Biology subjects

Davoudi, M.

Publications and source records attributed to Davoudi, M..

3 recordsLinked to original sources

bioRxiv2024

Capture of Human Neuromesodermal and Posterior Neural Tube Axial Stem Cells

The spinal cord, nerves, and skeletal muscles arise from neuromesodermal progenitors (NMPs). We have developed a growth-factor screening strategy, utilizing ES and iPS cells, facilitating the indefinite self-renewal of two types of human axial stem cells (AxSCs), closely resembling mouse NMPs (NM-AxSCs) and posterior neural tube progenitors (N-AxSCs). Under specific regimens-- Wnt/CHIR99021, FGF2, and TGF-{beta} inhibitor SB431542 (CFS) and excluding FGF2 (CS), respectively--these AxSCs self-renew and sustain telomeres. Single cell transcriptomics and proteomics have revealed expression of posterior growth-zone and dorsoventral neural tube markers in NM-AxSCs, and correspondingly, differentiation to a wide spectrum of neural tube neurons and myocytes. N-AxSCs rapidly matured into dorsal sensory subsets and neural crest. Crucially, neither AxSC type produces teratomas, and analogous mouse NM-AxSCs integrated successfully into the neural tube and somites. Capturing of AxSCs from patient and GMP ES / iPS cells without transgenesis unveils ontogeny and promises modeling and therapy in neuropathies.

developmental biology↗

bioRxiv2022

Lumbar time-varying muscle synergies in trunk flexion and bending movements at different velocities

PurposeAlthough the extent of which the central nervous system uses muscle synergies as a movement control strategy remains an open area of research, it is widely agreed that synergies facilitate the robustness of the neuromuscular system, allowing for effective postural control and flexible movement. This work aimed to investigate the muscle activation patterns of the trunk and time-varying muscle synergies using a novel 18-muscle 3-DOF, 3-D musculoskeletal model of the lumbar spine developed by the authors. Methods24 different biaxial trunk movements were simulated via the optimization of kinetic and kinematic measures towards obtaining the corresponding muscle activation patterns at 3 different velocities. These patterns were subsequently used to extract the principal (phasic and tonic) spatio-temporal synergies associated with the observed muscle activation patterns in the range of simulated movements. ResultsFour dominant synergies were able to explain a considerable percent (about 75%) of the variance of the simulated muscle activities. The extracted synergies were spatially tuned in the direction of the main simulated movements (flexion/extension and right/left lateral bending). The temporal patterns demonstrated gradual monotonic shifts in tonic synergies and biphasic modulatory components in phasic synergies with spatially tuned time-delays. The increase in velocity resulted in an elevated amplitude coefficient and accelerated activation of phasic synergies. ConclusionOur results suggest the plausibility of a time-varying synergies strategy in the dynamic control of trunk movement. Further work is needed to explore leveraging these concepts in various applications, such as rehabilitation and musculoskeletal biomechanics, towards providing more insight into the mechanisms underlying trunk stability and flexibility.

bioengineering↗

bioRxiv2022

Lumbar time-varying muscle synergies in trunk flexion and bending movements at different velocities

PurposeAlthough the extent of which the central nervous system uses muscle synergies as a movement control strategy remains an open area of research, it is widely agreed that synergies facilitate the robustness of the neuromuscular system, allowing for effective postural control and flexible movement. This work aimed to investigate the muscle activation patterns of the trunk and time-varying muscle synergies using a novel 18-muscle 3-DOF, 3-D musculoskeletal model of the lumbar spine developed by the authors. Methods24 different biaxial trunk movements were simulated via the optimization of kinetic and kinematic measures towards obtaining the corresponding muscle activation patterns at 3 different velocities. These patterns were subsequently used to extract the principal (phasic and tonic) spatiotemporal synergies associated with the observed muscle activation patterns in the range of simulated movements. ResultsFour dominant synergies were able to explain a considerable percent (about 75%) of the variance of the simulated muscle activities. The extracted synergies were spatially tuned in the direction of the main simulated movements (flexion/extension and right/left lateral bending). The temporal patterns demonstrated gradual monotonic shifts in tonic synergies and biphasic modulatory components in phasic synergies with spatially tuned time-delays. The increase in velocity resulted in an elevated amplitude coefficient and accelerated activation of phasic synergies. ConclusionOur results suggest the plausibility of a time-varying synergies strategy in the dynamic control of trunk movement. Further work is needed to explore leveraging these concepts in various applications, such as rehabilitation and musculoskeletal biomechanics, towards providing more insight into the mechanisms underlying trunk stability and flexibility.

bioengineering↗