Publications

[No abstract available]

JTD Keywords: Breathing, Cost, Developed country, Developing countries, Developing country, Health care facility, Home monitoring, Human, Humans, Internet, Internet of things, Letter, Lowest income group, Lung function, Lung mechanics, Lung resistance, Mathematical model, Middle income country, Mobile applications, Non invasive procedure, Open source technology, Oscillometry, Pneumotachygraphy, Telemedicine

Sprouting angiogenesis is a core biological process critical to vascular development. Its accurate simulation, relevant to multiple facets of human health, is of broad, interdisciplinary appeal. This study presents an in-silico model replicating a microfluidic assay where endothelial cells sprout into a biomimetic extracellular matrix, specifically, a large-pore, low-concentration fibrin-based porous hydrogel, influenced by chemotactic factors. We introduce a novel approach by incorporating the extracellular matrix and chemotactic factor effects into a unified term using a single parameter, primarily focusing on modelling sprouting dynamics and morphology. This continuous model naturally describes chemotactic-induced sprouting with no need for additional rules. In addition, we extended our base model to account for matrix sensing and degradation, crucial aspects of angiogenesis. We validate our model via a hybrid in-silico experimental method, comparing the model predictions with experimental results derived from the microfluidic setup. Our results underscore the intricate relationship between the extracellular matrix structure and angiogenic sprouting, proposing a promising method for predicting the influence of the extracellular matrix on angiogenesis.Copyright © 2023 Ferre-Torres, Noguera-Monteagudo, Lopez-Canosa, Romero-Arias, Barrio, Castaño and Hernandez-Machado.

JTD Keywords: angiogenesis, biomimmetic, chemotaxis, endothelial cells, filopodia, growth, in silico model, mathematical models, mechanisms, metalloproteinase, migration, morphogenesis, phase field, pore-size, simulation, Angiogenesis, Biomimmetic, Chemotaxis, Endothelial cells, Extracellular matrix, In silico model, Mathematical models, Phase field, Tip cells

During collective migration of epithelial cells, the migration direction is aligned over a tissue-scale expanse. Although the collective cell migration is known to be directed by mechanical forces transmitted via cell-cell junctions, it remains elusive how the intercellular force transmission is coordinated with intracellular biochemical signaling to achieve collective movements. Here, we show that intercellular coupling of extracellular signal-regulated kinase (ERK)-mediated mechanochemical feedback yields long-distance transmission of guidance cues. Mechanical stretch activates ERK through epidermal growth factor receptor (EGFR) activation, and ERK activation triggers cell contraction. The contraction of the activated cell pulls neighboring cells, evoking another round of ERK activation and contraction in the neighbors. Furthermore, anisotropic contraction based on front-rear polarization guarantees unidirectional propagation of ERK activation, and in turn, the ERK activation waves direct multicellular alignment of the polarity, leading to long-range ordered migration. Our findings reveal that mechanical forces mediate intercellular signaling underlying sustained transmission of guidance cues for collective cell migration.

JTD Keywords: Collective cell migration, EGFR, ERK/MAPK, FRET, Front-rear polarity, Intercellular signal transfer, Mathematical model, Mechanochemical feedback, Mechanotransduction, wave propagation

Obstructive Sleep Apnea severity is commonly determined after a sleep polysomnographic study by the Apnea-Hypopnea Index (AHI). This index does not contain information about the duration of events, and weights apneas and hypopneas alike. Significant differences in disease severity have been reported in patients with the same AHI. The aim of this work was to study the effect of obstructive event type and duration on the subsequent oxygen desaturation (SaO2) by mixed-effects models. These models allow continuous and categorical independent variables and can model within-subject variability through random effects. The desaturation depth dSaO2, desaturation duration dtSaO2 and desaturation area dSaO2A were analyzed in the 2022 apneas and hypopneas of eight severe patients. A mixed-effects model was defined to account for the influence of event duration (AD), event type, and their interaction on SaO2 parameters. A two-step backward model reduction process was applied for random and fixed effects optimization. The optimum model obtained for dtSaO2 suggests an almost subject-independent proportion increase with AD, which did not significantly change in apneas as compared to hypopneas. The optimum model for dSaO2 reveals a significantly higher increase as a function of AD in apneas than hypopneas. Dependence of on event type and duration was different in every subject, and a subject-specific model could be obtained. The optimum model for SaO2A combines the effects of the other two. In conclusion, the proposed mixed-effects models for SaO2 parameters allow to study the effect of respiratory event duration and type, and to include repeated events within each subject. This simple model can be easily extended to include the contribution of other important factors such as patient severity, sleep stage, sleeping position, or the presence of arousals.

JTD Keywords: Biological system modeling, Sleep apnea, Mathematical model, Indexes, Reduced order systems, Optimization

Endowing current surgical robotic systems with haptic feedback to perform minimally invasive surgery (MIS), such as laparoscopy, is still a challenge. Haptic is a feature lost in surgical teleoperated systems limiting surgeons capabilities and ability. The availability of haptics would provide important advantages to the surgeon: Improved tissue manipulation, reducing the breaking of sutures and increase the feeling of telepresence, among others. To design and develop a haptic system, the measurement of forces can be implemented based on two approaches: Direct and indirect force sensing. MIS performed with surgical robots, imposes many technical constraints to measure forces, such as: Miniaturization, need of sterilization or materials compatibility, making it necessary to rely on indirect force sensing. Based on mathematical models of the components involved in an intervention and indirect force sensing techniques, a global perspective on how to address the problem of measurement of tool-tissue interaction forces is presented.

JTD Keywords: Surgical robotics, Haptic feedback, Indirect force sensing, Machine learning, Data fusion, Mathematical models