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Frontiers | The Musculoskeletal Involvement After Mild to Moderate COVID-19 Infection

COVID-19, a disease caused by the novel coronavirus SARS-CoV-2, has been drastically affecting the daily lives of millions of people. COVID-19 is described as a multiorgan disease that affects not only the respiratory tract of infected individuals, but it has considerable effects on the musculoskeletal system, causing excessive fatigue, myalgia, arthralgia, muscle weakness and skeletal muscle damage. These symptoms can persist for months, decreasing the quality of life of numerous individuals. Curiously, most studies in the scientific literature focus on patients who were hospitalized due to SARS-CoV-2 infection and little is known about the mechanism of action of COVID-19 on skeletal muscles, especially of individuals who had the mild to moderate forms of the disease (non-hospitalized patients). In this review, we focus on the current knowledge about the musculoskeletal system in COVID-19, highlighting the lack of researches investigating the mild to moderate cases of infection and po ....

Pan American Health Organization , District Of Columbia , United States , United Kingdom , City Of , National Institutes Of Health , The Bench , Faroe Islands , Treasure Island , Bangladesh General , Daei Sorkhabi , J Neuroimmune Pharmacol , Le Turnier , Carcamo Garcia , Campos Florian , Salazar Linares , Afamefuna Victor , Gourna Paleoudis , El Sahly , Van Herck , Al Jody , Van Laethem , Acta Myol , Garcia Choza , Alberti Minutti , Abu Hanoud ,

Frontiers | Predicting Spike Features of Hodgkin-Huxley-Type Neurons With Simple Artificial Neural Network

Hodgkin-Huxley (HH) -type model is the most famous computational model for simulating neural activity. It shows the highest accuracy in capturing neuronal spikes, and its model parameters have definite physiological meanings. However, HH-type models are computationally expensive. To address this problem, a previous study proposed a spike prediction module (SPM) to predict whether a spike will take place 1 ms later based on three voltage values with intervals of 1ms. Although SPM does well, it fails to evaluate the informative features of the spike. In this study, the feature prediction module (FPM) based on simple ANN was proposed to predict spike features including maximum voltage, minimum voltage, and dropping interval. Nine different HH-type models were adopted whose firing patterns cover most of the firing behaviors observed in the brain. Voltage and spike feature samples under constant external input current were collected for training and testing. Experiment results illustrated t ....

United Kingdom , City Of , Noadaptation Fohlmeister , Noadaptaton Wang , Cerebellumorphic Yang , Cambridge University , Cambridge University Press , National Natural Science Foundation Of China , National Key Research , Neuronal Networks Of The Hippocampus , Development Program Of China , Atypical Features , Adaptation Ermentrout , Adaptation Gouwens , Spike Features , Voltage Samples , Firing Patterns , National Natural Science Foundation , Development Program , Open Project Program , State Key Laboratory , Mathematical Engineering , Advanced Computing , Supplementary Material , Med Abstract , Crossref Full Text ,

10 лучших рассказов Рэя Брэдбери: очень субъективный топ | Книги

10 лучших рассказов Рэя Брэдбери: очень субъективный топ | Книги
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