Publications

Additive manufacturing enhances the catalyst performance via hierarchical design. To address environmental and resource concerns, this work aims to fabricate directly recycled 3D-printed monoliths using Direct-Ink Writing (DIW) from 100 % recovered cobalt-zirconia powders. Virgin cobalt-zirconia monoliths were firstly fabricated by DIW of 3.0-7.0 wt% Co-enriched hydrogel-based ceramic inks, followed by calcination at 600 degrees C in a single thermal treatment. After testing the catalytic performance of monoliths in ethanol steam reforming, 3Dprinted cobalt-zirconia monoliths were fragmented and subjected to subsequent milling and sieving steps to recover composite cobalt-zirconia powders with the appropriate properties for reuse in DIW. The recovered powders, inks and monoliths were microstructurally, rheologically and catalytically characterized, and then compared to catalysts constituted by virgin materials. The rheology properties of inks for the recycled and virgin monoliths presented an appropriate printability. Furthermore, the catalytic performance of recycled monoliths was close to that exhibited by virgin catalysts. This study demonstrates the feasibility of directly recycling fully 3D-printed catalysts, potentially reducing the environmental impact with a circular production model to enhance sustainability in the catalyst industry.

JTD Keywords: Additive manufacturing, Catalyst ethanol steam reforming, Cobalt catalysts, Direct-ink writing, Efficient, Heterogeneous catalyst, Hydrogen production, Ionically conductive supports, Monoliths, Nanoparticles, Oxidation, Performance, Recycled ceramics, Regeneration, Solid oxide fuel, Zirconia

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 endosomal sorting complex required for transport (ESCRT) is a multi-protein machinery involved in several membrane remodeling processes. Different approaches have been used to resolve how ESCRT proteins scission membranes. However, the underlying mechanisms generating membrane deformations are still a matter of debate. Here, giant unilamellar vesicles, microfluidic technology, and micropipette aspiration are combined to continuously follow the ESCRT-III-mediated membrane remodeling on the single-vesicle level for the first time. With this approach, we identify different mechanisms by which a minimal set of three ESCRT-III proteins from Entamoeba histolytica reshape the membrane. These proteins modulate the membrane stiffness and spontaneous curvature to regulate bud size and generate intraluminal vesicles even in the absence of ATP. We demonstrate that the bud stability depends on the protein concentration and membrane tension. The approaches introduced here should open the road to diverse applications in synthetic biology for establishing artificial cells with several membrane compartments.© 2022 The Author(s).

JTD Keywords: bilayer, curvature, diffusion-coefficients, identification, membrane-scission, phase-diagram, reveals, sorting complex, structural basis, Biophysics, Biotechnology, Cell biology, Giant vesicles, Membranes

Tauopathies are a group of neurodegenerative diseases characterized by the hyperphosphorylation and deposition of tau proteins in the brain. In Alzheimer's disease, and other related tauopathies, the pattern of tau deposition follows a stereotypical progression between anatomically connected brain regions. Increasing evidence suggests that tau behaves in a "prion-like" manner, and that seeding and spreading of pathological tau drive progressive neurodegeneration. Although several advances have been made in recent years, the exact cellular and molecular mechanisms involved remain largely unknown. Since there are no effective therapies for any tauopathy, there is a growing need for reliable experimental models that would provide us with better knowledge and understanding of their etiology and identify novel molecular targets. In this review, we will summarize the development of cellular models for modeling tau pathology. We will discuss their different applications and contributions to our current understanding of the "prion-like" nature of pathological tau.

JTD Keywords: neurodegeneration, seeding, spreading, Culture model, Efficient generation, Extracellular tau, Familial alzheimers-disease, Microtubule-associated protein, Mouse model, Neurodegeneration, Neurofibrillary tangles, Paired helical filaments, Pathogenic tau, Pluripotent stem-cells, Seeding, Spreading, Tauopathies

Great advances in cancer treatment have been undertaken in the last years as a consequence of the development of new antitumoral drugs able to target cancer cells with decreasing side effects and a better understanding of the behavior of neoplastic cells during invasion and metastasis. Specifically, drug delivery systems (DDS) based on the use of hydroxyapatite nanoparticles (HAp NPs) are gaining attention and merit a comprehensive review focused on their potential applications. These are derived from the intrinsic properties of HAp (e.g., biocompatibility and biodegradability), together with the easy functionalization and easy control of porosity, crystallinity and morphology of HAp NPs. The capacity to tailor the properties of DLS based on HAp NPs has well-recognized advantages for the control of both drug loading and release. Furthermore, the functionalization of NPs allows a targeted uptake in tumoral cells while their rapid elimination by the reticuloendothelial system (RES) can be avoided. Advances in HAp NPs involve not only their use as drug nanocarriers but also their employment as nanosystems for magnetic hyperthermia therapy, gene delivery systems, adjuvants for cancer immunotherapy and nanoparticles for cell imaging.

JTD Keywords: antitumoral, cancer, cell imaging, controlled-release, drug-carrier, efficient drug-delivery, fatty-acid-metabolism, fe3o4 nanoparticles, gene delivery, hydroxyapatite, hyperthermia, immunotherapy, in-vitro, magnetic hydroxyapatite, nano-hydroxyapatite, protein adsorption, tumor-growth, Calcium-phosphate nanoparticles, Cancer, Immunotherapy

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

Respiration rate can be assessed by analyzing respiratory changes of the electrocardiogram (ECG). Several methods can be applied to derive the respiratory signal from the ECG (EDR signal). In this study, four EDR estimation methods based on QRS features were analyzed. A database with 44 healthy subjects (16 females) in supine and sitting positions was analyzed. Respiratory flow and ECG recordings on leads I, II, III and a Chest lead was studied. A QR slope-based method, an RS slope-based method, an QRS angle-based method and an QRS area-based method were applied. Their performance was evaluated by the correlation coefficient with the reference respiratory volume signal. Significantly higher correlation coefficients in the range r = 0.77 – 0.86 were obtained with the Chest lead for all methods. The EDR estimation method based on the QRS angle provided the highest similarity with the volume signal for all recording leads and subject positions. We found no statistically significant differences according to gender or subject position.Clinical Relevance— This work analyzes the EDR signal from four electrocardiographic leads to obtain the respiratory signal and contributes to a simplified analysis of respiratory activity.

JTD Keywords: Electrocardiography, Lead, Estimation, Correlation coefficient, Databases, Heart, Correlation

Understanding how polyprotic compounds distribute within liposome (LP) suspensions is of major importance to design effective drug delivery strategies. Advances in this research field led to the definition of LP-based active drug encapsulation methods driven by transmembrane pH gradients with evidenced efficacy in the management of cancer and infectious diseases. An accurate modeling of membrane-solution drug partitioning is also fundamental when designing drug delivery systems for poorly endocytic cells, such as red blood cells (RBCs), in which the delivered payloads rely mostly on the passive diffusion of drug molecules across the cell membrane. Several experimental models have been proposed so far to predict the partitioning of polyprotic basic/acid drugs in artificial membranes. Nevertheless, the definition of a model in which the membrane-solution partitioning of each individual drug microspecies is studied relative to each other is still a topic of ongoing research. We present here a novel experimental approach based on mathematical modeling of drug encapsulation efficiency (EE) data in liposomal systems by which microspecies-specific partition coefficients are reported as a function of pH and phospholipid compositions replicating the RBC membrane in a simple and highly translatable manner. This approach has been applied to the study of several diprotic basic antimalarials of major clinical importance (quinine, primaquine, tafenoquine, quinacrine, and chloroquine) describing their respective microspecies distribution in phosphatidylcholine-LP suspensions. Estimated EE data according to the model described here closely fitted experimental values with no significant differences obtained in 75% of all pH/lipid composition-dependent conditions assayed. Additional applications studied include modeling drug EE in LPs in response to transmembrane pH gradients and lipid bilayer asymmetric charge, conditions of potential interest reflected in our previously reported RBC-targeted antimalarial nanotherapeutics.

JTD Keywords: Distribution coefficient, Liposomal systems, Malaria therapy, Nanomedicine, Partition coefficient, PH-controlled drug encapsulation, Polyprotic drug, Targeted drug delivery

The study of the mechanomyographic signal of the diaphragm muscle (MMGdi) is a promising technique in order to evaluate the respiratory muscles effort. The relationship between amplitude and frequency parameters of this signal with the respiratory effort performed during respiration is of great interest for researchers and physicians due to its diagnostic potentials. However, MMGdi signals are frequently contaminated by a cardiac vibration or mechanocardiographic (MCG) signal. An adaptive noise cancellation (ANC) can be used to reduce the MCG interference in the recorded MMGdi activity. In this paper, it is evaluated the proposed ANC scheme by means of a synthetic MMGdi signal with a controlled MCG interference. The Pearson's correlation coefficient (PCC) between both root mean square (RMS) and mean frequency (fm) of the synthetic MMGdi signal are considerably reduced with the presence of cardiac vibration noise (from 0.95 to 0.87, and from 0.97 to 0.76, respectively). With the ANC algorithm proposed the effect of the MCG noise on the amplitude and frequency of MMG parameters is reduced considerably (PCC of 0.93 and 0.97 for the RMS and fm, respectively). The ANC method proposed in this work is an interesting technique to attenuate the cardiac interference in respiratory MMG signals. Further investigation should be carried out to evaluate the performance of the ANC algorithm in real MMGdi signals.

JTD Keywords: Adaptive filters, Frequency modulation, Interference, Muscles, Noise cancellation, Vibrations, Cardiology, Medical signal processing, Muscle, Signal denoising, ANC algorithm, MCG interference, Pearson correlation coefficient, Adaptive noise cancellation, Cardiac vibration interference, Cardiac vibration noise, Diaphragm muscle, Mechanocardiographic signal, Mechanomyographic signals, Respiratory muscles effort

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