysosomes, and pH. Electrochemical assays have been proposed as an alternative to fluorescence-based assays because of excellent analytical features of electrochemical devices. Notably, thanks to the rapid progress of micro/nanotechnologies and electrochemical techniques, intracellular electrochemical sensing is making rapid progress, leading to a successful detection of intracellular components. Such insight can provide a deep understanding of cellular biological processes and, ultimately, define the human healthy and diseased states. In this review, we present an overview of recent research progress in intracellular electrochemical sensing. We focus on two main topics, electrochemical extraction of cytosolic contents from cells and intracellular electrochemical sensing in situ.

JTD Keywords: Micro/nanoelectrode, Analytical electrochemistry, Intracellular sensing, Cell analysis

Cardiac motion estimation is an important diagnostic tool for detecting heart diseases and it has been explored with modalities such as MRI and conventional ultrasound (US) sequences. US cardiac motion estimation still presents challenges because of complex motion patterns and the presence of noise. In this work, we propose a novel approach to estimate cardiac motion using ultrafast ultrasound data. Our solution is based on a variational formulation characterized by the L 2-regularized class. Displacement is represented by a lattice of b-splines and we ensure robustness, in the sense of eliminating outliers, by applying a maximum likelihood type estimator. While this is an important part of our solution, the main object of this work is to combine low-rank data representation with topology preservation. Low-rank data representation (achieved by finding the k-dominant singular values of a Casorati matrix arranged from the data sequence) speeds up the global solution and achieves noise reduction. On the other hand, topology preservation (achieved by monitoring the Jacobian determinant) allows one to radically rule out distortions while carefully controlling the size of allowed expansions and contractions. Our variational approach is carried out on a realistic dataset as well as on a simulated one. We demonstrate how our proposed variational solution deals with complex deformations through careful numerical experiments. The low-rank constraint speeds up the convergence of the optimization problem while topology preservation ensures a more accurate displacement. Beyond cardiac motion estimation, our approach is promising for the analysis of other organs that exhibit motion.

JTD Keywords: Cardiac analysis, Low-rank representation, Motion estimation, Topology preservation, Ultrafast ultrasound

Cardiac death risk is still a big problem by an important part of the population, especially in elderly patients. In this study, we propose to characterize and analyze the cardiovascular and cardiorespiratory systems using the Poincaré plot. A total of 46 cardiomyopathy patients and 36 healthy subjets were analyzed. Left ventricular ejection fraction (LVEF) was used to stratify patients with low risk (LR: LVEF > 35%, 16 patients), and high risk (HR: LVEF ≤ 35%, 30 patients) of heart attack. RR, SBP and TTot time series were extracted from the ECG, blood pressure and respiratory flow signals, respectively. Parameters that describe the scatterplott of Poincaré method, related to short- and long-term variabilities, acceleration and deceleration of the dynamic system, and the complex correlation index were extracted. The linear discriminant analysis (LDA) and the support vector machines (SVM) classification methods were used to analyze the results of the extracted parameters. The results showed that cardiac parameters were the best to discriminate between HR and LR groups, especially the complex correlation index (p = 0.009). Analising the interaction, the best result was obtained with the relation between the difference of the standard deviation of the cardiac and respiratory system (p = 0.003). When comparing HR vs LR groups, the best classification was obtained applying SVM method, using an ANOVA kernel, with an accuracy of 98.12%. An accuracy of 97.01% was obtained by comparing patients versus healthy, with a SVM classifier and Laplacian kernel. The morphology of Poincaré plot introduces parameters that allow the characterization of the cardiorespiratory system dynamics.

JTD Keywords: Time series analysis, Electrocardiography, Support vector machines, Kernel, Standards, Correlation, RF signals

Obstructive sleep apnea (OSA) is a highly prevalent chronic disease, especially in elderly and obese populations. Despite constituting a serious health, social and economic problem, most patients remain undiagnosed and untreated due to limitations in current equipment. In this work, we propose a novel method to diagnose OSA and monitor therapy adherence and effectiveness at home in a non-invasive and inexpensive way: combining acoustic analysis of breathing and snoring sounds with oral appliance therapy (OA). Audiodontics has introduced a new sensor, a tooth microphone coupled to an OA device, which is the main pillar of this system. The objective of this work is to characterize the response of this sensor, comparing it with a commercial tracheal microphone (Biopac transducer). Signals containing OSA-related sounds were acquired simultaneously with the two microphones for that purpose. They were processed and analyzed in time, frequency and time-frequency domains, in a custom MATLAB interface. We carried out a single-event approach focused on breaths, snores and apnea episodes. We found that the quality of the signals obtained by both microphones was quite similar, although the tooth microphone spectrum concentrated more energy at the high-frequency band. This opens a new field of study about high-frequency components of snores and breathing sounds. These characteristics, together with its intraoral position, wireless option and combination with customizable OAs, give the tooth microphone a great potential to reduce the impact of sleep disorders, by enabling prompt detection and continuous monitoring of patients at home.

JTD Keywords: Microphones, Teeth, Sleep apnea, Time-frequency analysis, Signal to noise ratio, Monitoring, Acoustics

Synchronization is a central key feature of neural information processing and communication between different brain areas. Disturbance of oscillatory brain rhythms and decreased synchronization have been associated with different disorders including schizophrenia. The aim of this study was to investigate whether synchronization (in relaxed conditions with no stimuli) between different brain areas within the delta, theta, alpha (alpha1, alpha2), beta (beta1, beta2), and gamma bands is altered in patients with a neurological disorder in order to generate significant cortical enhancements. To achieve this, we investigated schizophrenic patients (SZO; N=17, 37.5±10.4 years, 15 males) and compared them to healthy subjects (CON; N=21, 36.7±13.4 years, 15 males) applying the phase locking value (PLV). We found significant differences between SZO and CON in different brain areas of the theta, alpha1, beta2 and gamma bands. These areas are related to the central and parietal lobes for the theta band, the parietal lobe for the alpha1, the parietal and frontal for the beta2 and the frontal-central for the gamma band. The gamma band revealed the most significant differences between CON and SZO. PLV were 61.7% higher on average in SZO in most of the clusters when compared to CON. The related brain areas are directly related to cognition skills which are proved to be impaired in SZO. The results of this study suggest that synchronization in SZO is also altered when the patients were not asked to perform a task that requires their cognitive skills (i.e., no stimuli are applied - in contrast to other findings).

JTD Keywords: Synchronization, Electroencephalography, Electrodes, Brain, Time series analysis, Oscillators, Frequency synchronization

In this work, the cardiorespiratory pattern of patients undergoing extubation process is studied. First, the respiratory and cardiac signals were resampled, next the Symbolic Dynamics (SD) technique was implemented, followed of a dimensionality reduction applying Forward Selection (FS) and Moving Window with Variance Analysis (MWVA) methods. Finally, the Linear Discriminant Analysis (LDA) and Support Vector Machines (SVM) classifiers were used. The study analyzed 153 patients undergoing weaning process, classified into 3 groups: Successful Group (SG: 94 patients), Failed Group (FG: 39 patients), and patients who had been successful during the extubation and had to be reintubated before 48 hours, Reintubated Group (RG: 21 patients). According to the results, the best classification present an accuracy higher than 88.98 ± 0.013% in all proposed combinations.

JTD Keywords: Support vector machines, Standards, Time series analysis, Resonant frequency, Nonlinear dynamical systems, Ventilation

A novel suspended planar-array chips technology is described, which effectively allows molecular multiplexing using a single suspended chip to analyze extraordinarily small volumes. The suspended chips are fabricated by combining silicon-based technology and polymer-pen lithography, obtaining increased molecular pattern flexibility, and improving miniaturization and parallel production. The chip miniaturization is so dramatic that it permits the intracellular analysis of living cells.

JTD Keywords: Chip-in-a-cell, Suspended-arrays, Planar-arrays, Silicon chips, Single-cell analysis

Altered nutrition in the intervertebral disc affects cell viability and can generate catabolic cascades contributing to extracellular matrix (ECM) degradation. Such degradation is expected to affect couplings between disc mechanics and nutrition, contributing to accelerate degenerative processes. However, the relation of ECM changes to major biophysical events within the loaded disc remains unclear. A L4-L5 disc finite element model including the nucleus (NP), annulus (AF) and endplates was used and coupled to a transport-cell viability model. Solute concentrations and cell viability were evaluated along the mid-sagittal plane path. A design of experiment (DOE) was performed. DOE parameters corresponded to AF and NP biochemical tissue measurements in discs with different degeneration grades. Cell viability was not affected by any parameter combinations defined. Nonetheless, the initial water content was the parameter that affected the most the solute contents, especially glucose. Calculations showed that altered NP composition could negatively affect AF cell nutrition. Results suggested that AF and NP tissue degeneration are not critical to nutrition-related cell viability at early-stage of disc degeneration. However, small ECM degenerative changes may alter significantly disc nutrition under mechanical loads. Coupling disc mechano-transport simulations and enzyme expression studies could allow identifying spatiotemporal sequences related to tissue catabolism.

JTD Keywords: Cell nutrition, Finite element analysis, Intervertebral disc degeneration, Multiphysics, Tissue composition

The use of non-invasive methods for the study of respiratory muscle signals can provide clinical information for the evaluation of the respiratory muscle function. The aim of this study was to evaluate time-frequency characteristics of the electrical activity of the sternocleidomastoid muscle recorded superficially by means of concentric ring electrodes (CREs) in a bipolar configuration. The CREs enhance the spatial resolution, attenuate interferences, as the cardiac activity, and also simplify the orientation problem associated to the electrode location. Five healthy subjects underwent a respiratory load test in which an inspiratory load was imposed during the inspiratory phase. During the test, the electromyographic signal of the sternocleidomastoid muscle (EMGsc) and the inspiratory mouth pressure (Pmouth) were acquired. Time-frequency characteristics of the EMGsc signal were analyzed by means of eight time-frequency representations (TFRs): the spectrogram (SPEC), the Morlet scalogram (SCAL), the Wigner-Ville distribution (WVD), the Choi-Williams distribution (CHWD), two generalized exponential distributions (GED1 and GED2), the Born-Jordan distribution (BJD) and the Cone-Kernel distribution (CKD). The instantaneous central frequency of the EMGsc showed an increasing behavior during the inspiratory cycle and with the increase of the inspiratory load. The bilinear TFRs (WVD, CHWD, GEDs and BJD) were less sensitive to cardiac activity interference than classical TFRs (SPEC and SCAL). The GED2 was the TFR that shown the best results for the characterization of the instantaneous central frequency of the EMGsc.

JTD Keywords: Electrodes, Interference, Kernel, Mouth, Muscles, Spectrogram, Time-frequency analysis

The present paper reports a bacteria autonomous controlled concentrator prototype with a user-friendly interface for bench-top applications. It is based on a micro-fluidic lab-on-a-chip and its associated custom instrumentation, which consists in a dielectrophoretic actuator, to pre-concentrate the sample, and an impedance analyser, to measure concentrated bacteria levels. The system is composed by a single micro-fluidic chamber with interdigitated electrodes and a instrumentation with custom electronics. The prototype is supported by a real-time platform connected to a remote computer, which automatically controls the system and displays impedance data used to monitor the status of bacteria accumulation on-chip. The system automates the whole concentrating operation. Performance has been studied for controlled volumes of Escherichia coli (E. coli) samples injected into the micro-fluidic chip at constant flow rate of 10 μL/min. A media conductivity correcting protocol has been developed, as the preliminary results showed distortion of the impedance analyser measurement produced by bacterial media conductivity variations through time. With the correcting protocol, the measured impedance values were related to the quantity of bacteria concentrated with a correlation of 0.988 and a coefficient of variation of 3.1%. Feasibility of E. coli on-chip automated concentration, using the miniaturized system, has been demonstrated. Furthermore, the impedance monitoring protocol had been adjusted and optimized, to handle changes in the electrical properties of the bacteria media over time.

JTD Keywords: Autonomous Device, Bacteria Concentrator, Dielectrophoresis, Escherichia coli, Impedance Analysis

This work investigates the performance of cardiorespiratory analysis detecting periodic breathing (PB) in chest wall recordings in mountaineers climbing to extreme altitude. The breathing patterns of 34 mountaineers were monitored unobtrusively by inductance plethysmography, ECG and pulse oximetry using a portable recorder during climbs at altitudes between 4497 and 7546 m on Mt. Muztagh Ata. The minute ventilation (VE) and heart rate (HR) signals were studied, to identify visually scored PB, applying time-varying spectral, coherence and entropy analysis. In 411 climbing periods, 30–120 min in duration, high values of mean power (MPVE) and slope (MSlopeVE) of the modulation frequency band of VE, accurately identified PB, with an area under the ROC curve of 88 and 89 %, respectively. Prolonged stay at altitude was associated with an increase in PB. During PB episodes, higher peak power of ventilatory (MPVE) and cardiac (MP LF HR ) oscillations and cardiorespiratory coherence (MP LF Coher ), but reduced ventilation entropy (SampEnVE), was observed. Therefore, the characterization of cardiorespiratory dynamics by the analysis of VE and HR signals accurately identifies PB and effects of altitude acclimatization, providing promising tools for investigating physiologic effects of environmental exposures and diseases.

JTD Keywords: High-altitude periodic breathing, Cardiorespiratory characterization, Time-varying spectral analysis, Acclimatization, Hypoxia

In computer-assisted beating heart surgeries, accurate tracking of the heart's motion is of huge importance and there is a continuous need to eliminate any source of error that might disturb the tracking process. One source of error is the specular reflection that appears on the glossy surface of the heart. In this paper, we propose a robust solution for the detection and removal of specular highlights. A hybrid color attributes and wavelet based edge projection approach is applied to accurately identify the affected regions. These regions are then recovered using a dynamic search-based inpainting with adaptive windowing. Experimental results demonstrate the precision and efficiency of the proposed method. Moreover, it has a real-time performance and can be generalized to various other applications.

JTD Keywords: Heart, Image color analysis, Image edge detection, Surgery, Tracking, Wavelet transforms

Cardiovascular diseases are the first cause of death in developed countries. Using electrocardiographic (ECG), blood pressure (BP) and respiratory flow signals, we obtained parameters for classifying cardiomyophaty patients. 42 patients with ischemic (ICM) and dilated (DCM) cardiomyophaties were studied. The left ventricular ejection fraction (LVEF) was used to stratify patients with low risk (LR: LVEF>35%, 14 patients) and high risk (HR: LVEF≤ 35%, 28 patients) of heart attack. RR, SBP and T_Tot time series were extracted from the ECG, BP and respiratory flow signals, respectively. The time series were transformed to a binary space and then analyzed using Joint Symbolic Dynamic with a word length of three, characterizing them by the probability of occurrence of the words. Extracted parameters were then reduced using correlation and statistical analysis. Principal component analysis and support vector machines methods were applied to characterize the cardiorespiratory and cardiovascular interactions in ICM and DCM cardiomyopaties, obtaining an accuracy of 85.7%.

JTD Keywords: Blood pressure, Electrocardiography, Joints, Kernel, Principal component analysis, Support vector machines, Time series analysis

The scope of our work focuses on investigating the potential use of the built-in accelerometer of the smartphones for the recording of the respiratory activity and deriving the respiratory rate. Five healthy subjects performed an inspiratory load protocol. The excursion of the right chest was recorded using the built-in triaxial accelerometer of a smartphone along the x, y and z axes and with an external uniaxial accelerometer. Simultaneously, the respiratory airflow and the inspiratory mouth pressure were recorded, as reference respiratory signals. The chest acceleration signal recorded in the z axis with the smartphone was denoised using a scheme based on the ensemble empirical mode decomposition, a noise data assisted method which decomposes nonstationary and nonlinear signals into intrinsic mode functions. To distinguish noisy oscillatory modes from the relevant modes we use the detrended fluctuation analysis. We reported a very strong correlation between the acceleration of the z axis of the smartphone and the reference accelerometer across the inspiratory load protocol (from 0.80 to 0.97). Furthermore, the evaluation of the respiratory rate showed a very strong correlation (0.98). A good agreement was observed between the respiratory rate estimated with the chest acceleration signal from the z axis of the smartphone and with the respiratory airflow signal: Bland-Altman limits of agreement between -1.44 and 1.46 breaths per minute with a mean bias of -0.01 breaths per minute. This preliminary study provides a valuable insight into the use of the smartphone and its built-in accelerometer for respiratory monitoring.

JTD Keywords: Acceleration, Accelerometers, Correlation, Empirical mode decomposition, Fluctuations, Protocols, Time series analysis

The lack of physiological motion compensation is a major problem in robotic-assisted cardiac surgery. Since the heart is beating while the surgeon carried out the procedure, dexterity of the surgeon’s and precision are compromised. Due to the operative space and the visibility of the surgical field are reduced, the most practical solution is the use of computer vision techniques. The lack of efficiency and robustness of the existing proposals make physiological motion compensation to be considered an open problem. In this work a novel solution to solve this problem based on the minimization of an energy functional is presented. It is described in the three-dimensional space using the l1−regularized optimization class in which cubic b-splines are used to represent the changes produced on the heart surface. Moreover, the logarithmic barrier function is applied to create an approximation of the total energy in order to avoid its non-differentiability. According to the results, this proposal is able to deal with complex deformations, requires a short computational time and gives a small error.

JTD Keywords: Beating heart surgery, Image analysis, Motion compensation

Xenopus tadpoles are an emerging model for developmental, genetic and behavioral studies. A small size, optical accessibility of most of their organs, together with a close genetic and structural relationship to humans make them a convenient experimental model. However, there is only a limited toolset available to measure behavior and organ function of these animals at medium or high-throughput. Herein, we describe an imaging-based platform to quantify body and autonomic movements of Xenopus tropicalis tadpoles of advanced developmental stages. Animals alternate periods of quiescence and locomotor movements and display buccal pumping for oxygen uptake from water and rhythmic cardiac movements. We imaged up to 24 animals in parallel and automatically tracked and quantified their movements by using image analysis software. Animal trajectories, moved distances, activity time, buccal pumping rates and heart beat rates were calculated and used to characterize the effects of test compounds. We evaluated the effects of propranolol and atropine, observing a dose-dependent bradycardia and tachycardia, respectively. This imaging and analysis platform is a simple, cost-effective high-throughput in vivo assay system for genetic, toxicological or pharmacological characterizations.

JTD Keywords: Xenopus tropicalis, Animal behavior, Cardiac imaging, Motion analysis, Animal tracking, Hhigh-throughput in vivo assay

The electric polarizability of DNA, represented by the dielectric constant, is a key intrinsic property that modulates DNA interaction with effector proteins. Surprisingly, it has so far remained unknown owing to the lack of experimental tools able to access it. Here, we experimentally resolved it by detecting the ultraweak polarization forces of DNA inside single T7 bacteriophages particles using electrostatic force microscopy. In contrast to the common assumption of low-polarizable behavior like proteins (εr ~ 2–4), we found that the DNA dielectric constant is ~ 8, considerably higher than the value of ~ 3 found for capsid proteins. State-of-the-art molecular dynamic simulations confirm the experimental findings, which result in sensibly decreased DNA interaction free energy than normally predicted by Poisson–Boltzmann methods. Our findings reveal a property at the basis of DNA structure and functions that is needed for realistic theoretical descriptions, and illustrate the synergetic power of scanning probe microscopy and theoretical computation techniques.

JTD Keywords: Atomic force microscopy, Atomistic simulations, DNA packaging, DNA-ligand binding, Poisson-Boltzmann equation, capsid protein, DNA, double stranded DNA, amino acid composition, article, atomic force microscopy, bacteriophage, bacteriophage T7, dielectric constant, dipole, DNA binding, DNA packaging, DNA structure, electron microscopy, ligand binding, nonhuman, polarization, priority journal, protein analysis, protein DNA interaction, scanning probe microscopy, static electricity, virion, virus capsid, virus particle, atomic force microscopy, atomistic simulations, DNA packaging, DNA-ligand binding, Poisson-Boltzmann equation, Bacteriophage T7, Capsid, Cations, Dielectric Spectroscopy, DNA, DNA, Viral, DNA-Binding Proteins, Electrochemical Techniques, Ligands, Microscopy, Atomic Force, Models, Chemical, Nuclear Proteins

Novel strategies to heal discogenic low back pain could highly benefit from comprehensive biophysical studies that consider both mechanical and biological factors involved in intervertebral disc degeneration. A decrease in nutrient availability at the bone-disc interface has been indicated as a relevant risk factor and as a possible initiator of cell death processes. Mechanical behaviour of both healthy and degenerated discs could highly interact with cell death in these compromised situations. In the present study, a mechano-transport finite element model was used to investigate the nature of mechanical effects on cell death processes via load-induced metabolic transport variations. Cycles of static sustained compression were chosen to simulate daily human activity. Healthy and degenerated cases were simulated as well as a reduced supply of solutes and an increase in solute exchange area at the bone-disc interface. Results showed that a reduction in metabolite concentrations at the bone-disc boundaries induced cell death, even when the increased exchange area was simulated. Slight local mechanical enhancements of glucose in the disc centre were capable of decelerating cell death but occurred only with healthy mechanical properties. However, mechanical deformations were responsible for a worsening in terms of cell death in the inner annulus, a disadvantaged zone far from the boundary supply with both an increased cell demand and a strain-dependent decrease of diffusivity. Such adverse mechanical effects were more accentuated when degenerative properties were simulated. Overall, this study paves the way for the use of biophysical models for a more integrated understanding of intervertebral disc pathophysiology.

JTD Keywords: Boundary conditions, Cell nutrition, Cell viability, Computational analysis, Intervertebraldisc, Softtissuebiomechanics

AbstractBackground Hip arthritis is a pathology linked to hip-cartilage degeneration. Although the aetiology of this disease is not well defined, it is known that age is a determinant risk factor. However, hip arthritis in young patients could be largely promoted by biomechanical factors. The objective of this paper is to analyze the impact of some normal anatomical variations on the cartilage stress distributions numerically predicted at the hip joint during walking. Methods A three-dimensional finite element model of the femur and the pelvis with the most relevant axial components of muscle forces was used to simulate normal walking activity. The hip anatomical condition was defined by: neck shaft angle, femoral anteversion angle, and acetabular anteversion angle with a range of 110-130º, 0-20º, and 0-20º, respectively. The direct boundary method was used to simulate the hip contact. Findings The hydrostatic stress found at the cartilage and labrum showed that a ± 10º variation with respect to the reference brings significant differences between the anatomic models. Acetabular anteversion angle of 0º and femoral anteversion angle of 0º were the most affected anatomical conditions with values of hydrostatic stress in the cartilage near 5 MPa under compression. Interpretation Cartilage stresses and contact areas were equivalent to the results found in literature and the most critical anatomical regions in terms of tissue loads were in a good accordance with clinical evidence. Altogether, results showed that decreasing femoral or acetabular anteversion angles isolately causes a dramatic increase in cartilage loads.

JTD Keywords: Hip arthritis, Neck shaft angle, Femoral and acetabular anteversions, Cartilage load, Hip joint contact, Finite element analysis

Due to the increasing elderly population and the extensive number of comorbidities that affect them, studies are required to determine future increments in admission to emergency departments. Some of these studies could focus on the relation between chronic diseases and breathing pattern in elderly patients. Variations in the fractal properties of respiratory signals can be associated with several diseases. To determine the relationship between these variations and breathing patterns, and to quantify the fractal properties of respiratory flow signals, we estimated the Hurst exponent (H). Detrended fluctuation analysis (DFA) and discrete wavelet transform-based estimation (DWTE) methods were applied. The estimation methods were analyzed using simulated data series generated by fractional Gaussian noise. 43 elderly patients (19 patients with a non-periodic breathing pattern - nPB, and 24 patients with a periodic breathing pattern - PB) were studied. The results were evaluated according to the length of data and the number of averaged data series used to obtain a good estimation. The DWTE method estimated the respiratory flow signals better than the DFA method, and obtained Hurst values clustered by group. We found significant differences in the H exponent (p = 0.002) between PB and nPB patients, which showed different behavior in the fractal properties.

JTD Keywords: Discrete wavelet transforms, Diseases, Estimation, Fractals, Modulation, Senior citizens, Time series analysis

Disconnection from mechanical ventilation, called the weaning process, is an additional difficulty in the management of patients in intensive care units (ICU). Unnecessary delays in the discontinuation process and a weaning trial that is undertaken too early are undesirable. In this study, we propose an extubation index based on the power of the respiratory flow signal (Pi). A total of 132 patients on weaning trials were studied: 94 patients with successful trials (group S) and 38 patients who failed to maintain spontaneous breathing and were reconnected (group F). The respiratory flow signals were processed considering the following three stages: a) zero crossing detection of the inspiratory phase, b) inflection point detection of the flow curve during the inspiratory phase, and c) calculation of the signal power on the time instant indicated by the inflection point. The zero crossing detection was performed using an algorithm based on thresholds. The inflection points were marked considering the zero crossing of the second derivative. Finally, the inspiratory power was calculated from the energy contained over the finite time interval (between the instant of zero crossing and the inflection point). The performance of this parameter was evaluated using the following classifiers: logistic regression, linear discriminant analysis, the classification and regression tree, Naive Bayes, and the support vector machine. The best results were obtained using the Bayesian classifier, which had an accuracy, sensitivity and specificity of 87%, 90% and 81% respectively.

JTD Keywords: Bayes methods, Bayesian classifier, Indexes, Logistics, Niobium, Regression tree analysis, Support vector machines, Ventilation

The position analysis of a planar mechanism is based on obtaining the roots of its characteristic polynomial. In general, this polynomial is the result of a system of kinematic equations which they are derived from closure condition of the mechanism, widely known as independent kinematic loop equations or loop closure equations . This way of solving the position analysis of kinematic chains introduces complex variable eliminations, and in general trigonometric substitutions. Recently, the use of methods based on bilateration to solve the position analysis, has been shown to avoid these variable eliminations and trigonometric substitutions in planar mechanism. In this work it is shown how this method based on bilateration can be use to automatically generate closure conditions of a planar mechanism.

JTD Keywords: Position analysis, Bilateration, Rigidity, Isomorphism, Kinematic

Assessment of the dynamic interactions between cardiovascular signals can provide valuable information that improves the understanding of cardiovascular control. Heart rate variability (HRV) analysis is known to provide information about the autonomic heart rate modulation mechanism. Using the HRV signal, we aimed to obtain parameters for classifying patients with and without chronic heart failure (CHF), and with periodic breathing (PB), non-periodic breathing (nPB), and Cheyne-Stokes respiration (CSR) patterns. An electrocardiogram (ECG) and a respiratory flow signal were recorded in 36 elderly patients: 18 patients with CHF and 18 patients without CHF. According to the clinical criteria, the patients were classified into the follow groups: 19 patients with nPB pattern, 7 with PB pattern, 4 with Cheyne-Stokes respiration (CSR), and 6 non-classified patients (problems with respiratory signal). From the HRV signal, parameters in the time and frequency domain were calculated. Frequency domain parameters were the most discriminant in comparisons of patients with and without CHF: P_Tot (p = 0.02), P_LF (p = 0.022) and fp_HF (p = 0.021). For the comparison of the nPB vs. CSR patients groups, the best parameters were RMSSD (p = 0.028) and SDSD (p = 0.028). Therefore, the parameters appear to be suitable for enhanced diagnosis of decompensated CHF patients and the possibility of developed periodic breathing and a CSR pattern.

JTD Keywords: cardiovascular system, diseases, electrocardiography, frequency-domain analysis, geriatrics, medical signal processing, patient diagnosis, pneumodynamics, signal classification, Cheyne-Stokes respiration patterns, ECG, autonomic heart rate modulation mechanism, cardiovascular control, cardiovascular signals, chronic heart failure, decompensated CHF patients, dynamic interaction assessment, elderly patients, electrocardiogram, enhanced diagnosis, frequency domain parameters, heart rate variability analysis, patient classification, periodic breathing, respiratory flow signal recording, Electrocardiography, Frequency modulation, Frequency-domain analysis, Heart rate variability, Senior citizens, Standards

Ischemic and dilated cardiomyopathy are associated with disorders of myocardium. Using the blood pressure (BP) signal and the values of the ventricular ejection fraction, we obtained parameters for stratifying cardiomyopathy patients as low- and high-risk. We studied 48 cardiomyopathy patients characterized by NYHA ≥2: 19 patients with dilated cardiomyopathy (DCM) and 29 patients with ischemic cardiomyopathy (ICM). The left ventricular ejection fraction (LVEF) percentage was used to classify patients in low risk (LR: LVEF > 35%, 17 patients) and high risk (HR: LVEF ≤ 35%, 31 patients) groups. From the BP signal, we extracted the upward systolic slope (BP_sl), the difference between systolic and diastolic BP (BPA), and systolic time intervals (STI). When we compared the LR and HR groups in the time domain analysis, the best parameters were standard deviation (SD) of 1=STI, kurtosis (K) of BP_sl, and K of BPA. In the frequency domain analysis, very low frequency (VLF) and high frequency (HF) bands showed statistically significant differences in comaprisons of LR and HR groups. The area under the curve of power spectral density was the best parameter in all classifications, and particularly in the very-low-and high- frequency bands (p <; 0.001). These parameters could help to improve the risk stratification of cardiomyopathy patients.

JTD Keywords: blood pressure measurement, cardiovascular system, diseases, medical disorders, medical signal processing, statistical analysis, time-domain analysis, BP signal, HR groups, LR groups, blood pressure signal analysis, cardiomyopathy patients, diastolic BP, dilated cardiomyopathy, frequency domain analysis, high-frequency bands, ischemic cardiomyopathy, left ventricular ejection fraction, low-frequency bands, myocardium disorders, patient characterization, power spectral density curve, standard deviation, statistical significant differences, systolic BP, systolic slope, systolic time intervals, time domain analysis, ventricular ejection fraction, Abstracts, Databases, Parameter extraction, Telecommunication standards, Time-frequency analysis

One of the most challenging problems in intensive care is still the process of discontinuing mechanical ventilation, called weaning process. Both an unnecessary delay in the discontinuation process and a weaning trial that is undertaken too early are undesirable. In this study, we analyzed respiratory pattern variability using the respiratory volume signal of patients submitted to two different levels of pressure support ventilation (PSV), prior to withdrawal of the mechanical ventilation. In order to characterize the respiratory pattern, we analyzed the following time series: inspiratory time, expiratory time, breath duration, tidal volume, fractional inspiratory time, mean inspiratory flow and rapid shallow breathing. Several autoregressive modeling techniques were considered: autoregressive models (AR), autoregressive moving average models (ARMA), and autoregressive models with exogenous input (ARX). The following classification methods were used: logistic regression (LR), linear discriminant analysis (LDA) and support vector machines (SVM). 20 patients on weaning trials from mechanical ventilation were analyzed. The patients, submitted to two different levels of PSV, were classified as low PSV and high PSV. The variability of the respiratory patterns of these patients were analyzed. The most relevant parameters were extracted using the classifiers methods. The best results were obtained with the interquartile range and the final prediction errors of AR, ARMA and ARX models. An accuracy of 95% (93% sensitivity and 90% specificity) was obtained when the interquartile range of the expiratory time and the breath duration time series were used a LDA model. All classifiers showed a good compromise between sensitivity and specificity.

JTD Keywords: autoregressive moving average processes, feature extraction, medical signal processing, patient care, pneumodynamics, signal classification, support vector machines, time series, ARX, autoregressive modeling techniques, autoregressive models with exogenous input, autoregressive moving average model, breath duration time series, classification method, classifier method, discontinuing mechanical ventilation, expiratory time, feature extraction, final prediction errors, fractional inspiratory time, intensive care, interquartile range, linear discriminant analysis, logistic regression analysis, mean inspiratory flow, patient respiratory volume signal, pressure support level, pressure support ventilation, rapid shallow breathing, respiratory pattern variability characterization, support vector machines, tidal volume, weaning trial, Analytical models, Autoregressive processes, Biological system modeling, Estimation, Support vector machines, Time series analysis, Ventilation

This work investigates the very low frequency (VLF) modulation of QRS slopes and heart rate variability (HRV). Electrocardiogram (ECG) and respiratory flow signal were acquired from patients with dilated cardiomyopathy and ischemic cardiomyopathy. HRV as well as the upward QRS slope (I_US) and downward QRS slope (I_DS) were extracted from the ECG. The relation between HRV and QRS slopes in the VLF band was measured using ordinary coherence in 5-minute segments. Partial coherence was then used to remove the influence that respiration simultaneously exerts on HRV and QRS slopes. A statistical threshold was determined, below which coherence values were considered not to represent a linear relation. 7 out of 276 segments belonging to 5 out of 29 patients for I_US and 10 segments belonging to 5 patients for I_DS presented a VLF modulation in QRS slopes, HRV and respiration. In these segments spectral coherence was statistically significant, while partial coherence decreased, indicating that the coupling HRV and QRS slopes was related to respiration. 4 segments had a partial coherence value below the threshold for I_US, 3 segments for I_DS. The rest of the segments also presented a notable decrease in partial coherence, but still above the threshold, which means that other non-linearly effects may also affect this modulation.

JTD Keywords: diseases, electrocardiography, feature extraction, medical signal processing, pneumodynamics, statistical analysis, ECG, QRS slopes, cardiomyopathy patients, dilated cardiomyopathy, electrocardiogram, feature extraction, heart rate variability, ischemic cardiomyopathy, ordinary coherence, partial coherence value, respiration, respiratory flow signal acquisition, spectral coherence, statistical threshold, time 5 min, very low frequency modulation, Coherence, Educational institutions, Electrocardiography, Frequency modulation, Heart rate variability

Some of the most common clinical problems in elderly patients are related to diseases of the cardiac and respiratory systems. Elderly patients often have altered breathing patterns, such as periodic breathing (PB) and Cheyne-Stokes respiration (CSR), which may coincide with chronic heart failure. In this study, we used the envelope of the respiratory flow signal to characterize respiratory patterns in elderly patients. To study different breathing patterns in the same patient, the signals were segmented into windows of 5 min. In oscillatory breathing patterns, frequency and time-frequency parameters that characterize the discriminant band were evaluated to identify periodic and non-periodic breathing (PB and nPB). In order to evaluate the accuracy of this characterization, we used a feature selection process, followed by linear discriminant analysis. 22 elderly patients (7 patients with PB and 15 with nPB pattern) were studied. The following classification problems were analyzed: patients with either PB (with and without apnea) or nPB patterns, and patients with CSR versus PB, CSR versus nPB and PB versus nPB patterns. The results showed 81.8% accuracy in the comparisons of nPB and PB patients, using the power of the modulation peak. For the segmented signal, the power of the modulation peak, the frequency variability and the interquartile ranges provided the best results with 84.8% accuracy, for classifying nPB and PB patients.

JTD Keywords: cardiovascular system, diseases, feature extraction, geriatrics, medical signal processing, oscillations, pneumodynamics, signal classification, time-frequency analysis, Cheyne-Stokes respiration, apnea, cardiac systems, chronic heart failure, classification problems, discriminant band, diseases, elderly patients, feature selection process, frequency variability, interquartile ranges, linear discriminant analysis, nonperiodic breathing, oscillatory breathing pattern, periodic breathing, respiratory How signal, respiratory systems, signal segmentation, time 5 min, time-frequency parameters, Accuracy, Aging, Frequency modulation, Heart, Senior citizens, Time-frequency analysis

This article reports on the research and development of a cutting-edge biomedical device for continuous in-vivo glucose monitoring. This entirely public-funded process of technological innovation has been conducted at the University of Barcelona within a context of converging technologies involving the fields of medicine, physics, chemistry, biology, telecommunications, electronics and energy. The authors examine the value chain and the market challenges faced by in-vivo implantable biomedical devices based on nanotechnologies. In so doing, they trace the process from the point of applied research to the final integration and commercialization of the product, when the social rate of return from academic research can be estimated. Using a case-study approach, the paper also examines the high-tech activities involved in the development of this nano-enabled device and describes the technology and innovation management process within the value chain conducted in a University-Hospital-Industry-Administration-Citizens framework. Here, nanotechnology is seen to represent a new industrial revolution, boosting the biomedical devices market. Nanosensors may well provide the tools required for investigating biological processes at the cellular level in vivo when embedded into medical devices of small dimensions, using biocompatible materials, and requiring reliable and targeted biosensors, high speed data transfer, safely stored data, and even energy autonomy.

JTD Keywords: Biomedical device, Diabetes, Innovation management, Nanobiosensor, Nanotechnology, Research commercialization, Technology transfer, Academic research, Applied research, Barcelona, Biocompatible materials, Biological process, Biomedical analysis, Biomedical devices, Cellular levels, Converging technologies, Glucose monitoring, High-speed data transfer, Implantable biomedical devices, Implantable devices, In-vivo, Industrial revolutions, Innovation management, Medical Devices, Nanobiosensor, Rate of return, Research and development, Technological innovation, Value chains, Biological materials, Biomedical engineering, Biosensors, Commerce, Data transfer, Earnings, Engineering education, Glucose, Implants (surgical), Industrial research, Innovation, Medical problems, Nanosensors, Nanotechnology, Technology transfer, Equipment

Robot-assisted rehabilitation therapies usually focus on physical aspects rather than on cognitive factors. However, cognitive aspects such as attention, motivation, and engagement play a critical role in motor learning and thus influence the long-term success of rehabilitation programs. This paper studies motor-related EEG activity during the execution of robot-assisted passive movements of the upper limb, while participants either: i) focused attention exclusively on the task; or ii) simultaneously performed another task. Six healthy subjects participated in the study and results showed lower desynchronization during passive movements with another task simultaneously being carried out (compared to passive movements with exclusive attention on the task). In addition, it was proved the feasibility to distinguish between the two conditions.

JTD Keywords: Electrodes, Electroencephalography, Induction motors, Medical treatment, Robot sensing systems, Time frequency analysis, Biomechanics, Cognition, Electroencephalography, Medical robotics, Medical signal detection, Medical signal processing, Patient rehabilitation, Attention, Cognitive aspects, Desynchronization, Engagement, Motivation, Motor learning, Motor task, Motor-related EEG activity, Physical aspects, Robot-assisted passive movement detection, Robot-assisted rehabilitation therapies, Upper limb

Weaning trials process of patients in intensive care units is a complex clinical procedure. 153 patients under extubation process (T-tube test) were studied: 94 patients with successful trials (group S), 38 patients who failed to maintain spontaneous breathing and were reconnected (group F), and 21 patients with successful test but that had to be reintubated before 48 hours (group R). The respiratory pattern of each patient was characterized through the following time series: inspiratory time (T_I), expiratory time (T_E), breathing cycle duration (T_Tot), tidal volume (V_T), inspiratory fraction (T_I/T_Tot), half inspired flow (V_T/T_I), and rapid shallow index (f/V_T), where f is respiratory rate. Using techniques as autoregressive models (AR), autoregressive moving average models (ARMA) and autoregressive models with exogenous input (ARX), the most relevant parameters of the respiratory pattern were obtained. We proposed the evaluation of these parameters using classifiers as logistic regression (LR), linear discriminant analysis (LDA), support vector machines (SVM) and classification and regression tree (CART) to discriminate between patients from groups S, F and R. An accuracy of 93% (98% sensitivity and 82% specificity) has been obtained using CART classification.

JTD Keywords: Accuracy, Indexes, Logistics, Regression tree analysis, Support vector machines, Time series analysis, Autoregressive moving average processes, Medical signal processing, Pattern classification, Pneumodynamics, Regression analysis, Sensitivity, Signal classification, Support vector machines, Time series, SVM, T-tube testing, Autoregressive models-with-exogenous input, Autoregressive moving average models, Breathing cycle duration, Classification-and-regression tree, Expiratory time, Extubation process, Half inspired flow, Inspiratory fraction, Inspiratory time, Intensive care units, Linear discriminant analysis, Logistic regression, Rapid shallow index, Respiratory pattern parameter performance, Sensitivity, Spontaneous breathing, Support vector machines, Tidal volume, Time 48 hr, Time series, Weaning process classifiers

High altitude periodic breathing (PB) shares some common pathophysiologic aspects with sleep apnea, Cheyne-Stokes respiration and PB in heart failure patients. Methods that allow quantifying instabilities of respiratory control provide valuable insights in physiologic mechanisms and help to identify therapeutic targets. Under the hypothesis that high altitude PB appears even during physical activity and can be identified in comparison to visual analysis in conditions of low SNR, this study aims to identify PB by characterizing the respiratory pattern through the respiratory volume signal. A number of spectral parameters are extracted from the power spectral density (PSD) of the volume signal, derived from respiratory inductive plethysmography and evaluated through a linear discriminant analysis. A dataset of 34 healthy mountaineers ascending to Mt. Muztagh Ata, China (7,546 m) visually labeled as PB and non periodic breathing (nPB) is analyzed. All climbing periods within all the ascents are considered (total climbing periods: 371 nPB and 40 PB). The best crossvalidated result classifying PB and nPB is obtained with Pm (power of the modulation frequency band) and R (ratio between modulation and respiration power) with an accuracy of 80.3% and area under the receiver operating characteristic curve of 84.5%. Comparing the subjects from 1_st and 2_nd ascents (at the same altitudes but the latter more acclimatized) the effect of acclimatization is evaluated. SaO₂ and periodic breathing cycles significantly increased with acclimatization (p-value <; 0.05). Higher Pm and higher respiratory frequencies are observed at lower SaO₂, through a significant negative correlation (p-value <; 0.01). Higher Pm is observed at climbing periods visually labeled as PB with >; 5 periodic breathing cycles through a significant positive correlation (p-value <; 0.01). Our data demonstrate that quantification of the respiratory volum- signal using spectral analysis is suitable to identify effects of hypobaric hypoxia on control of breathing.

JTD Keywords: Frequency domain analysis, Frequency modulation, Heart, Sleep apnea, Ventilation, Visualization, Cardiology, Medical disorders, Medical signal processing, Plethysmography, Pneumodynamics, Sensitivity analysis, Sleep, Spectral analysis, Cheyne-Stokes respiration, Climbing periods, Dataset, Heart failure patients, High altitude PB, High altitude periodic breathing, Hypobaric hypoxia, Linear discriminant analysis, Pathophysiologic aspects, Physical activity, Physiologic mechanisms, Power spectral density, Receiver operating characteristic curve, Respiratory control, Respiratory frequency, Respiratory inductive plethysmography, Respiratory pattern, Respiratory volume signal, Sleep apnea, Spectral analysis, Spectral parameters

In natural tissues, the extracellular matrix composition, cell density and physiological properties are often non-homogeneous. Here we describe a model system, in which the distribution of cells throughout tissue engineering scaffolds after perfusion seeding can be influenced by the pore architecture of the scaffold. Two scaffold types, both with gyroid pore architectures, were designed and built by stereolithography: one with isotropic pore size (412 ± 13 [mu]m) and porosity (62 ± 1%), and another with a gradient in pore size (250-500 [mu]m) and porosity (35%-85%). Computational fluid flow modelling showed a uniform distribution of flow velocities and wall shear rates (15-24 s-1) for the isotropic architecture, and a gradient in the distribution of flow velocities and wall shear rates (12-38 s-1) for the other architecture. The distribution of cells throughout perfusion-seeded scaffolds was visualised by confocal microscopy. The highest densities of cells correlated with regions of the scaffolds where the pores were larger, and the fluid velocities and wall shear rates were the highest. Under the applied perfusion conditions, cell deposition is mainly determined by local wall shear stress, which, in turn, is strongly influenced by the architecture of the pore network of the scaffold.

JTD Keywords: Scaffolds, Microstructure, Cell adhesion, Confocal microscopy, Image analysis, Computational fluid dynamics

The potential of a vanguard technique as is the Ion Mobility Spectrometry with Ultraviolet ionization (UV-IMS) coupled to a Continuous Flow System (CFS) have been demonstrated in this work by using a Gas Phase Separator (GPS). This vanguard system (CFS-GPS-UV-IMS) has been used for the analysis of different types of white wines to obtain a characteristic profile for each type of wine and their posterior classification using different chemometric tools. Precision of the method was 3.1% expressed as relative standard deviation. A deep chemometric study was carried out for the classification of the four types of wines selected. The best classification performance was obtained by first reducing the data dimensionality by Principal Component Analysis (PCA) followed by Linear Discriminant Analysis (LDA) and finally using a K-Nearest Neighbour (kNN) classifier. The classification rate in an independent validation set were 92.0% classification rate value with confidence interval [89.0%, 95.0%] at P = 0.05 confidence level. The same white wines analyzed by using CFS-GPS-UV-IMS were analyzed by using Gas Chromatography with a Flame Detector (GC-FID) as conventional technique. The chromatographic method used for the determination of superior alcohols in wine samples shown in the Regulation CEE 1238/1992 was selected to carry out the analysis of the same samples set and later the classification using appropriate chemometric tools. In this case, strategies PCA-LDA and kNN classifier were also used for the correct classification of the wine samples. This combination showed similar results to the ones obtained with the proposed method.

JTD Keywords: Classification, White wines, Ultraviolet-Ion Mobility Spectrometry, Gas Phase Separate, Vanguard method, Continuous Flow System, Chemometric analysis.

Electrokinetic techniques are contact-free methods currently used in many applications, where precise handling of biological entities, such as cells, bacteria or nucleic acids, is needed. These techniques are based on the effect of electric fields on molecules suspended in a fluid, and the corresponding induced motion, which can be tuned according to some known physical laws and observed behaviours. Increasing interest on the application of such strategies in order to improve the detection of DNA strands has appeared during the recent decades. Classical electrode-based DNA electrochemical biosensors with combined electrokinetic techniques present the advantage of being able to improve the working electrode's bioactive part during their fabrication and also the hybridization yield during the sensor detection phase. This can be achieved by selectively manipulating, driving and directing the molecules towards the electrodes increasing the speed and yield of the floating DNA strands attached to them. On the other hand, this technique can be also used in order to make biosensors reusable, or reconfigurable, by simply inverting its working principle and pulling DNA strands away from the electrodes. Finally, the combination of these techniques with nanostructures, such as nanopores or nanochannels, has recently boosted the appearance of new types of electrochemical sensors that exploit the time-varying position of DNA strands in order to continuously scan these molecules and to detect their properties. This review gives an insight into the main forces involved in DNA electrokinetics and discusses the state of the art and uses of these techniques in recent years.

JTD Keywords: Electrochemical DNA biosensors, Lab-on-a-chip (LOC), Micro-total analysis systems (mu TAS), Nanopore

In this study, a three-dimensional (3D) computational simulation of bone regeneration was performed in a human tibia under realistic muscle loading. The simulation was achieved using a discrete lattice modeling approach combined with a mechanoregulation algorithm to describe the cellular processes involved in the healing process namely proliferation, migration, apoptosis, and differentiation of cells. The main phases of fracture healing were predicted by the simulation, including the bone resorption phase, and there was a qualitative agreement between the temporal changes in interfragmentary strain and bending stiffness by comparison to experimental data and clinical results. Bone healing was simulated beyond the reparative phase by modeling the transition of woven bone into lamellar bone. Because the simulation has been shown to work with realistic anatomical 3D geometry and muscle loading, it demonstrates the potential of simulation tools for patient-specific pre-operative treatment planning.

JTD Keywords: Tissue differentiation, Computational analysis, Mechanical conditions, Bone regeneration, Weight-bearing, Proliferation, Osteoblast, Stiffness, Ingrowth, Scaffold

Ochratoxin A (OTA) is one of the most important mycotoxins because of its high toxicity to both humans and animals and its occurrence in a number of basic foods and agro-products. The need to develop high-performing methods for OTA analysis able to improve the traditional ones is evident. In this work, through in vitro SELEX (Systematic Evolution of Ligands by EXponential enrichment) two aptamers, designated H8 and H12 were produced that bind with nanomolar affinity with Ochratoxin A (OTA). Two strategies were investigated by using an indirect and a direct competitive Enzyme-Linked Aptamer Assay (ELAA) and were compared to the classical competitive Enzyme-Linked Immunosorbent Assay (ELISA) for the determination of OTA in spiked red wine samples. The limit of detection attained (1 ng/mL), the midpoint value obtained (5 ng/mL) and the analysis time needed (125 min) for the real sample analysis validate the direct competitive ELAA as useful screening tool for routine use in the control of OTA level in wine.

JTD Keywords: Competitive Enzyme-Linked Aptamer Assay (ELAA), DNA aptamer, Ochratoxin A, SELEX, Wine analysis

This paper depicts a virtual sensor array that allows the user to generate gas sensor synthetic data while controlling a wide variety of the characteristics of the sensor array response: arbitrary number of sensors, support for multi-component gas mixtures and full control of the noise in the system such as sensor drift or sensor aging. The artificial sensor array response is inspired on the response of 17 polymeric sensors for three analytes during 7 month. The main trends in the synthetic gas sensor array, such as sensitivity, diversity, drift and sensor noise, are user controlled. Sensor sensitivity is modeled by an optionally linear or nonlinear method (spline based). The toolbox on data generation is implemented in open source R language for statistical computing and can be freely accessed as an educational resource or benchmarking reference. The software package permits the design of scenarios with a very large number of sensors (over 10000 sensels), which are employed in the test and benchmarking of neuromorphic models in the Bio-ICT European project NEUROCHEM.

JTD Keywords: Data analysis, Circuit noise, Data acquisition, Signal processing

Quantitative measurement of the low-frequency dielectric constants of thick insulators at the nanoscale is demonstrated utilizing ac electrostatic force microscopy combined with finite-element calculations based on a truncated cone with hemispherical apex probe geometry. The method is validated on muscovite mica, borosilicate glass, poly(ethylene naphthalate), and poly(methyl methacrylate). The dielectric constants obtained are essentially given by a nanometric volume located at the dielectric-air interface below the tip, independently of the substrate thickness, provided this is on the hundred micrometer-length scale, or larger.

JTD Keywords: Borosilicate glasses, Finite element analysis, Insulating thin films, Mica, Nanostructured materials, Permittivity, Polymers, Scanning probe microscopy

Objective: Patients with idiopathic rapid eye movement (REM) sleep behavior disorder (IRBD) may show electroencephalographic (EEG) slowing reflecting cortical dysfunction and are at risk for developing neurological conditions characterized by cognitive dysfunction including mild cognitive impairment (MCI), dementia with Lewy bodies and Parkinson's disease with associated dementia. We hypothesized that those IRBD patients who later developed MCI had pronounced cortical EEG slowing at presentation. Methods: Power EEG spectral analysis was blindly quantified from the polysomnographic studies of 23 IRBD patients without cognitive complaints and 10 healthy controls without RBD. After a mean clinical follow-up of 2.40 +/- 1.55 years, 10 patients developed MCI (RBD + MCI) and the remaining 13 remained idiopathic. Results: Patients with RBD + MCI had marked EEG slowing (increased delta and theta activity) in central and occipital regions during wakefulness and REM sleep, particularly in the right hemisphere, when compared with controls and, to a lesser extent, with IRBD subjects who remained idiopathic. The EEG spectral pattern of the RBD + MCI group was similar to that seen in patients with dementia with Lewy bodies and Parkinson's disease associated with dementia. Conclusion: Our findings suggest that the presence of marked EEG slowing on spectral analysis might be indicative of the short-term development of MCI in patients initially diagnosed with IRBD.

JTD Keywords: Idiopathic REM sleep behavior disorder, Power EEG spectral analysis, Mild cognitive impairment, REM sleep, Parkinson's disease, Dementia with Lewy bodies

A new drift compensation method based on Common Principal Component Analysis (CPCA) is proposed. The drift variance in data is found as the principal components computed by CPCA. This method finds components that are common for all gasses in feature space. The method is compared in classification task with respect to the other approaches published where the drift direction is estimated through a Principal Component Analysis (PCA) of a reference gas. The proposed new method - employing no specific reference gas, but information from all gases -has shown the same performance as the traditional approach with the best-fitted reference gas. Results are shown with data lasting 7-months including three gases at different concentrations for an array of 17 polymeric sensors.

JTD Keywords: Gas sensor array, Drift, Common principal component, Analysis, Component correction, Electronic nose

A computational model of mechanoregulation is proposed to predict bone tissue formation stimulated mechanically by overall dynamical compression within a porous polymeric scaffold rendered by micro-CT. Dynamic compressions of 0.5-5% at 0.0025-0.025 s(-1) were simulated. A force-controlled dynamic compression was also performed by imposing a ramp of force from 1 to 70 N. The model predicts homogeneous mature bone tissue formation under strain levels of 0.5-1% at strain rates of 0.0025-0.005 s(-1). Under higher levels of strain and strain rates, the scaffold shows heterogeneous mechanical behaviour which leads to the formation of a heterogeneous tissue with a mixture of mature bone and fibrous tissue. A fibrous tissue layer was also predicted under the force-controlled dynamic compression, although the same force magnitude was found promoting only mature bone during a strain-controlled compression. The model shows that the mechanical stimulation of bone tissue formation within a porous scaffold closely depends on the loading history and on the mechanical behaviour of the scaffold at local and global scales.

JTD Keywords: Bone tissue engineering, Scaffold, Tissue differentiation, Mechanoregulation, Finite element analysis

Traditional time-domain techniques of data analysis are often not sufficient to characterize the complex dynamics of the cardiorespiratory interdependencies during the weaning trials. In this paper, the interactions between the heart rate (HR) and the breathing rate (BR) were studied using joint symbolic dynamic analysis. A total of 133 patients on weaning trials from mechanical ventilation were analyzed: 94 patients with successful weaning (group S) and 39 patients that failed to maintain spontaneous breathing (group F). The word distribution matrix enabled a coarse-grained quantitative assessment of short-term nonlinear analysis of the cardiorespiratory interactions. The histogram of the occurrence probability of the cardiorespiratory words presented a higher homogeneity in group F than in group S, measured with a higher number of forbidden words in group S as well as a higher number of words whose probability of occurrence is higher than a probability threshold in group S. The discriminant analysis revealed the best results when applying symbolic dynamic variables. Therefore, we hypothesize that joint symbolic dynamic analysis provides enhanced information about different interactions between HR and BR, when comparing patients with successful weaning and patients that failed to maintain spontaneous breathing in the weaning procedure.

JTD Keywords: Dynamical nonlinearities analysis, Cardiorespiratory interdependencies, Joint symbolic dynamic, Weaning procedure

An analysis of accuracy of time-constant spectrum extraction from thermal transients has been performed. Numerical calculations based on analytical models and finite element method simulations have been used in order to obtain the thermal transients. Simple geometries have been used such that analytical expressions for their time-constant spectrums are known. Results show that a large error in the time-constant spectrum is obtained for very small rms error ( 1 mK) in the thermal transient. The estimation problem is ill-conditioned. Moreover, the differential structure function shows a low accuracy identifying stacked structures. The initial part of the differential structure function shows numerical oscillations and the final part has an asymptotic behavior to infinity that has been identified as an artifact related to errors in the time-constant spectrum estimation. Peak identification from the differential structure function heavily depends on an accurate determination of the time-constant spectrum. The limited spectral resolution and dynamic range of the differential structure function are a direct consequence of the time-constant spectrum imprecision.

JTD Keywords: Finite element analysis, Spectral analysis

The differentiation of obstructive and central respiratory events is a major challenge in the diagnosis of sleep disordered breathing. Esophageal pressure (Pes) measurement is the gold-standard method to identify these events but its invasiveness deters its usage in clinical routine. Flattening patterns appear in the airflow signal during episodes of inspiratory flow limitation (IFL) and have been shown with invasive techniques to be useful to differentiate between central and obstructive hypopneas. In this study we present a new method for the automatic non-invasive differentiation of obstructive and central hypopneas solely with nasal airflow. An overall of 36 patients underwent full night polysomnography with systematic Pes recording and a total of 1069 hypopneas were manually scored by human experts to create a gold-standard annotation set. Features were automatically extracted from the nasal airflow signal to train and test our automatic classifier (Discriminant Analysis). Flattening patterns were non-invasively assessed in the airflow signal using spectral and time analysis. The automatic non-invasive classifier obtained a sensitivity of 0.71 and an accuracy of 0.69, similar to the results obtained with a manual non-invasive classification algorithm. Hence, flattening airflow patterns seem promising for the non-invasive differentiation of obstructive and central hypopneas.

JTD Keywords: Practical, Experimental/ biomedical measurement, Feature extraction, Flow measurement, Medical disorders, Medical signal processing, Patient diagnosis, Pneumodynamics, Pressure measurement, Signal classification, Sleep, Spectral analysis/ automatic noninvasive differentiation, Obstructive hypopnea, Central hypopnea, Inspiratory flow limitation, Nasal airflow, Esophageal pressure, Polysomnography, Feature extraction, Discriminant analysis, Spectral analysis

In this study we propose the correntropy function as a discriminative measure for detecting nonlinearities in the respiratory pattern of chronic heart failure (CHF) patients with periodic or nonperiodic breathing pattern (PB or nPB, respectively). The complexity seems to be reduced in CHF patients with higher risk level. Correntropy reflects information on both, statistical distribution and temporal structure of the underlying dataset. It is a suitable measure due to its capability to preserve nonlinear information. The null hypothesis considered is that the analyzed data is generated by a Gaussian linear stochastic process. Correntropy is used in a statistical test to reject the null hypothesis through surrogate data methods. Various parameters, derived from the correntropy and correntropy spectral density (CSD) to characterize the respiratory pattern, presented no significant differences when extracted from the iteratively refined amplitude adjusted Fourier transform (IAAFT) surrogate data. The ratio between the powers in the modulation and respiratory frequency bands R was significantly different in nPB patients, but not in PB patients, which reflects a higher presence of nonlinearities in nPB patients than in PB patients.

JTD Keywords: Practical, Theoretical or Mathematical, Experimental/cardiology diseases, Fourier transforms, Medical signal processing, Pattern classification, Pneumodynamics, Spectral analysis, Statistical analysis, Stochastic processes/ correntropy based nonlinearity test, Chronic heart failure, Correntropy function, Respiratory pattern nonlinearities, CHF patients, Nonperiodic breathing pattern, Dataset statistical distribution, Dataset temporal structure, Nonlinear information, Null hypothesis, Gaussian linear stochastic process, Statistical test, Correntropy spectral density, Iteratively refined amplitude adjusted Fourier transform, Surrogate data, Periodic breathing pattern

Statistical methods like Principal Components Analysis (PCA) or Partial Least Squares (PLS) and multiscale approaches, have been reported to be very useful in the task of fault diagnosis of malfunctioning sensors for several types of faults. In this work, we compare the performance of PCA and Multiscale-PCA on a fault based on a change of sensor sensitivity. This type of fault affects chemical gas sensors and it is one of the effects of the sensor poisoning. These two methods will be applied on a dataset composed by the signals of 17 conductive polymer gas sensors, measuring three analytes at several concentration levels during 10 months. Therefore, additionally to performance's comparison, both method's stability along the time will be tested. The comparison between both techniques will be made regarding three aspects; detection, identification of the faulty sensors and correction of faulty sensors response.

JTD Keywords: Fault diagnosis, Gas sensors, Principal component analysis

Statistical analysis, power spectral density, and Lempel Ziv complexity, are used in a multi-parameter approach to analyze four temporal series obtained from the Electrocardiographic and Respiratory Flow signals of 126 patients on weaning trials. In which, 88 patients belong to successful group (SG), and 38 patients belong to failure group (FG), i.e. failed to maintain spontaneous breathing during trial. It was found that mean values of cardiac inter-beat and breath durations give higher values for SG than for FG; Kurtosis coefficient of the spectrum of the rapid shallow breathing index is higher for FG; also Lempel Ziv complexity mean values associated with the respiratory flow signal are bigger for FG. Patients were then classified with a pattern recognition neural network, obtaining 80% of correct classifications (81.6% for FG and 79.5% for SG).

JTD Keywords: Electrocardiography, Medical signal processing, Neural nets, Pattern recognition, Pneumodynamics, Signal classification, Statistical analysis, ECG, Kurtosis coefficient, Lempel Ziv complexity, Breath durations, Cardiac interbeat durations, Electrocardiography, Multiparameter analysis, Pattern recognition neural network, Power spectral density, Respiratory flow signals, Signal classification, Spontaneous breathing, Statistical analysis, Weaning trials

Sleep science and respiratory engineering as medical subspecialties and research areas grew up side-by-side with biomedical engineering. The formation of EMBS in the 1950's and the discovery of REM sleep in the 1950's led to parallel development and interaction of sleep and biomedical engineering in diagnostics and therapeutics.

JTD Keywords: Practical/ biomedical equipment, Biomedical measurement, Patient diagnosis, Patient monitoring, Patient treatment, Pneumodynamics, Sleep/ sleep engineering, Respiratory engineering, Automatic sleep analysis, Automatic sleep interpretation systems, Breathing, Biomedical, Engineering, Diagnostics, Therapeutics, REM sleep, Portable, Measurement, Ambulatory measurement, Monitoring

A considerable number of patients in weaning process have problems to keep spontaneous breathing during the trial and after it. This study proposes to extract characteristic parameters of the RR series and respiratory flow signal according to the patients' condition in weaning test. Three groups of patients have been considered: 93 patients with successful trials (group S), 40 patients that failed to maintain spontaneous breathing (group F), and 21 patients who had successful weaning trials, but that had to be reintubated before 48 hours (group R). The characterization was performed using spectral analysis of the signals, through the power spectral density, cross power spectral density and Coherence method. The parameters were extracted on the three frequency bands (VLF, LF and HF), and the principal statistical differences between groups were obtained in bands of VLF and HF. The results show an accuracy of 76.9% in the classification of the groups S and F.

JTD Keywords: Biomedical measurement, Electrocardiography, Medical signal processing, Pneumodynamics, Spectral analysis, RR series, Coherence method, Cross power spectral density, Electrocardiography, Principal statistical differences, Respiratory flow signal, Spectral analysis, Spontaneous breathing, Weaning test

Transcription Factor binding sites are short and degenerate sequences, located mostly at the promoter of the gene, where some proteins bind in order to regulate transcription. Locating these sequences is an important issue, and many experimental and computational methods have been developed. Algorithms to search binding sites are usually based on Position Specific Scoring Matrices (PSSM), where each position is treated independently. Mapping symbolical DNA to numerical sequences, a detector has been built with a Principal Component Analysis of the numerical sequences, taking into account covariances between positions. When a treatment of missing values is incorporated the Q-residuals detector, based on PCA, performs better than a PSSM algorithm. The performance on the detector depends on the estimation of missing values and the percentage of missing values considered in the model.

JTD Keywords: Binding sites, BPCA, Missing values, Numerical DNA, Principal components analysis, Transcription factors

A computational model based on finite element method (FEM) and computational fluid dynamics (CFD) is developed to analyse the mechanical stimuli in a composite scaffold made of polylactic acid (PLA) matrix with calcium phosphate glass (Glass) particles. Different bioreactor loading conditions were simulated within the scaffold. In vitro perfusion conditions were reproduced in the model. Dynamic compression was also reproduced in an uncoupled fluid-structure scheme: deformation level was studied analyzing the mechanical response of scaffold alone under static compression while strain rate was studied considering the fluid flow induced by compression through fixed scaffold. Results of the model show that during perfusion test an inlet velocity of 25mum/s generates on scaffold surface a fluid flow shear stress which may stimulate osteogenesis. Dynamic compression of 5% applied on the PLA-Glass scaffold with a strain rate of 0.005s(-1) has the benefit to generate mechanical stimuli based on both solid shear strain and fluid flow shear stress on large scaffold surface area. Values of perfusion inlet velocity or compression strain rate one order of magnitude lower may promote cell proliferation while values one order of magnitude higher may be detrimental for cells. FEM-CFD scaffold models may help to determine loading conditions promoting bone formation and to interpret experimental results from a mechanical point of view.

JTD Keywords: Bone tissue engineering, Scaffold, Finite element analysis, Computational fluid dynamics, Mechanical stimuli

This work describes our studies on the molecular design of interfacial architectures suitable for DNA sensing which could resist non-specific binding of nanomaterials commonly used as labels for amplifying biorecognition events. We observed that the non-specific binding of bio-nanomaterials to surface-confined oligonucleotide strands is highly dependent on the characteristics of the interfacial architecture. Thiolated double stranded oligonucleotide arrays assembled on Au surfaces evidence significant fouling in the presence of nanoparticles (NPs) at the nanomolar level. The non-specific interaction between the oligonucleotide strands and the nanomaterials can be sensitively minimized by introducing streptavidin (SAv) as an underlayer conjugated to the DNA arrays. The role of the SAv layer was attributed to the significant hydrophilic repulsion between the SAv-modified surface and the nanomaterials in close proximity to the interface, thus conferring outstanding anti-fouling characteristics to the interfacial architecture. These results provide a simple and straightforward strategy to overcome the limitations introduced by the non-specific binding of labels to achieve reliable detection of DNA-based biorecognition events.

JTD Keywords: DNA/ analysis, Gold, Nanostructures/ chemistry, Oligonucleotide Array Sequence Analysis/ instrumentation, Oligonucleotides/ chemistry, Streptavidin/ chemistry, Sulfhydryl Compounds

Analytical devices able to perform accurate and fast automatic DNA detection or sequencing procedures have many potential benefits in the biomedical and environmental fields. The conversion of biological or biochemical responses into quantifiable optical, mechanical or electronic signals is achieved by means of biosensors. Most of these transducing elements can be miniaturized and incorporated into lab-on-a-chip devices, also known as Micro Total Analysis Systems. The use of multiple DNA biosensors integrated in these miniaturized laboratories, which perform several analytical operations at the microscale, has many cost and efficiency advantages. Tiny amounts of reagents and samples are needed and highly sensitive, fast and parallel assays can be done at low cost. A particular type of DNA biosensors are the ones used based on electrochemical principles. These sensors offer several advantages over the popular fluorescence-based detection schemes. The resulting signal is electrical and can be processed by conventional electronics in a very cheap and fast manner. Furthermore, the integration and miniaturization of electrochemical transducers in a microsystem makes easier its fabrication in front of the most common currently used detection method. In this review, different electrochemical DNA biosensors integrated in analytical microfluidic devices are discussed and some early stage commercial products based on this strategy are presented.

JTD Keywords: DNA, Electrochemical DNA biosensors, Electrochemistry, Lab-on-a-chip, Micro Total Analysis systems, Field-effect transistors, Sequence-specific detection, Chemical-analysis systems, Solid-state nanopores, Carbon nanotubes, Microfluidic device, Electrical detection, Hybridization, Molecules, Sensor

A statistical factorial analysis approach was conducted on a poroelastic finite element model of a lumbar intervertebral disc to analyse the influence of six material parameters (permeabilities of annulus, nucleus, trabecular vertebral bone, cartilage endplate and Young's moduli of annulus and nucleus) on the displacement, fluid pore pressure and velocity fields. Three different loading modes were investigated: compression, flexion and axial rotation. Parameters were varied considering low and high levels in agreement with values found in the literature for both healthy and degenerated lumbar discs. Results indicated that annulus stiffness and cartilage endplate permeability have a strong effect on the overall fluid- and solid-phase responses in all loading conditions studied. Nucleus stiffness showed its main relevance in compression while annulus permeability influenced mainly the annular pressure field. This study confirms the permeability's central role in biphasic modelling and highlights for the lumbar disc which experiments of material property characterization should be performed. Moreover, such sensitivity study gives important guidelines in poroelastic material modelling and finite element disc validation.

JTD Keywords: Intervertebral disc, Permeability, Fractional factorial design, Design of experiments, Finite element analysis

Miniaturization is a powerful trend for smart chemical instrumentation in a diversity of applications.. It is know that miniaturization in IMS leads to a degradation of the system characteristics. For the present work, we are interested in signal processing solutions to mitigate limitations introduced by limited drift tube length that basically involve a loss of chemical selectivity. While blind source separation techniques (BSS) are popular in other domains, their application for smart chemical instrumentation is limited. However, in some conditions, basically linearity, BSS may fully recover the concentration time evolution and the pure spectra with few underlying hypothesis. This is extremely helpful in conditions where non-expected chemical interferents may appear, or unwanted perturbations may pollute the spectra. SIMPLISMA has been advocated by Harrington et al. in several papers. However, more modem methods of BSS for bilinear decomposition with the restriction of positiveness have appeared in the last decade. In order to explore and compare the performances of those methods a series of experiments were performed.

JTD Keywords: Ion Mobility Spectrometry (IMS), Blind Source Separation (BSS), Multivariate Analysis, SIMPLISMA, MCR, Non-Negative Matrix Factorization (NMF)

With the goal of deepen in the understanding of coding of chemical information in the olfactory system, a large data set consisting of rat's olfactory bulb activity values in response to several different volatile compounds has been analyzed by fuzzy c-means clustering methods. Clustering should help to discover groups of glomeruli that are similary activated according to their response profiles across the odorants. To investigate the significance of the achieved fuzzy partitions we developed and applied a novel validity approach based on cluster stability. Our results show certain level of glomerular clustering in the olfactory bulb and indicate that exist a main chemo-topic subdivision of the glomerular layer in few macro-area which are rather specific to particular functional groups of the volatile molecules.

JTD Keywords: Olfactory bulb, 2-deoxyglucose mapping, Olfactory coding, Cluster analysis, Cluster validity

Transcription starts when multiple proteins, known as transcription factors recognize and bind to transcription start site in DNA sequences. Since mutation in transcription factor binding sites are known to underlie diseases it remains a major challenge to identify these binding sites. Conversion from symbolic DNA to numerical sequences and genome data make it possible to construct a detector based on a numerical analysis of DNA binding sites. A subspace model for the TFBS is built. TFBS will show a very small distance to this particular subspace. Using this distance binding sites are distinguished from random sequences and from genome data.

JTD Keywords: Transcription factors, Binding sites, Principal components analysis

The Ischemic Heart Disease (IHD) is characterized by an insufficient supply with blood of the myocardium usually caused by an artherosclerotic disease of the coronary arteries (coronary artery disease CAD). The IHD and its consequences have become a leading problem in the industrialized nations. The aim of this study was to evaluate a new diagnosing method, the cardiogoniometry, using two different classifying techniques: the method of linear discriminant function analysis (LDA) and the method of Support Vector Machines (SVM). Data of a group of 109 female subjects (62 healthy, 47 with IHD) were analyzed on the basis of extracted parameters from the three-dimensional vector loops of the heart. The LDA achieved an accuracy of 83,5% (Sensitivity 78,7%, Specificity 87,1%), whereas the SVM achieved an accuracy of 86% (Sensitivity 80,5%, Specificity 89,8%). It could be shown that cardiogoniometry, an electrophysiological diagnostic method performed at rest, detects variables that are helpful in identifying ischemic heart disease. As it is easy to apply, non-invasive, and provides an automated interpretation it may become an inexpensive addition to the cardiologic diagnostic armamentarium, possibly useful for early diagnosis of IHD or CAD, as well as in patients who do not tolerate exercise testing. It was also proven that by applying Support Vector Machines an increased diagnostic precision in comparison to the conventional discriminant function analysis can be achieved.

JTD Keywords: Cardiogoniometry, Support Vector Machines, Nonlinear classifier, Linear discriminant analysis, Vector loop

The Streptococcus pyogenes genome harbors two clusters of class Ib ribonucleotide reductase genes, nrdHEF and nrdF*I*E*, and a second stand-alone nrdI gene, designated nrdI2. We show that both clusters are expressed simultaneously as two independent operons. The NrdEF enzyme is functionally active in vitro, while the NrdE*F* enzyme is not. The NrdF* protein lacks three of the six highly conserved iron-liganding side chains and cannot form a dinuclear iron site or a tyrosyl radical. In vivo, on the other hand, both operons are functional in heterologous complementation in Escherichia coli. The nrdF*I*E* operon requires the presence of the nrdI* gene, and the nrdHEF operon gained activity upon cotranscription of the heterologous nrdI gene from Streptococcus pneumoniae, while neither nrdI* nor nrdI2 from S. pyogenes rendered it active. Our results highlight the essential role of the flavodoxin NrdI protein in vivo, and we suggest that it is needed to reduce met-NrdF, thereby enabling the spontaneous reformation of the tyrosyl radical. The NrdI* flavodoxin may play a more direct role in ribonucleotide reduction by the NrdF*I*E* system. We discuss the possibility that the nrdF*I*E* operon has been horizontally transferred to S. pyogenes from Mycoplasma spp.

JTD Keywords: Group-a streptococcus, Bacillus-subtilis genes, Escherichia-coli, Corynebacterium-ammoniagenes, Mycobacterium-tuberculosis, Expression analysis, Genome sequence, Small-subunit, Salmonella-typhimurium, Iron center

The H-NS protein plays a significant role in the modulation of gene expression in Gram-negative bacteria. Whereas isolation and characterization of hns mutants in Escherichia coli, Salmonella and Shigella represented critical steps to gain insight into the modulatory role of H-NS, it has hitherto not been possible to isolate hns mutants in Yersinia. The hns mutation is considered to be deleterious in this genus. To study the modulatory role of H-NS in Yersinia we circumvented hns lethality by expressing in Y. enterocolitica a truncated H-NS protein known to exhibit anti-H-NS activity in E. coli (H-NST(EPEC)). Y. enterocolitica cells expressing H-NST(EPEC) showed an altered growth rate and several differences in the protein expression pattern, including the ProV protein, which is modulated by H-NS in other enteric bacteria. To further confirm that H-NST(EPEC) expression in Yersinia can be used to demonstrate H-NS-dependent regulation in this genus, we used this approach to show that H-NS modulates expression of the YmoA protein.

JTD Keywords: Bacterial Proteins/biosynthesis/genetics/ physiology, DNA-Binding Proteins/biosynthesis/genetics/ physiology, Electrophoresis, Gel, Two-Dimensional, Gene Expression Profiling, Gene Expression Regulation, Bacterial, Genes, Essential, Proteome/analysis, RNA, Bacterial/biosynthesis, RNA, Messenger/biosynthesis, Reverse Transcriptase Polymerase Chain Reaction, Sequence Deletion, Yersinia enterocolitica/chemistry/genetics/growth & development/ physiology

Mechanical stimuli are one of the factors that affect cell proliferation and differentiation in the process of bone tissue regeneration. Knowledge on the specific deformation sensed by cells at a microscopic level when mechanical loads are applied is still missing in the development of biomaterials for bone tissue engineering. The objective of this study was to analyze the behavior of the mechanical stimuli within some calcium phosphate-based scaffolds in terms of stress and strain distributions in the solid material phase and fluid velocity, fluid pressure and fluid shear stress distributions in the pores filled of fluid, by means of micro computed tomographed (CT)-based finite element (FE) models. Two samples of porous materials, one of calcium phosphate-based cement and another of biodegradable glass, were used. Compressive loads equivalent to 0.5% of compression applied to the solid material phase and interstitial fluid flows with inlet velocities of 1, 10 and 100 mu m/s applied to the interconnected pores were simulated, changing also the inlet side and the viscosity of the medium. Similar strain distributions for both materials were found, with compressive and tensile strain maximal values of 1.6% and 0.6%, respectively. Mean values were consistent with the applied deformation. When 10 mu m/s of inlet fluid velocity and 1.45 Pa s viscosity, maximal values of fluid velocity were 12.76 mm/s for CaP cement and 14.87 mm/s for glass. Mean values were consistent with the inlet ones applied, and mean values of shear stress were around 5 x 10(-5) Pa. Variations on inlet fluid velocity and fluid viscosity produce proportional and independent changes in fluid velocity, fluid shear stress and fluid pressure. This study has shown how mechanical loads and fluid flow applied on the scaffolds cause different levels of mechanical stimuli within the samples according to the morphology of the materials.

JTD Keywords: Bone tissue engineering, Finite element analysis, Scaffolds, Mechanical stimuli

Bioabsorbable materials are of great interest for bone regeneration applications, since they are able to degrade gradually as new tissue is formed. In this work, a fully biodegradable composite material containing polylactic acid (PLA) and calcium phosphate (CaP) soluble glass particles has been characterized in terms of surface properties and cell response. Cell cultures were performed in direct contact with the materials and also with their extracts, and were evaluated using the MTT assay, alkaline phosphatase activity, and osteocalcin measurements. The CaP glass and PLA were used as reference materials. No significant differences were observed in cell proliferation with the extracts containing the degradation by-products of the three materials studied. A relation between the materials wettability and the material-cell interactions at the initial stages of contact was observed. The most hydrophilic material (CaP glass) presented the highest cell adhesion values as well as an earlier differentiation, followed by the PLA/glass material. The incorporation of glass particles into the PLA matrix increased surface roughness. SEM images showed that the heterogeneity of the composite material induced morphological changes in the cells cytoskeleton.

JTD Keywords: Glass, Polylactic acid, Surface analysis, Cell culture, In vitro test

In this paper we compare three different spectral estimation techniques for the classification of mental tasks. These techniques are the standard periodogram, the Welch periodogram and the Burg method, applied to electroencephalographic (EEG) signals. For each one of these methods we compute two parameters: the mean power and the root mean square (RMS), in various frequency bands. The classification of the mental tasks was conducted with a linear discriminate analysis. The Welch periodogram and the Burg method performed better than the standard periodogram. The use of the RMS allows better classification accuracy than the obtained with the power of EEG signals.

JTD Keywords: Adult, Algorithms, Artificial Intelligence, Cognition, Electroencephalography, Female, Humans, Male, Pattern Recognition, Automated, Reproducibility of Results, Sensitivity and Specificity, Task Performance and Analysis, User-Computer Interface

This study involves the mechanical and structural characterisation of completely degradable scaffolds for tissue engineering applications. The scaffolds are a composite of polylactic acid (PLA) and a soluble calcium phosphate glass, and are thus completely degradable. A factorial experimental design was applied to optimise scaffold composition prior to simultaneous microtomography and micromechanical testing. Synchrotron X-ray microtomography combined with in situ micromechanical testing was performed to obtain three-dimensional 3D images of the scaffolds under compression. The 3D reconstruction was converted into a finite element mesh which was validated by simulating a compression test and comparing it with experimental results. The experimental design reveals that larger glass particle and pore sizes reduce the stiffness of the scaffolds, and that the porosity is largely unaffected by changes in pore sizes or glass weight content. The porosity ranges between 93% and 96.5%, and the stiffness ranges between 50 and 200 kPa. X-ray projections show a homogeneous distribution of the glass particles within the PLA matrix, and illustrate pore-wall breakage under strain. The 3D reconstructions are used qualitatively to visualise the distribution of the phases of the composite material, and to follow pore deformation under compression. Quantitatively, scaffold porosity, pore interconnectivity and surface/volume ratios have been calculated. Finite element analysis revealed the stress and strain distribution in the scaffold under compression, and could be used in the future to characterise the mechanical properties of the scaffolds.

JTD Keywords: Synchrotron x-ray microtomography, Mechanical test, Biodegradable, Glass, Scaffold, Finite element analysis