by Keyword: Nervous system

Palma-Florez, S, Lagunas, A, Mir, M, (2024). Neurovascular unit on a chip: the relevance and maturity as an advanced in vitro model Neural Regeneration Research 19, 1165-1166

Levy, N, Kiskinis, E, Ortega, JA, Alvarez, Z, (2023). Effect of Age-specific Decellularized Extracellular Matrix on Neuronal Physiology and Repair (PP‐455) Tissue Engineering Part a 29, PP-455

Karkali, K, Tiwari, P, Singh, A, Tlili, S, Jorba, I, Navajas, D, Munoz, JJ, Saunders, TE, Martin-Blanco, E, (2022). Condensation of the Drosophila nerve cord is oscillatory and depends on coordinated mechanical interactions Developmental Cell 57, 867-+

During development, organs reach precise shapes and sizes. Organ morphology is not always obtained through growth; a classic counterexample is the condensation of the nervous system during Drosophila embryogenesis. The mechanics underlying such condensation remain poorly understood. Here, we characterize the condensation of the embryonic ventral nerve cord (VNC) at both subcellular and tissue scales. This analysis reveals that condensation is not a unidirectional continuous process but instead occurs through oscillatory contractions. The VNC mechanical properties spatially and temporally vary, and forces along its longitudinal axis are spatially heterogeneous. We demonstrate that the process of VNC condensation is dependent on the coordinated mechanical activities of neurons and glia. These outcomes are consistent with a viscoelastic model of condensation, which incorporates time delays and effective frictional interactions. In summary, we have defined the progressive mechanics driving VNC condensation, providing insights into how a highly viscous tissue can autonomously change shape and size.

JTD Keywords: actomyosin, central nervous system, drosophila, glia, mechanics, morphogenesis, neuron, ventral nerve cord, Collagen-iv, Contraction, Forces, Gene, Glial-cells, Migration, Morphogenesis, Quantification, System, Tissue, Viscolelastic model

Vouloutsi, Vasiliki, Mura, Anna, Tauber, F., Speck, T., Prescott, T. J., Verschure, P., (2020). Biomimetic and Biohybrid Systems 9th International Conference, Living Machines 2020, Freiburg, Germany, July 28–30, 2020, Proceedings , Springer, Cham (Lausanne, Switzerland) 12413, 1-428

This book constitutes the proceedings of the )th International Conference on Biomimetic and Biohybrid Systems, Living Machines 2020, held in Freiburg, Germany, in July 2020. Due to COVID-19 pandemic the conference was held virtually. The 32 full and 7 short papers presented in this volume were carefully reviewed and selected from 45 submissions. They deal with research on novel life-like technologies inspired by the scientific investigation of biological systems, biomimetics, and research that seeks to interface biological and artificial systems to create biohybrid systems.

JTD Keywords: Artificial intelligence, Soft robotics, Biomimetics, Insect navigation, Synthetic nervous system, Computer vision, Bio-inspired materials, Visual homing, Locomotion+, Image processing, Intelligent robots, Human-robot interaction, Machine learning, Snake robot, Mobile robots, Robotic systems, Drosophila, Robots, Sensors, Signal processing

Calvo, M., Le Rolle, V., Romero, D., Béhar, N., Gomis, P., Mabo, P., Hernández, A. I., (2019). Recursive model identification for the analysis of the autonomic response to exercise testing in Brugada syndrome Artificial Intelligence in Medicine 97, 98-104

This paper proposes the integration and analysis of a closed-loop model of the baroreflex and cardiovascular systems, focused on a time-varying estimation of the autonomic modulation of heart rate in Brugada syndrome (BS), during exercise and subsequent recovery. Patient-specific models of 44 BS patients at different levels of risk (symptomatic and asymptomatic) were identified through a recursive evolutionary algorithm. After parameter identification, a close match between experimental and simulated signals (mean error = 0.81%) was observed. The model-based estimation of vagal and sympathetic contributions were consistent with physiological knowledge, enabling to observe the expected autonomic changes induced by exercise testing. In particular, symptomatic patients presented a significantly higher parasympathetic activity during exercise, and an autonomic imbalance was observed in these patients at peak effort and during post-exercise recovery. A higher vagal modulation during exercise, as well as an increasing parasympathetic activity at peak effort and a decreasing vagal contribution during post-exercise recovery could be related with symptoms and, thus, with a worse prognosis in BS. This work proposes the first evaluation of the sympathetic and parasympathetic responses to exercise testing in patients suffering from BS, through the recursive identification of computational models; highlighting important trends of clinical relevance that provide new insights into the underlying autonomic mechanisms regulating the cardiovascular system in BS. The joint analysis of the extracted autonomic parameters and classic electrophysiological markers could improve BS risk stratification.

JTD Keywords: Autonomic nervous system, Brugada syndrome, Computational model, Recursive identification

Gil, V., Del Río, J. A., (2019). Generation of 3-d collagen-based hydrogels to analyze axonal growth and behavior during nervous system development Journal of Visualized Experiments , (148), e59481

This protocol uses natural type I collagen to generate three-dimensional (3-D) hydrogel for monitoring and analyzing the axonal growth. The protocol is centered on culturing small pieces of embryonic or early postnatal rodent brains inside a 3-D hydrogel formed by the rat tail tendon-derived type I collagen with specific porosity. Tissue pieces are cultured inside the hydrogel and confronted to specific brain fragments or genetically-modified cell aggregates to produce and secrete molecules suitable for creating a gradient inside the porous matrix. The steps of this protocol are simple and reproducible but include critical steps to be considered carefully during its development. Moreover, the behavior of growing axons can be monitored and analyzed directly using a phase-contrast microscope or mono/multiphoton fluorescence microscope after fixation by immunocytochemical methods.

JTD Keywords: 3-D hydrogel cultures, Axonal growth, Cell transfection, Chemoattraction, Chemorepulsion, Embryonic nervous system, Issue 148, Neuroscience, Tissue explants

Jané, R., Lazaro, J., Ruiz, P., Gil, E., Navajas, D., Farre, R., Laguna, P., (2013). Obstructive Sleep Apnea in a rat model: Effects of anesthesia on autonomic evaluation from heart rate variability measures CinC 2013 Computing in Cardiology Conference (CinC) , IEEE (Zaragoza, Spain) , 1011-1014

Rat model of Obstructive Sleep Apnea (OSA) is a realistic approach for studying physiological mechanisms involved in sleep. Rats are usually anesthetized and autonomic nervous system (ANS) could be blocked. This study aimed to assess the effect of anesthesia on ANS activity during OSA episodes. Seven male Sprague-Dawley rats were anesthetized intraperitoneally with urethane (1g/kg). The experiments were conducted applying airway obstructions, simulating 15s-apnea episodes for 15 minutes. Five signals were acquired: respiratory pressure and flow, SaO2, ECG and photoplethysmography (PPG). In total, 210 apnea episodes were studied. Normalized power spectrum of Pulse Rate Variability (PRV) was analyzed in the Low Frequency (LF) and High Frequency (HF) bands, for each episode in consecutive 15s intervals (before, during and after the apnea). All episodes showed changes in respiratory flow and SaO2 signal. Conversely, decreases in the amplitude fluctuations of PPG (DAP) were not observed. Normalized LF presented extremely low values during breathing (median=7,67%), suggesting inhibition of sympathetic system due to anesthetic effect. Subtle increases of LF were observed during apnea. HRV and PPG analysis during apnea could be an indirect tool to assess the effect and deep of anesthesia.

JTD Keywords: electrocardiography, fluctuations, medical disorders, medical signal detection, medical signal processing, neurophysiology, photoplethysmography, pneumodynamics, sleep, ECG, SaO2 flow, SaO2 signal, airway obstructions, amplitude fluctuations, anesthesia effects, anesthetized nervous system, autonomic evaluation, autonomic nervous system, breathing, heart rate variability, high-frequency bands, low-frequency bands, male Sprague-Dawley rats, normalized power spectrum, obstructive sleep apnea, photoplethysmography, physiological mechanisms, pulse rate variability, rat model, respiratory flow, respiratory pressure, signal acquisition, sympathetic system inhibition, time 15 min, time 15 s, Abstracts, Atmospheric modeling, Computational modeling, Electrocardiography, Rats, Resonant frequency

Gutierrez, A., Marco, S., (2009). Biologically inspired signal processing for chemical sensing Studies in Computational Intelligence GOSPEL Workshop on Bio-inspired Signal Processing (ed. Gutierrez, A., Marco, S.), Springer (Barcelona, Spain) -----, (188), -----

This 167-page book is volume 188 in the series 'Studies in computational intelligence.' This volume contain 9 extensive chapters written in English. This volume presents a collection of research advances in biologically inspired signal processing for chemical sensing. The olfactory system, and the gustatory system to a minor extent, has been taken in the last decades as a source of inspiration to develop artificial sensing systems. The recognition of odors by the olfactory system entails a number of signal processing functions such as preprocessing, dimensionality reduction, contrast enhancement, and classification. Using mathematical models to mimic the architecture of the olfactory system, these processing functions can be applied to chemical sensor signals. This book provides background on the olfactory system including a review on information processing in the insect olfactory system along with a proposed signal processing architecture based on the mammalian cortex. It also provides some bio-inspired approaches to process chemical sensor signals such as an olfactory mucosa to improve odor separation and a model of olfactory receptor neuron convergence to correlated sensor responses to an odor and his organoleptic properties. This book will useful to those working or studying in the areas of sensory reception and computational biology.

JTD Keywords: Nervous System (Neural Coordination), Computer Applications (Computational Biology), Sense Organs (Sensory Reception)