Publications

Odorant discrimination mechanisms are based on the differential interactions between odorant molecules and olfactory receptors (ORs). Biohybrid sensors based on ORs described to date show selectivity towards specific versus non-specific binding of odorants, being unable to distinguish between specific ligands of different affinity. Here we disclose a method that enables odorant discrimination based on the modulation of the capacitive response of the receptor, which allows the differentiation of three high-affinity hOR1A1 agonists. We performed voltammetry and impedance measurements of the hOR1A1 receptor selectively immobilized on a gold electrode in the absence and presence of the agonists. Binding induces a decrease in the capacitive response of the receptor that is proportional to the ligand potency, reaching up to a 40% decrease for the cognate ligand dihydrojasmone, which is attributed to changes in the magnitude and orientation of the electric dipole in the receptor, thereby regulating its response to the applied electric field.

JTD Keywords: Agonist, Biosenso, Electric dipol, Electrochemical impedance spectroscopy, Impedance, Nose, Odorant receptors, Olfactory receptor, Selectivity, Specific capacitance

Electronic noses have improved in terms of reliability in the last two decades. Their design has allowed for model training and validation for predicting odour emissions and classifying odour sources. In the last few years, interest has turned to designing e-noses capable of flying in drones. Fast 3D mapping of areas where odour might become a problem, such as Wastewater Treatment Plants, Compost Plants, and Refineries, has been the main target of some recent studies. Here, a fully functional design of a drone-embedded, E-Nosebased measurement platform is presented. The design of its ENose and its fast-sampling frequency will allow for fast tracking of plumes and fast 3D odour mapping. In this contribution, a description of the system is provided in addition to preliminary measurements in the laboratory characterizing the fast response of the E-Nose to an odour stimulus.

JTD Keywords: Autonomous, Drone, E-nose, Iot, Machine learnin, Odour

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

The extracellular matrix (ECM) of the lung is a filamentous network composed mainly of collagens, elastin, and proteoglycans that provides structural and physical support to its populating cells. Proliferation, migration and overall behaviour of those cells is greatly determined by micromechanical queues provided by the ECM. Lung fibrosis displays an aberrant increased deposition of ECM which likely changes filament organization and stiffens the ECM, thus upregulating the profibrotic profile of pulmonary cells. We have previously used AFM to assess changes in the Young’s Modulus (E) of the ECM in the lung. Here, we perform further ECM topographical, mechanical and viscoelastic analysis at the micro- and nano-scale throughout fibrosis development. Furthermore, we provide nanoscale correlations between topographical and elastic properties of the ECM fibres. Firstly, we identify a softening of the ECM after rats are instilled with media associated with recovery of mechanical homeostasis, which is hindered in bleomycin-instilled lungs. Moreover, we find opposite correlations between fibre stiffness and roughness in PBS- vs bleomycin-treated lung. Our findings suggest that changes in ECM nanoscale organization take place at different stages of fibrosis, with the potential to help identify pharmacological targets to hinder its progression.

JTD Keywords: atomic force microscopy, cells, deposition, extracellular matrix, idiopathic pulmonary fibrosis, mechanisms, mechanosensing, membranes, micromechanical properties, pathogenesis, stiffness, tissues, viscoelasticity, Extracellular matrix, Induced lung fibrosis, Mechanosensing

Proprioceptive sensory neurons (pSN) are an essential and undervalued part of the neuromuscular circuit. A protocol to differentiate healthy and amyotrophic lateral sclerosis (ALS) human neural stem cells (hNSC) into pSN, and their comparison with the motor neuron (MN) differentiation process from the same hNSC sources, facilitated the development of in vitro co-culture platforms. The obtained pSN spheroids cultured interact with human skeletal myocytes showing the formation of annulospiral wrapping-like structures between TrkC + neurons and a multinucleated muscle fibre, presenting synaptic bouton-like structures in the contact point. The comparative analysis of the genetic profile performed in healthy and sporadic ALS hNSC differentiated to pSN suggested that basal levels of ETV1, critical for motor feedback from pSN, were much lower for ALS samples and that the differences between healthy and ALS samples, suggest the involvement of pSN in ALS pathology development and progression.© 2022. The Author(s).

JTD Keywords: Amyotrophic-lateral-sclerosis,pluripotent stem-cells,peripheral nervous-system,stretch reflex arc,mechanosensory circuit,cellular-localization,molecular-cloning,motor-neurons,muscle,expressio

Conventionally, odours emitted by different sources present in wastewater treatment plants (WWTPs) are measured by dynamic olfactometry, where a human panel sniffs and analyzes air bags collected from the plant. Although the method is considered the gold standard, the process is costly, slow, and infrequent, which does not allow operators to quickly identify and respond to problems. To better monitor and map WWTP odour emissions, here we propose a small rotary-wing drone equipped with a lightweight (1.3-kg) electronic nose. The "sniffing drone" sucks in air via a ten-meter (33-foot) tube and delivers it to a sensor chamber where it is analyzed in real-time by an array of 21 gas sensors. From the sensor signals, machine learning (ML) algorithms predict the odour concentration that a human panel using the EN13725 methodology would report. To calibrate and validate the predictive models, the drone also carries a remotely controlled sampling device (compliant with EN13725:2022) to collect sample air in bags for post-flight dynamic olfactometry. The feasibility of the proposed system is assessed in a WWTP in Spain through several measurement campaigns covering diverse operating regimes of the plant and meteorological conditions. We demonstrate that training the ML algorithms with dynamic (transient) sensor signals measured in flight conditions leads to better performance than the traditional approach of using steady-state signals measured in the lab via controlled exposures to odour bags. The comparison of the electronic nose predictions with dynamic olfactometry measurements indicates a negligible bias between the two measurement techniques and 95 % limits of agreement within a factor of four. This apparently large disagreement, partly caused by the high uncertainty of olfactometric measurements (typically a factor of two), is more than offset by the immediacy of the predictions and the practical advantages of using a drone-based system.Copyright © 2022. Published by Elsevier B.V.

JTD Keywords: calibration, chemical sensors, drone, dynamic olfactometry, electronic nose, odourquantification, olfaction, volatile organic-compounds, wwtp, Calibration, Chemical sensors, Drone, Dynamic olfactometry, Electronic nose, Environmental monitoring, Odour quantification, Olfaction, Variable selection methods, Wwtp

Cells are subjected to multiple mechanical inputs throughout their lives. Their ability to detect these environmental cues is called mechanosensing, a process in which integrins play an important role. During cellular mechanosensing, plasma membrane (PM) tension is adjusted to mechanical stress through the buffering action of caveolae; however, little is known about the role of caveolae in early integrin mechanosensing regulation. Here, we show that Cav1KO fibroblasts increase adhesion to FN-coated beads when pulled with magnetic tweezers, as compared to wild type fibroblasts. This phenotype is Rho-independent and mainly derived from increased active b1-integrin content on the surface of Cav1KO fibroblasts. FRAP analysis and endocytosis/recycling assays revealed that active b1-integrin is mostly endocytosed through the CLIC/GEEC pathway and is more rapidly recycled to the PM in Cav1KO fibroblasts, in a Rab4 and PM tension-dependent manner. Moreover, the threshold for PM tension-driven b1-integrin activation is lower in Cav1KO MEFs than in wild type MEFs, through a mechanism dependent on talin activity. Our findings suggest that caveolae couple mechanical stress to integrin cycling and activation, thereby regulating the early steps of the cellular mechanosensing response.© 2022, Lolo et al.

JTD Keywords: adhesion, alpha-v-beta-3, cell, integrin activation, internalization, kinase, mechanosensing, mediated endocytosis, mouse, stiffness, talin, trafficking, Animals, Caveolae, Cell adhesion, Cell biology, Fibroblasts, Integrin activation, Integrin beta1, Integrin recycling, Integrins, Mechanosensing, Membrane tension, Mice, Mouse, Stress, mechanical

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

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

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

Pulmonary fibrosis (PF) is a progressive disease that disrupts the mechanical homeostasis of the lung extracellular matrix (ECM). These effects are particularly relevant in the lung context, given the dynamic nature of cyclic stretch that the ECM is continuously subjected to during breathing. This work uses an in vivo model of pulmonary fibrosis to characterize the macro-and micromechanical properties of lung ECM subjected to stretch. To that aim, we have compared the micromechanical properties of fibrotic ECM in baseline and under stretch conditions, using a novel combination of Atomic Force Microscopy (AFM) and a stretchable membrane-based chip. At the macroscale, fibrotic ECM displayed strain-hardening, with a stiffness one order of magnitude higher than its healthy counterpart. Conversely, at the microscale, we found a switch in the stretch-induced mechanical behaviour of the lung ECM from strain-hardening at physiological ECM stiffnesses to strain-softening at fibrotic ECM stiffnesses. Similarly, we observed solidification of healthy ECM versus fluidization of fibrotic ECM in response to stretch. Our results suggest that the mechanical behaviour of fibrotic ECM under stretch involves a potential built-in mechanotransduction mechanism that may slow down the progression of PF by steering resident fibroblasts away from a pro-fibrotic profile. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.

JTD Keywords: atomic force microscopy, extracellular matrix, fibrosis, mechanics, mechanosensing, strain, system, viscoelasticity, Atomic force microscopy, Extracellular matrix, Fibrosis, Lung fibrosis, Mechanosensing

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

Commercial printers based on fused deposition modeling (FDM) are widely adopted for 3D printing applications. This method consists of the heating of polymeric filaments over the melting point followed by their deposition onto a solid base to create the desirable 3D structure. Prior investigation using chromatographic techniques has shown that chemical compounds (e.g. VOCs), which can be harmful to users, are emitted during the printing process, producing adverse effects to human health and contributing to indoor air pollution. In this study, we present a simple, inexpensive and disposable paperbased optoelectronic nose (i.e. colorimetric sensor array) to identify the gaseous emission fingerprint of five different types of thermoplastic filaments (ABS, TPU, PETG, TRITAN and PLA) in the indoor environment. The optoelectronic nose is comprised of selected 15 dyes with different chemical properties deposited onto a microfluidic paper-based device with spots of 5 mm in diameter each. Digital images were obtained from an ordinary flatbed scanner, and the RGB information collected before and after air exposure was extracted by using an automated routine designed in MATLAB, in which the color changes provide a unique fingerprint for each filament in 5 min of printing. Reproducibility was obtained in the range of 2.5-10% (RSD). Hierarchical clustering analysis (HCA) and principal component analysis (PCA) were successfully employed, showing suitable discrimination of all studied filaments and the non-polluted air. Besides, air spiked with vapors of the most representative VOCs were analyzed by the optoelectronic nose and visually compared to each filament. The described study shows the potential of the paper-based optoelectronic nose to monitor possible hazard emissions from 3D printers. (C) 2020 Elsevier B.V. All rights reserved.

JTD Keywords: 3d printing, colorimetric sensor array, indoor air pollution, optoelectronic nose, paper-based, 3d printing, Colorimetric sensor array, Emissions, Indoor air pollution, Optoelectronic nose, Paper-based, Thermoplastic filaments

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)

Engineered immunoglobulin-G molecules (IgGs) are of wide interest for the development of detection elements in protein-based biosensors with clinical applications. The strategy usually employed for the de novo design of such engineered IgGs consists on merging fragments of the three-dimensional structure of a native IgG, which is immobilized on the biosensor surface, and of an antibody with an exquisite target specificity and affinity. In this work conventional and accelerated classical molecular dynamics (cMD and aMD, respectively) simulations have been used to propose two IgG-like antibodies for COVID-19 detection. More specifically, the crystal structure of the IgG1 B12 antibody, which inactivates the human immunodeficiency virus-1, has been merged with the structure of the antibody CR3022 Fab tightly bounded to SARS-CoV-2 receptor-binding domain (RBD) and the structure of the 5309 antibody Fab fragment complexed with SARS-CoV-2 RBD. The two constructed antibodies, named IgG1-CR3022 and IgG1-S309, respectively, have been immobilized on a stable gold surface through a linker. Analyses of the influence of both the merging strategy and the substrate on the stability of the two constructs indicate that the IgG1-S309 antibody better preserves the neutralizing structure than the IgG1-CR3022 one. Overall, results indicate that the IgG1-S309 is appropriated for the generation of antibody based sensors for COVID-19 diagnosis. (C) 2021 The Author(s). Published by Elsevier B.V. on behalf of Research Network of Computational and Structural Biotechnology.

JTD Keywords: cr3022, igg1, molecular engineering, s309, Antibodies, Antibody engineering, Biosensors, Chemical detection, Clinical application, Cov, Cr3022, Crystal structure, Design, Diseases, Gold nanoparticles, Igg1, Igg1 antibody, Immobilization, Immunoglobulin g, Immunosensor, In-silico, Merging, Molecular dynamics, Molecular engineering, Orientation, Protein-based biosensors, Receptor-binding domains, S309, Sars, Sensor, Spike protein, Target, Vaccine, Viruses

Malaria, a parasitic infection caused by Plasmodium parasites and transmitted through the bite of infected female Anopheles mosquitos, is one of the main causes of mortality in many developing countries. Over 200 million new infections and nearly half a million deaths are reported each year, and more than three billion people are at risk of acquiring malaria worldwide. Nevertheless, most malaria cases could be cured if detected early. Malaria eradication is a top priority of the World Health Organisation. However, achieving this goal will require mass population screening and treatment, which will be hard to accomplish with current diagnostic tools. We report an electrochemical point-of-care device for the fast, simple and quantitative detection of Plasmodium falciparum lactate dehydrogenase (PfLDH) in whole blood samples. Sample analysis includes 5-min lysis to release intracellular parasites, and stirring for 5 more min with immuno-modified magnetic beads (MB) along with an immuno-modified signal amplifier. The rest of the magneto-immunoassay, including sample filtration, MB washing and electrochemical detection, is performed at a disposable paper electrode microfluidic device. The sensor provides PfLDH quantitation down to 2.47 ng mL−1 in spiked samples and for 0.006–1.5% parasitemias in Plasmodium-infected cultured red blood cells, and discrimination between healthy individuals and malaria patients presenting parasitemias >0.3%. Quantitative malaria diagnosis is attained with little user intervention, which is not achieved by other diagnostic methods.

JTD Keywords: Electrochemical magneto-immunosensor, Malaria quantitative diagnosis, Paper microfluidic electrode, Plasmodium LDH, Point-of-care (POC) testing

Metal Oxide (MOX) gas sensors rely on chemical reactions that occur efficiently at high temperatures, resulting in too-demanding power requirements for certain applications. Operating the sensor under a Pulsed-Temperature Operation (PTO), by which the sensor heater is switched ON and OFF periodically, is a common practice to reduce the power consumption. However, the sensor performance is degraded as the OFF periods become larger. Other research works studied, generally, PTO schemes applying waveforms to the heater with time periods of seconds and duty cycles above 20%. Here, instead, we explore the behaviour of PTO sensors working under aggressive schemes, reaching power savings of 99% and beyond with respect to continuous heater stimulation. Using sensor sensitivity and the limit of detection, we evaluated four Ultra Low Power (ULP) sensors under different PTO schemes exposed to ammonia, ethylene, and acetaldehyde. Results show that it is possible to operate the sensors with total power consumption in the range of microwatts. Despite the aggressive power reduction, sensor sensitivity suffers only a moderate decline and the limit of detection may degrade up to a factor five. This is, however, gas-dependent and should be explored on a case-by-case basis since, for example, the same degradation has not been observed for ammonia. Finally, the run-in time, i.e., the time required to get a stable response immediately after switching on the sensor, increases when reducing the power consumption, from 10 minutes to values in the range of 10–20 hours for power consumptions smaller than 200 microwatts.

JTD Keywords: Robot sensing systems, Temperature sensors, Heating systems, Gas detectors, Power demand, Sensitivity, Electronic nose, gas sensors, low-power operation, machine olfaction, pulsed-temperature operation, temperature modulation

Biocatalytic micro- and nanomotors have emerged as a new class of active matter self-propelled through enzymatic reactions. The incorporation of functional nanotools could enable the rational design of multifunctional micromotors for simultaneous real-time monitoring of their environment and activity. Herein, we report the combination of DNA nanotechnology and urease-powered micromotors as multifunctional tools able to swim, simultaneously sense the pH of their surrounding environment, and monitor their intrinsic activity. With this purpose, a FRET-labeled triplex DNA nanoswitch for pH sensing was immobilized onto the surface of mesoporous silica-based micromotors. During self-propulsion, urea decomposition and the subsequent release of ammonia led to a fast pH increase, which was detected by real-time monitoring of the FRET efficiency through confocal laser scanning microscopy at different time points (i.e., 30 s, 2 and 10 min). Furthermore, the analysis of speed, enzymatic activity, and propulsive force displayed a similar exponential decay, matching the trend observed for the FRET efficiency. These results illustrate the potential of using specific DNA nanoswitches not only for sensing the micromotors’ surrounding microenvironment but also as an indicator of the micromotor activity status, which may aid to the understanding of their performance in different media and in different applications.

JTD Keywords: Micromotors, DNA-nanoswitch, pH detection, Self-propulsion, Nanosensors, Nanomotors

Cells are constantly submitted to external mechanical stresses, which they must withstand and respond to. By forming a physical boundary between cells and their environment that is also a biochemical platform, the plasma membrane (PM) is a key interface mediating both cellular response to mechanical stimuli, and subsequent biochemical responses. Here, we review the role of the PM as a mechanosensing structure. We first analyse how the PM responds to mechanical stresses, and then discuss how this mechanical response triggers downstream biochemical responses. The molecular players involved in PM mechanochemical transduction include sensors of membrane unfolding, membrane tension, membrane curvature or membrane domain rearrangement. These sensors trigger signalling cascades fundamental both in healthy scenarios and in diseases such as cancer, which cells harness to maintain integrity, keep or restore homeostasis and adapt to their external environment.

JTD Keywords: Plasma membrane, Mechanotransduction, Membrane tension, Mechanosensor

YAP is a mechanosensitive transcriptional activator with a critical role in cancer, regeneration, and organ size control. Here, we show that force applied to the nucleus directly drives YAP nuclear translocation by decreasing the mechanical restriction of nuclear pores to molecular transport. Exposure to a stiff environment leads cells to establish a mechanical connection between the nucleus and the cytoskeleton, allowing forces exerted through focal adhesions to reach the nucleus. Force transmission then leads to nuclear flattening, which stretches nuclear pores, reduces their mechanical resistance to molecular transport, and increases YAP nuclear import. The restriction to transport is further regulated by the mechanical stability of the transported protein, which determines both active nuclear transport of YAP and passive transport of small proteins. Our results unveil a mechanosensing mechanism mediated directly by nuclear pores, demonstrated for YAP but with potential general applicability in transcriptional regulation. Force-dependent changes in nuclear pores control protein access to the nucleus.

JTD Keywords: Atomic force microscopy, Hippo pathway, Mechanosensing, Mechanotransduction, Molecular mechanical stability, Nuclear mechanics, Nuclear pores, Nuclear transport, Rigidity sensing, Transcription regulation

Inherent variability of chemical sensors makes it necessary to calibrate chemical detection systems individually. This shortcoming has traditionally limited usability of systems based on metal oxide gas sensor arrays and prevented mass-production for some applications. Here, aiming at exploring calibration transfer between chemical sensor arrays, we exposed five twin 8-sensor detection units to different concentration levels of ethanol, ethylene, carbon monoxide, or methane. First, we built calibration models using data acquired with a master unit. Second, to explore the transferability of the calibration models, we used Direct Standardization to map the signals of a slave unit to the space of the master unit in calibration. In particular, we evaluated the transferability of the calibration models to other detection units, and within the same unit measuring days apart. Our results show that signals acquired with one unit can be successfully mapped to the space of a reference unit. Hence, calibration models trained with a master unit can be extended to slave units using a reduced number of transfer samples, diminishing thereby calibration costs. Similarly, signals of a sensing unit can be transformed to match sensor behavior in the past to mitigate drift effects. Therefore, the proposed methodology can reduce calibration costs in mass-production and delay recalibrations due to sensor aging. Acquired dataset is made publicly available.

JTD Keywords: Calibration transfer, Chemical sensors, Direct Standardization, Electronic nose, MOX sensors, Public dataset

Cell membrane proteins are involved in a variety of biochemical pathways and therefore constitute important targets for therapy and development of new drugs. Bioanalytical platforms and binding assays using these membrane protein receptors for drug screening or diagnostic require the construction of well-characterized liposome and lipid bilayer arrays that act as support to prevent protein denaturation during biochip processing. Quantification of the protein receptors in the lipid membrane arrays is a key issue in order to produce reproducible and well-characterized chips. Herein, we report a novel immunochemical analytical approach for the quantification of membrane proteins (i.e., G-protein-coupled receptor, GPCR) in nanovesicles (NVs). The procedure allows direct determination of tagged receptors (i.e., c-myc tag) without any previous protein purification or extraction steps. The immunochemical method is based on a microplate ELISA format and quantifies this tag on proteins embedded in NVs with detectability in the picomolar range, using protein bioconjugates as reference standards. The applicability of the method is demonstrated through the quantification of the c-myc-olfactory receptor (OR, c-myc-OR1740) in the cell membrane NVs. The reported method opens the possibility to develop well-characterized drug-screening platforms based on G-coupled proteins embedded on membranes.

JTD Keywords: Bioelectronic nose, Competitive ELISA, G-protein-coupled receptors quantification, Natural vesicles, Olfactory receptors, Transmembrane proteins

A method for online decorrelation of chemical sensor signals from the effects of environmental humidity and temperature variations is proposed. The goal is to improve the accuracy of electronic nose measurements for continuous monitoring by processing data from simultaneous readings of environmental humidity and temperature. The electronic nose setup built for this study included eight metal-oxide sensors, temperature and humidity sensors with a wireless communication link to external computer. This wireless electronic nose was used to monitor the air for two years in the residence of one of the authors and it collected data continuously during 537 days with a sampling rate of 1 sample per second. To estimate the effects of variations in air humidity and temperature on the chemical sensors' signals, we used a standard energy band model for an n-type metal-oxide (MOX) gas sensor. The main assumption of the model is that variations in sensor conductivity can be expressed as a nonlinear function of changes in the semiconductor energy bands in the presence of external humidity and temperature variations. Fitting this model to the collected data, we confirmed that the most statistically significant factors are humidity changes and correlated changes of temperature and humidity. This simple model achieves excellent accuracy with a coefficient of determination R2 close to 1. To show how the humidity–temperature correction model works for gas discrimination, we constructed a model for online discrimination among banana, wine and baseline response. This shows that pattern recognition algorithms improve performance and reliability by including the filtered signal of the chemical sensors.

JTD Keywords: Electronic nose, Chemical sensors, Humidity, Temperature, Decorrelation, Wireless e-nose, MOX sensors, Energy band model, Home monitoring

Metal oxide (MOX) gas sensors arrays are a predominant technological choice to perform fundamental tasks of chemical detection. Yet, their use has been mainly limited to relatively controlled instrument configurations where the sensor array is placed within a closed measurement chamber. Usually, the experimental protocol is defined beforehand and it includes three stages: the array is first exposed to a gas reference, then to the gas sample, and finally to the reference again to recover the initial state. Such sampling procedure requires signal acquisition during the complete experimental protocol and usually delays the output prediction until the predefined measurement duration is complete. Due to the slow time response of chemical sensors, the completion of the measurement typically requires minutes. In this paper we propose the use of reservoir computing (RC) algorithms to overcome the slow temporal dynamics of chemical sensor arrays, allowing identification and quantification of chemicals of interest continuously and reducing measurement delays. We generated two datasets to test the ability of RC algorithms to provide accurate and continuous prediction to fast varying gas concentrations in real time. Both datasets - one generated with synthetic data and the other acquired from actual gas sensors - provide time series of MOX sensors exposed to binary gas mixtures where concentration levels change randomly over time. Our results show that our approach improves the time response of the sensory system and provides accurate predictions in real time, making the system specifically suitable for online monitoring applications. Finally, the collected dataset and developed code are made publicly available to the research community for further studies.

JTD Keywords: Chemical sensors, Continuous gas prediction, Electronic nose, Real-time detection, Reservoir computing

Abstract Here we describe the fabrication of a highly sensitive and label-free ITO-based impedimetric immunosensor for the detection of pathogenic bacteria Escherichia coli O157:H7. Anti-E. coli antibodies were immobilized onto ITO electrodes using a simple, robust and direct methodology. First, the covalent attachment of epoxysilane on the ITO surface was demonstrated by Atomic Force Microscopy and cyclic voltammetry. The immobilization of antibody on the epoxysilane layer was quantified by Optical Waveguide Lightmode Spectroscopy, obtaining a mass variation of 12 ng cm− 2 (0.08 pmol cm− 2). Microcontact printing and fluorescence microscopy were used to demonstrate the specific binding of E. coli O157:H7 to the antibody-patterned surface. We achieved a ratio of 1:500 Salmonella typhimurium/E. coli O157:H7, thus confirming the selectivity of the antibodies and efficiency of the functionalization procedure. Finally, the detection capacity of the ITO-based immunosensor was evaluated by Electrochemical Impedance Spectroscopy. A very low limit of detection was obtained (1 CFU mL− 1) over a large linear working range (10–106 CFU mL− 1). The specificity of the impedimetric immunosensor was also examined. Less than 20% of non-specific bacteria (S. typhimurium and E. coli K12) was observed. Our results reveal the applicability of ITO for the development of highly sensitive and selective impedimetric immunosensors.

JTD Keywords: E. coli O157:H7, Electrochemical Impedance Spectroscopy, Immunosensor, Indium tin oxide, Label-free detection

Abstract Inherent variability of chemical sensors makes necessary individual calibration of chemical detection systems. This shortcoming has traditionally limited usability of systems based on Metal Oxide (MOX) sensor arrays and prevented mass-production for some applications. Here, aiming at exploring transfer calibration between electronic nose systems, we exposed five identical 8-sensor detection units to controlled gas conditions. Our results show that a calibration model provides more accurate predictions when the tested board is included in the calibration dataset. However, we show that previously built calibration models can be extended to other units using a reduced number of measurements. While baseline correction seems imperative for successful baseline correction, among the different tested strategies, piecewise direct standardization provides more accurate predictions.

JTD Keywords: Electronic nose, Calibration, MOX sensor, Machine Olfaction

Over the last two decades, electronic nose research has produced thousands of research works. Many of them were describing the ability of the e-nose technology to solve diverse applications in domains ranging from food technology to safety, security, or health. It is, in fact, in the biomedical field where e-nose technology is finding a research niche in the last years. Although few success stories exist, most described applications never found the road to industrial or clinical exploitation. Most described methodologies were not reliable and were plagued by numerous problems that prevented practical application beyond the lab. This work emphasizes the need of external validation in machine olfaction. I describe some statistical and methodological pitfalls of the e-nose practice and I give some best practice recommendations for researchers in the field.

JTD Keywords: Chemical sensor arrays, Pattern recognition, Chemometrics, Electronic noses, Robustness, Signal and data processing

Electronic nose is an instrument which is composed of gas sensor array and pattern recognition unit. It is generally used for classifying, identifying or quantifying the odors or volatile organic components for these commonly used devices, calibration transfer is an important issue because of differences in each instrument, sensor drift, changes in environmental conditions or background changes. Calibration transfer is a transfer of model between different instruments which have different conditions. In this study, calibration transfer is applied to the e-noses which have different temperature conditions. Also the results of the direct standardization, piecewise direct standardization and orthogonal signal correction which are different calibration methods were compared. The results of the piecewise direct standardization method are more successful than the other methods for the dataset which is used in this study.

JTD Keywords: Calibration, Conferences, Electronic noses, Ethanol, Instruments, Signal processing, Standardization

Although Metal Oxide (MOX) sensors are predominant choices to perform fundamental tasks of chemical detection, their use has been mainly limited to relatively controlled scenarios where a gas sensor array is first exposed to a reference, then to the gas sample, and finally to the reference again to recover the initial state. In this paper we propose the use of MOX sensors along with Reservoir Computing algorithms to identify chemicals of interest. Our approach allows continuous gas monitoring in simple experimental setups without the requirement of acquiring recovery transient of the sensors, thereby making the system specifically suitable for online monitoring applications.

JTD Keywords: Chemical sensing, Reservoir computing, Gas sensors, Dynamic gas mixtures, Electronic nose

This manuscript introduces a software tool that allows for the design of synthetic experiments in machine olfaction. The proposed software package includes both, a virtual sensor array that reproduces the diversity and response of a polymer array and tools for data generation. The synthetic array of sensors allows for the generation of chemosensor data with a variety of characteristics: unlimited number of sensors, support of multicomponent gas mixtures and full parametric control of the noise in the system. The artificial sensor array is inspired from a reference database of seventeen polymeric sensors with concentration profiles for three analytes. The main features in the sensor data, like sensitivity, diversity, drift and sensor noise, are captured by a set of models under simplified assumptions. The generator of sensor signals can be used in applications related to test and benchmarking of signal processing methods, neuromorphic simulations in machine olfaction and educational tools. The software is implemented in R language and can be freely accessed.

JTD Keywords: Gas Sensor Array, Conducting Polymers, Electronic Nose, Sensor Simulation, Synthetic Dataset, Benchmark, Educational Tool

The sensitivity and selectivity of metal oxide (MOX) gas sensors change significantly when the sensors operate at different temperatures. While previous investigations have presented systematic approaches to optimize the operating temperature of a single MOX sensor, in this paper we present a methodology to select the optimal operating temperature of all the MOX sensors constituent of a gas sensor array based on the multivariate response of all the sensing elements. Our approach estimates a widely used Information Theory measure, the so-called Mutual Information (MI), which quantifies the amount of information that the state of one random variable (response of the gas sensor array) can provide from the state of another random variable representing the gas quality. More specifically, our methodology builds sensor models from experimental data to solve the technical problem of populating the joint probability distribution for the MI estimation. We demonstrate the relevance of our approach by maximizing the MI and selecting the best operating temperatures of a four-sensor array sampled at 94 different temperatures to optimize the discrimination task of ethanol, acetic acid, 2-butanone, and acetone. In addition to being applicable in principle to sensor arrays of any size, our approach gives precise information on the ability of the system to discriminate odors according to the temperature of the MOX sensors, for either the optimal set of temperatures or the temperatures that may render inefficient operation of the system itself.

JTD Keywords: MOX gas sensor, Temperature optimization, Limit of detection, Mutual Information, E-nose, Sensor array, Information Theory, Chemical sensing

Assembly and disassembly of adhesion structures such as focal adhesions (FAs) and podosomes regulate cell adhesion and differentiation. On antigen-presenting dendritic cells (DCs), acquisition of a migratory and immunostimulatory phenotype depends on podosome dissolution by prostaglandin E2 (PGE2). Whereas the effects of physico-chemical and topographical cues have been extensively studied on FAs, little is known about how podosomes respond to these signals. Here, we show that, unlike for FAs, podosome formation is not controlled by substrate physico-chemical properties. We demonstrate that cell adhesion is the only prerequisite for podosome formation and that substrate availability dictates podosome density. Interestingly, we show that DCs sense 3-dimensional (3-D) geometry by aligning podosomes along the edges of 3-D micropatterned surfaces. Finally, whereas on a 2-dimensional (2-D) surface PGE2 causes a rapid increase in activated RhoA levels leading to fast podosome dissolution, 3-D geometric cues prevent PGE2-mediated RhoA activation resulting in impaired podosome dissolution even after prolonged stimulation. Our findings indicate that 2-D and 3-D geometric cues control the spatial organization of podosomes. More importantly, our studies demonstrate the importance of substrate dimensionality in regulating podosome dissolution and suggest that substrate dimensionality plays an important role in controlling DC activation, a key process in initiating immune responses.

JTD Keywords: Mechanosensitivity, Podosomes, Dendritic cell, Adhesion

Smart biomaterials play a key role when aiming at successful tissue repair by means of regenerative medicine approaches, and are expected to contain chemical as well as mechanical cues that will guide the regenerative process. Recent advances in the understanding of stem cell biology and mechanosensing have shed new light onto the importance of the local microenvironment in determining cell fate. Herein we report the biological properties of a bioactive, biodegradable calcium phosphate glass/polylactic acid composite biomaterial that promotes bone marrow-derived endothelial progenitor cell (EPC) mobilisation, differentiation and angiogenesis through the creation of a controlled bone healing-like microenvironment. The angiogenic response is triggered by biochemical and mechanical cues provided by the composite, which activate two synergistic cell signalling pathways: a biochemical one mediated by the calcium-sensing receptor and a mechanosensitive one regulated by non-muscle myosin II contraction. Together, these signals promote a synergistic response by activating EPCs-mediated VEGF and VEGFR-2 synthesis, which in turn promote progenitor cell homing, differentiation and tubulogenesis. These findings highlight the importance of controlling microenvironmental cues for stem/progenitor cell tissue engineering and offer exciting new therapeutical opportunities for biomaterialbased vascularisation approaches and clinical applications.

JTD Keywords: Calcium phosphate glass composite, Smart biomaterial, Endothelial progenitor cell, Angiogenesis, Mechanosensing, Calcium-sensing receptor

In this work we report the fabrication and characterization of a label-free impedimetric immunosensor based on a silicon nitride (Si 3N 4) surface for the specific detection of human serum albumin (HSA) proteins. Silicon nitride provides several advantages compared with other materials commonly used, such as gold, and in particular in solid-state physics for electronic-based biosensors. However, few Si 3N 4-based biosensors have been developed; the lack of an efficient and direct protocol for the integration of biological elements with silicon-based substrates is still one of its the main drawbacks. Here, we use a direct functionalization method for the direct covalent binding of monoclonal anti-HSA antibodies on an aldehyde-functionalized Si-p/SiO 2/Si 3N 4 structure. This methodology, in contrast with most of the protocols reported in literature, requires less chemical reagents, it is less time-consuming and it does not need any chemical activation. The detection capability of the immunosensor was tested by performing non-faradaic electrochemical impedance spectroscopy (EIS) measurements for the specific detection of HSA proteins. Protein concentrations within the linear range of 10 -13-10 -7M were detected, showing a sensitivity of 0.128ΩμM -1 and a limit of detection of 10 -14M. The specificity of the sensor was also addressed by studying the interferences with a similar protein, bovine serum albumin. The results obtained show that the antibodies were efficiently immobilized and the proteins detected specifically, thus, establishing the basis and the potential applicability of the developed silicon nitride-based immunosensor for the detection of proteins in real and more complex samples.

JTD Keywords: Aldehyde, Electrochemical impedance spectroscopy, Human serum albumin, Immunosensor, Silicon nitride, Bovine serum albumins, Chemical reagents, Complex samples, Covalent binding, Detection capability, Electrochemical impedance, Electrochemical impedance spectroscopy measurements, Functionalizations, Human serum albumins, Impedimetric immunosensors, Label free, Limit of detection, Linear range, Protein concentrations, Silicon-based, Specific detection, Aldehydes

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

Signal and data processing are essential elements in electronic noses as well as in most chemical sensing instruments. The multivariate responses obtained by chemical sensor arrays require signal and data processing to carry out the fundamental tasks of odor identification (classification), concentration estimation (regression), and grouping of similar odors (clustering). In the last decade, important advances have shown that proper processing can improve the robustness of the instruments against diverse perturbations, namely, environmental variables, background changes, drift, etc. This article reviews the advances made in recent years in signal and data processing for machine olfaction and chemical sensing.

JTD Keywords: Chemical sensors, Electronic nose, Intelligent sensors, Measurement techniques, Sensor arrays, Sensor systems

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

In this paper the feasibility of using metal oxide gas sensor technology for evaluating spoilage process for sea bream (Sparus aurata) is explored. It is shown that a single sensor under temperature modulation is able to find a correlation with the fish spoilage process. Results are obtained in real frigorific storage conditions: that is, at low measurement temperatures with variations of relative humidity.

JTD Keywords: Gas sensors, Electronic nose, Spoilage process, Temperature modulation, Bream sparus-aurata, Electronic nose, Freshness, Quality, Sardines, Storage

Drift is an important issue that impairs the reliability of gas sensing systems. Sensor aging, memory effects and environmental disturbances produce shifts in sensor responses that make initial statistical models for gas or odor recognition useless after a relatively short period (typically few weeks). Frequent recalibrations are needed to preserve system accuracy. However, when recalibrations involve numerous samples they become expensive and laborious. An interesting and lower cost alternative is drift counteraction by signal processing techniques. Orthogonal Signal Correction (OSC) is proposed for drift compensation in chemical sensor arrays. The performance of OSC is also compared with Component Correction (CC). A simple classification algorithm has been employed for assessing the performance of the algorithms on a dataset composed by measurements of three analytes using an array of seventeen conductive polymer gas sensors over a ten month period.

JTD Keywords: Gas sensor array, Drift, Orthogonal signal correction, Component correction, Cross-validation, Electronic nose, Data shift

The present work focuses on the development of an immunosensing surface to build a portable olfactory system for the detection of complex mixture of odorants. Homogeneous cell derived vesicles expressing the olfactory receptors were produced and immobilized with efficiency onto a gold substrate through an optimized surface functionalization method.

JTD Keywords: Bioelectronic noses, Biosensors, Nanoproteoliposomes, Nanosomes, Olfactory receptors, SAMs

Silicon nitride surfaces are modified with a triethoxysilane aldehyde self-assembled monolayer for the direct immobilization of monoclonal antibodies and the detection of human serum albumin proteins, without any activation requirements. Surface modification and the specific recognition interaction between the HSA protein and its associated antibody are studied by fluorescence microscopy and atomic force microscopy.

JTD Keywords: Aldehyde, Human serum albumin, Immunosensors, Microcontact printing, Silicon nitride

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JTD Keywords: Self-assembled monolayers, High-aspect-ratio, Dip-pen nanolithography, Langmuir-blodgett-films, Conducting polymer, Enzymes, Microstructures, Immunosensors, Fabrication, Stability