Biology subjects

Mathew, S.

Publications and source records attributed to Mathew, S..

18 recordsLinked to original sources

bioRxiv2026

Dose-Dependent Effects of Low-Intensity Focused Ultrasound on Human Deep White Matter Tracts

Background: Low-intensity focused ultrasound (LIFU) is emerging as a method for anatomically specific, noninvasive, and reversible neuromodulation of deep brain structures relevant to psychopathology. A key requirement for clinical translation is evidence of graded target engagement. We examined whether LIFU applied to deep white matter tracts produces dose-dependent functional connectivity changes in healthy adults. Methods: In this preregistered, double-blind, randomized study, 35 healthy adults underwent LIFU targeting (80 s, 10% duty cycle, estimated ISPPA 2.26 W/cm2, 0.5 MHz, in a {theta}-burst pattern) of individually modeled right thalamo-prefrontal white matter tracts under two dose conditions: one and three consecutive sonications. Dose-dependent changes in resting-state functional connectivity were examined during a 30-minute poststimulation period in 31 participants. Results: One sonication acutely increased right thalamic functional connectivity with the left thalamus (28 voxels; Z = 5.48, Cohen's d = 0.61), whereas three sonications decreased connectivity with the right dorsolateral prefrontal cortex (Z = -4.05, Cohen's d = -0.45). Poststimulation time-course analysis revealed a 3-LIFU-specific linear recovery trend in the left cerebellum (Z = 4.14, d = 0.48), reflecting initial suppression followed by progressive recovery across 30 minutes. Stronger thalamo-prefrontal structural connectivity was associated with condition-specific functional connectivity changes (left frontal pole; F = 14.73, {rho}2 = 0.41). Conclusions: These findings provide initial human evidence that LIFU is well tolerated and produces dose-dependent changes in functional connectivity associated with deep white matter tract stimulation, informing parameter selection for future circuit-based mechanistic and clinical studies.

neuroscience↗

bioRxiv2026

Glyphosate as a driver of antimicrobial resistance evolution in bacteria

Glyphosate, the worlds most widely used herbicide, targets the enzyme 5-enolpyruvylshikimate-3-phosphate synthase (EPSPS), which is conserved across plants and many bacteria. While its environmental effects are increasingly recognized, its role on antimicrobial resistance (AMR) remains incompletely understood. In particular, the link between intrinsic glyphosate sensitivity and AMR gene content or evolutionary dynamics has not been systematically explored. We examined the relationship between bacterial sensitivity to glyphosate, AMR profiles, and the evolution of AMR genes. We analyzed genome datasets from the human gut microbiota and the Alignable Tight Genomic Clusters (ATGC). EPSPS sequences were identified via BLAST and annotations and classified based on the intrinsic sensitivity to glyphosate using the EPSPSClass webserver. AMR genes, including associated drug classes and resistance mechanisms, were annotated using the Comprehensive Antibiotic Resistance Database (CARD). Across datasets, glyphosate-sensitive bacteria carried a greater diversity of AMR genes and mechanisms. In contrast, probabilistic modeling revealed that glyphosate-resistant bacteria accumulate AMR genes at significantly higher rates. Phylogenetic birth-and-death analyses and stochastic mapping further revealed elevated AMR gene gain, loss, expansion, and reduction in resistant strains. These results indicate a decoupling between AMR gene diversity and evolutionary dynamics: sensitive bacteria maintain more resistance genes, whereas resistant bacteria display accelerated AMR gene turnover. This suggests that glyphosate resistance is linked to increased genome dynamics, potentially enhancing bacterias adaptability under combined herbicide and antimicrobial pressures. Given glyphosates extensive agricultural use and potential human exposure, these findings highlight an underappreciated link between herbicide resistance and the evolution of AMR in bacterial populations.

microbiology↗

bioRxiv2025

The neural basis of emotional generalization in empathy

The essence of empathy is generalization of emotion across persons. Here, we leverage recent theoretical advances in the neuroscience of generalization to help us understand empathy. We measured brain activity in human neurosurgical patients performing two tasks, one focused on identifying their own emotional response and one identifying emotional responses in others. We quantified the representational geometry of local field potential (LFP) high-gamma activity in four regions: the medial temporal lobe, anterior cingulate cortex, orbitofrontal cortex, and insula. We found encoding of both self- and other-emotions in all four regions, but codes for emotion and person are disentangled (that is, factorized) in the insula, but not the other regions. This factorized representation allows for cross-person generalization of emotion in a way that tangled (non-factorized) representations do not. Together, these results support the hypothesis that the insula uniquely contributes to social mirroring processes by which we understand emotions across individuals.

neuroscience↗

bioRxiv2025

MCWs (MiCroWire sorter): A new framework for automated and reliable spike sorting in human intracerebral recordings.

Efficient and accurate spike sorting is critical for isolating single neurons from extracellular recordings to distinguish neural activity of interest. However, while the electrodes and acquisition systems for non-human electrophysiology have been enhanced over the past decades to enable higher-yield single-neuron detections, those advances have not been translated into human electrophysiology. Single-wire electrodes are still ubiquitously used, and although acquisition systems have augmented their signal-to-noise ratio over the last 15 years, we are still limited by their low electrode count. Moreover, unlike non-human recordings, human recordings often take place in hospitals where different noise sources and subject breaks can compromise the recording quality during experimental sessions. To bridge this gap, this work presents an automatic, open-source spike sorting pipeline that leverages contemporary computational capabilities and is tailored to single-neuron recordings from humans acquired via microwires. The pipeline is implemented in both MATLAB and Python, ensuring accessibility and compatibility across computational environments. Its modular and comprehensive structure supports customization and even opportunities for new developments as per the requirements of the user and the application. One feature is a data-driven automatic module to remove narrow-band interference, besides electrical line noise, which can be an essential tool while recording in clinical settings, particularly for online processing implementations. Following spike detection, the pipeline implements an artifact rejection module that separates waveforms that are unlikely to be associated with actual spikes. Additionally, we introduce a configurable feature-extraction, clustering, and benchmarking framework that not only allows flexibility in employing user-defined or conventional algorithms, such as wavelet transform with superparamagnetic clustering, but can also evaluate multi-method agreement among the different sorters. The pipeline also utilizes established and novel quality metrics to support semiautomatic curation of isolated clusters. Furthermore, we can integrate the customized pipeline with experimental tasks by removing task-unrelated waveforms (e.g., during a break in a task) and prevent over-clustering with the aid of metrics for comparing response profiles. Thus, the presented pipeline addresses the three-pronged objectives of algorithm-adaptability, rigorous validation, and human single-neuron recording optimization to support clinical and cognitive neuroscience applications.

neuroscience↗

bioRxiv2025

An online dynamic experimental framework to study single neuron responses in humans

Single-neuron activity can be recorded from patients being evaluated for neurosurgical treatment of drug-resistant epilepsy who volunteer to have microwires implanted for single cell research that aims to study various aspects of the human brain. These recordings provide an unprecedented window into the human brain to observe how information is encoded and retrieved at the cellular level. Current single cell research paradigms require laborious offline analysis to identify stimuli eliciting neuronal responses and introduce new relevant stimuli in a follow up task. Any delays due to patient availability can compromise the follow up task, risking loss of experimental progress as recording electrodes may move away from previously recorded neurons. This paper introduces a novel experimental framework for online single cell data analysis and dynamic sampling of the stimulus space. It allows for real-time data acquisition and analysis to identify response-eliciting stimuli, introduce new relevant stimuli, and discard those that fail to elicit responses.

neuroscience↗

bioRxiv2025

Biomimetic biaxial mechanical properties enhance hemodynamic performance and prevent adverse tissue remodelling in tissue-engineered heart valves

Heart valve tissue engineering holds the promise of providing an unlimited supply of heart valve replacements for patients with valvular heart disease. While tissue-engineered heart valves show promising performance in the short term, regurgitation due to fibrotic leaflet shortening remains a persistent limitation in most cases. Here we tested the hypothesis that engineering heart valves with native biaxial mechanical properties would mitigate adverse tissue remodeling in vitro. Melt electrowriting and hydrogel casting were used to generate four types of tissue-engineered heart valves with combinatorial biomimetic or non-biomimetic mechanical properties in the radial and circumferential direction of the heart valves. The heart valves were subject to pulmonary hemodynamic conditions in a pulse duplicator bioreactor, and their tissue remodelling, including cell phenotype and orientation and extracellular matrix properties, was investigated. The results showed that tissue-engineered heart valves with native mechanical properties, particularly in the radial direction, outperformed those with non-physiological mechanics in hemodynamic function, maintaining quiescent cell phenotype and cell orientation, and avoiding fibrosis. This study, for the first time, elucidates the impact of native mechanical properties on the performance of tissue- engineered heart valves and their cell and extracellular matrix homeostasis.

bioengineering↗

bioRxiv2024

The intersection of inflammation and DNA damage as a novel axis underlying the pathogenesis of autism spectrum disorders

Autism spectrum disorders (ASD) affects 1 in 36 children and is characterized by repetitive behaviors and difficulties in social interactions and social communication. The etiology of ASD is extremely heterogeneous, with a large number of ASD cases that are of unknown or complex etiology, which suggests the potential contribution of epigenetic risk factors. In particular, epidemiological and animal model studies suggest that inflammation during pregnancy could lead to an increased risk of ASD in the offspring. However, the molecular mechanisms that contribute to ASD pathogenesis in relation to maternal inflammation during pregnancy in humans are underexplored. Several pro-inflammatory cytokines have been associated with increased autistic-like behaviors in animal models of maternal immune activation, including IL-17A. Using a combination of ASD patient lymphocytes and stem cell-derived human neurons exposed to IL-17A we discovered a shared molecular signature that highlights a metabolic and translational node that could lead to altered neuronal excitability. Further, our work on human neurons brings forward the possibility that defects in the DNA damage response could be underlying the effect of IL-17A on human excitatory neurons, linking exacerbated unrepaired DNA damage to the pathogenicity of maternal inflammation in connection to ASD.

neuroscience↗

bioRxiv2024

ENACT: End-to-End Analysis of Visium High Definition (HD) Data

MotivationSpatial transcriptomics (ST) enables the study of gene expression within its spatial context in histopathology samples. To date, a limiting factor has been the resolution of sequencing based ST products. The introduction of the Visium High Definition (HD) technology opens the door to cell resolution ST studies. However, challenges remain in the ability to accurately map transcripts to cells and in assigning cell types based on the transcript data. ResultsWe developed ENACT, the first tissue-agnostic pipeline that integrates advanced cell segmentation with Visium HD transcriptomics data to infer cell types across whole tissue sections. Our pipeline incorporates novel bin-to-cell assignment methods, enhancing the accuracy of single-cell transcript estimates. Validated on diverse synthetic and real datasets, our approach is both scalable and effective offering a robust solution for spatially resolved transcriptomics analysis. Availability and implementationENACT source code is available at https://github.com/Sanofi-Public/enact-pipeline. Experimental data is available at https://zenodo.org/records/13887921. Supplementary information: Supplementary data are available at BiorXiv online.

bioinformatics↗

bioRxiv2024

Injury Severity is a Key Contributor to Coagulation Dysregulation and Fibrinogen Consumption

BackgroundTraumatic injury is a leading cause of death for those under the age of 45, with 40% occurring due to hemorrhage. Severe tissue injury and hypoperfusion lead to marked changes in coagulation, thereby preventing formation of a stable blood clot and increasing hemorrhage associated mortality. ObjectivesWe aimed to quantify changes in clot formation and mechanics occurring after traumatic injury and the relationship to coagulation kinetics, and fibrinolysis. MethodsPlasma was isolated from injured patients upon arrival to the emergency department. Coagulation kinetics and mechanics of healthy donors and patient plasma were compared with rheological, turbidimetric and thrombin generation assays. ELISAs were performed to determine tissue plasminogen activator (tPA) and D-dimer concentration, as fibrinolytic markers. ResultsSixty-three patients were included in the study. The median injury severity score (ISS) was 17, median age was 37.5 years old, and mortality rate was 30%. Rheological, turbidimetric and thrombin generation assays indicated that trauma patients on average, and especially deceased patients, exhibited reduced clot stiffness, increased fibrinolysis and reduced thrombin generation compared to healthy donors. Fibrinogen concentration, clot stiffness, D-dimer and tPA all demonstrated significant direct correlation to increasing ISS. Machine learning algorithms identified and highlighted the importance of clinical factors on determining patient outcomes. ConclusionsViscoelastic and biochemical assays indicate significant contributors and predictors of mortality for improved patient treatment and therapeutic target detection. ESSENTIALSO_LITraumatic injury may lead to alterations in a patients ability to form stable blood clots C_LIO_LIA study was performed to assess how trauma severity affects coagulation kinetics C_LIO_LIKey alterations were observed in trauma patients, who exhibit weaker and slower forming clots C_LIO_LIPaired with machine learning methods, the results indicate key aspects contributing to mortality C_LI

bioengineering↗

bioRxiv2023

Adaptations to water stress and pastoralism in the Turkana of northwest Kenya

The Turkana people inhabit arid regions of east Africa--where temperatures are high and water is scarce--and they practice subsistence pastoralism, such that their diet is primarily composed of animal products. Working with Turkana communities, we sequenced 367 genomes and identified 8 regions putatively involved in adaptation to water stress and pastoralism. One of these regions includes a putative enhancer for STC1--a kidney-expressed gene involved in the response to dehydration and the metabolism of purine-rich foods such as red meat. We show that STC1 is induced by antidiuretic hormone in humans, is associated with urea levels in the Turkana themselves, and is under strong selection in this population (s[~]0.041). This work highlights that partnerships with subsistence-level groups can lead to new models of human physiology with biomedical relevance.

evolutionary biology↗

bioRxiv2022

SPTLC1 variants associated with childhood onset amyotrophic lateral sclerosis produce distinct sphingolipid signatures through impaired interaction with ORMDL proteins

Amyotrophic lateral sclerosis (ALS) is a progressive neurodegenerative disease affecting motor neurons. Mutations in the SPTLC1 subunit of serine-palmitoyltransferase (SPT), which catalyzes the first step in the de novo synthesis of sphingolipids cause childhood-onset ALS. SPTLC1-ALS variants map to a transmembrane domain that interacts with ORMDL proteins, negative regulators of SPT activity. We show that ORMDL binding to the holoenzyme complex is impaired in cells expressing pathogenic SPTLC1-ALS alleles, resulting in increased sphingolipid synthesis and a distinct lipid signature. C-terminal SPTLC1 variants cause the peripheral sensory neuropathy HSAN1 due to the synthesis of 1-deoxysphingolipids (1-deoxySLs) that form when SPT metabolizes L-alanine instead of L-serine. Limiting L-serine availability in SPTLC1-ALS expressing cells increased 1-deoxySL and shifted the SL profile from an ALS to an HSAN1-like signature. This effect was corroborated in an SPTLC1-ALS pedigree in which the index patient uniquely presented with an HSAN1 phenotype, increased 1-deoxySL levels, and an L-serine deficiency. These data demonstrate how pathogenic variants in different domains of SPTLC1 give rise to distinct clinical presentations that are nonetheless modifiable by substrate availability.

biochemistry↗

bioRxiv2022

Symbolic quantitative cognition in wild zebrafish (Danio rerio)

Zebrafish (Danio rerio) constitute an excellent model system to investigate the neural and genetic basis of quantitative cognition We tested the ability of reward quantity discrimination of wild-type zebrafish in an associative learning task. We used an operant conditioning paradigm in which the number of horizontal lines zebrafish approached in a 2-alternative forced choice task predicted the number of food reward pellets they would receive. Zebrafish did not learn a preference for the 2-line stimulus predictive of receiving 2 food pellets. However, a subset of the fish performed significantly above chance in a discrimination task with the same apparatus, in which the 2-line stimulus was associated with the same reward but the choice of the 1-line stimulus was not rewarded. Zebrafish also showed a population level learning in a simpler spatial association task with the same apparatus. We also explored the explanatory value of alternative spatial learning hypotheses such as a Win-Stay, Lose-Shift (WSLS) strategy at the individual level for fish in navigating these spatially randomised tasks.

animal behavior and cognition↗

bioRxiv2021

Genomic analysis reveals geography rather than culture as the predominant factor shaping genetic variation in northern Kenyan human populations

ObjectivesThe aim of this study was to characterize the genetic relationships within and among four neighboring populations in northern Kenya in light of cultural relationships to understand the extent to which geography and culture shape patterns of genetic variation. Materials and MethodsWe collected DNA and demographic information pertaining to aspects of social identity and heritage from 572 individuals across the Turkana, Samburu, Waso Borana, and Rendille of northern Kenya. We sampled individuals across a total of nine clans from these four groups and, additionally, three territorial sections within the Turkana and successfully genotyped 376 individuals. ResultsHere we report that geography predominately shapes genetic variation within and among human groups in northern Kenya. We observed a clinal pattern of genetic variation that mirrors the overall geographic distribution of the individuals we sampled. We also found relatively higher rates of intermarriage between the Rendille and Samburu and evidence of gene flow between them that reflect these higher rates of intermarriage. Among the Turkana, we observed strong recent genetic substructuring based on territorial section affiliation. Within ethnolinguistic groups, we found that Y chromosome haplotypes do not consistently cluster by natal clan affiliation. Finally, we found that sampled populations that are geographically closer have lower genetic differentiation, and that cultural similarity does not predict genetic similarity as a whole across these northern Kenyan populations. DiscussionOverall, the results from this study highlight the importance of geography, even on a local geographic scale, in shaping observed patterns of genetic variation in human populations.

genetics↗

bioRxiv2020

Initial insights into the genetic epidemiology of SARS-CoV-2 isolates from Kerala suggest local spread from limited introductions

Coronavirus disease 2019 (COVID-19) rapidly spread from a city in China to almost every country in the world, affecting millions of individuals. Genomic approaches have been extensively used to understand the evolution and epidemiology of SARS-CoV-2 across the world. Kerala is a unique state in India well connected with the rest of the world through a large number of expatriates, trade, and tourism. The first case of COVID-19 in India was reported in Kerala in January 2020, during the initial days of the pandemic. The rapid increase in the COVID-19 cases in the state of Kerala has necessitated the understanding of the genetic epidemiology of circulating virus, evolution, and mutations in SARS-CoV-2. We sequenced a total of 200 samples from patients at a tertiary hospital in Kerala using COVIDSeq protocol at a mean coverage of 7,755X. The analysis identified 166 unique high-quality variants encompassing 4 novel variants and 89 new variants identified for the first time in SARS-CoV-2 samples isolated from India. Phylogenetic and haplotype analysis revealed that the circulating population of the virus was dominated (94.6% of genomes) by three distinct introductions followed by local spread, apart from identifying polytomies suggesting recent outbreaks. The genomes formed a monophyletic distribution exclusively mapping to the A2a clade. Further analysis of the functional variants revealed two variants in the S gene of the virus reportedly associated with increased infectivity and 5 variants that mapped to five primer/probe binding sites that could potentially compromise the efficacy of RT-PCR detection. To the best of our knowledge, this is the first and most comprehensive report of genetic epidemiology and evolution of SARS-CoV-2 isolates from Kerala.

genomics↗

bioRxiv2020

Analysis of the potential impact of genomic variants in SARS-CoV-2 genomes from India on molecular diagnostic assays

An isolated epidemic of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) causing Coronavirus Diseases (COVID-19) originating in Wuhan, China has now rapidly emerged into a global pandemic affecting millions of people worldwide. Molecular detection of SARS-CoV-2 using reverse transcription polymerase chain reaction (RT-PCR) forms the mainstay in screening, diagnosis and epidemiology of disease. The virus has been evolving through base substitutions. The recent availability of genomes of SARS-CoV-2 isolates from different countries including India motivated us to assess the presence and potential impact of variations in target sites for the oligonucleotide primers and probes used in molecular diagnosis. We catalogued a total of 132 primers or probes sequences from the literature and the public domain. Our analysis revealed a total of 125 unique genetic variants in 80 either primers or probes binding sites. A total of 13 unique variants had allele frequency of [≥] 1% in Indian SARS-CoV-2 genomes mapped to the primers or probes binding sites. A total of 15 primers or probes binding sites had cumulative variant frequency of [≥] 1% in the SARS-CoV-2 genomes. These included primers or probes sites which are widely used in India and across the world for molecular diagnosis as well as approved by national and international agencies. This highlights the need for sequencing genomes of emerging pathogens to make evidence based policies for development and approval of diagnostics. To the best of our knowledge, ours is the most comprehensive analysis of genomic variants in genomes of SARS-CoV-2 isolates from India and their potential impact on efficacy of molecular diagnostics.

genomics↗

bioRxiv2019

Histone deacetylase 9 promoter hypomethylation associated with adipocyte dysfunction is a statin-related metabolic effect

BackgroundAdipogenesis, the process whereby preadipocytes differentiate into mature adipocytes, is crucial for maintaining metabolic homeostasis. Cholesterol lowering statins increase type 2 diabetes (T2D) risk possibly by affecting adipogenesis and insulin resistance but the (epi)genetic mechanisms involved are unknown. Here, we characterised the effects of statin treatment on adipocyte differentiation using in vitro human preadipocytes cell model to identify putative effective genes. ResultsStatin treatment during adipocyte differentiation caused a reduction in key genes involved in adipogenesis, such as ADIPOQ, GLUT4 and ABCG1. Using Illuminas Infinium 850K Methylation EPIC array, we found a significant hypomethylation of cg14566882, located in the promoter of the histone deacetylase 9 (HDAC9) gene, in response to two types of statins (atorvastatin and mevastatin), which correlates with an increased HDAC9 mRNA expression. HDAC9 is a transcriptional repressor of the cholesterol efflux ABCG1 gene expression, which is epigenetically modified in obesity and prediabetic states. Thus, we assessed the putative impact of ABCG1 knockdown in mimicking the effect of statin in adipogenesis. ABCG1 KD reduced the expression of key genes involved in adipocyte differentiation and decreased insulin signalling and glucose uptake. In human blood cells from two cohorts, ABCG1 expression was impaired in response to statins, confirming that ABCG1 is in vivo targeted by these drugs. ConclusionsWe identified an epigenetic link between adipogenesis and adipose tissue insulin resistance in the context of T2D risk associated with statin use, which has important implications as HDAC9 and ABCG1 are considered potential therapeutic targets for obesity and metabolic diseases.

cell biology↗

bioRxiv2019

Deletion of beta-fructofuranosidase (invertase) genes is associated with sucrose content in Date Palm fruit

The fruit of date palm trees are an important part of the diet for a large portion of the Middle East and North Africa. The fruit is consumed both fresh and dry and can be stored dry for extended periods of time. Date fruits vary significantly across hundreds of cultivars identified in the main regions of cultivation. Most dried date fruit are low in sucrose but high in glucose and fructose. However, high sucrose content is a distinctive feature of some date fruit and affects flavor as well as texture and water retention. To identify the genes controlling high sucrose content we analyzed date fruit metabolomics for association with genotype data from 121 date fruits. We found significant association of dried date sucrose content and a genomic region that contains 3 tandem copies of the beta-fructofuranosidase (invertase) gene in the reference Khalas genome, a low sucrose fruit. High sucrose cultivars including the popular Deglet Noor had a homozygous deletion of two of the 3 copies of the invertase gene. We show the deletion allele is derived when compared to the ancestral allele that retains the all copies of the gene in 3 other species of Phoenix. The fact that 2 of the 3 tandem invertase copies are associated with dry fruit sucrose content will assist in better understanding the distinct roles of multiple date palm invertases in plant physiology. Identification of the recessive alleles associated with end-point sucrose content in date fruit may be used in selective breeding in the future.

plant biology↗

bioRxiv2018

Myosin Heavy Chain-embryonic is a crucial regulator of skeletal muscle development and differentiation.

Myosin heavy chains (MyHCs) are contractile proteins that are part of the thick filaments of the functional unit of the skeletal muscle, the sarcomere. In addition to MyHCs that are part of the adult muscle contractile network, two MyHCs - MyHC-embryonic and -perinatal are expressed during muscle development and are only transiently expressed in the adult during regeneration. The functions performed by these MyHCs has been a long-standing question and using a targeted mouse allele, we have characterized the role of MyHC-embryonic. Analysis of loss-of-function mice reveals that lack of MyHC-embryonic leads to mis-regulation of other MyHCs, alterations in fiber size, fiber number and fiber type at neonatal stages. We also find that loss of MyHC-embryonic leads to mis-regulation of genes involved in muscle differentiation. A broad theme from these studies is that loss of MyHC-embryonic has distinct effects on different muscles, possibly reflecting the unique fiber type composition of different muscles. Most significantly, our results indicate that MyHC-embryonic is required during embryonic and fetal myogenesis to regulate myogenic progenitor and myoblast differentiation in a non-cell autonomous manner via Mitogen Activated Protein Kinase (MAPKinase) and Fibroblast Growth Factor (FGF) signaling. Thus, our results signify that MyHC-embryonic is a key regulator of myogenic differentiation during embryonic, fetal and neonatal myogenesis.

developmental biology↗