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Endothelial cells (EC) play a pivotal role in vascular homeostasis. By sensing shear stress generated by blood flow, EC endorse vasculoprotection through mechanotransduction signaling pathways. Various ion channels are involved in mechanosignaling, and here, we investigated the endothelial voltage-gated Na channels (Na channels), since their mechanosensitivity has been previously demonstrated in cardiomyocytes. First, we showed that EC from aorta (TeloHAEC) behave as EC from umbilical vein (HUVEC) under laminar shear stress (LSS). For both EC models, cell alignment and elongation occurred with the activation of the KLF2/KLF4 atheroprotective signaling pathways. We found that LSS decreased the expression of SCN5A, encoding Na1.5, while LSS increased that of SCN3B, encoding Naβ3. We demonstrated that the KLF4 transcription factor is involved in SCN3B expression under both static and LSS conditions. Interestingly, SCN3B silencing impaired EC alignment induced by LSS. The characterization of Naβ3 interactome by coimmunoprecipitation and proteomic analysis revealed that mTOR, implicated in autophagy, binds to Naβ3. This result was evidenced by the colocalization between Naβ3 and mTOR inside cells. Moreover, we showed that SCN3B silencing led to the decrease in LC3B expression and the number of LC3B positive autophagosomes. Furthermore, we showed that Naβ3 is retained within the cell and colocalized with LAMP1 and LC3B. Finally, we found that resveratrol, a stimulating-autophagy and vasculoprotective molecule, induced KLF4 together with Naβ3 expression. Altogether, our findings highlight a novel role of Naβ3 in endothelial function and cell alignment as an actor in shear stress vasculoprotective intracellular pathway through autophagy modulation.
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http://dx.doi.org/10.1096/fj.202401558RR | DOI Listing |
PLoS One
September 2025
Horticultural Sciences Department, University of Florida, Gainesville, Florida, United States of America.
The study of plant biology has traditionally focused on investigations conducted at the tissue, organ, or whole plant level. However, single-cell transcriptomics has recently emerged as an important tool for plant biology, enabling researchers to uncover the expression profiles of individual cell types within a tissue. The application of this tool has revealed new insights into cell-to-cell gene expression heterogeneity and has opened new avenues for research in plant biology.
View Article and Find Full Text PDFPLoS One
September 2025
Department of Orthopedic Surgery, Center for Shoulder and Elbow Surgery, Konkuk University School of Medicine, Seoul, Korea.
Purpose: We aimed to compare the effects of atelocollagen (AC) and individual growth factors on the expression of key molecular markers associated with tendon healing.
Methods: C2C12 myoblasts were cultured in Dulbecco's Modified Eagle Medium (DMEM) containing 5% fetal bovine serum (FBS) and treated with 1 nM or 10 nM of Atelocollagen (AC), bone morphogenetic protein-2 (BMP-2), transforming growth factor-beta 1 (TGF-β1), insulin-like growth factor-1 (IGF-1), or vascular endothelial growth factor (VEGF) for 5 days. After 5 days of treatment, cells were harvested from the culture medium, and Western blot analysis was performed to quantify the expression of phosphorylated extracellular signal-regulated kinase (p-ERK), Collagen type I (Col I), Collagen type Ⅲ (Col Ⅲ), and Tenascin C (TnC).
Mol Omics
September 2025
Laboratory of Structural Bioinformatics and Computational Biology, Federal University of Rio Grande do Sul, Av. Bento Gonçalves, 9500, Porto Alegre 91501-970, RS, Brazil.
The integration of multimodal single-cell omics data is a state-of-art strategy for deciphering cellular heterogeneity and gene regulatory mechanisms. Recent advances in single-cell technologies have enabled the comprehensive characterization of cellular states and their interactions. However, integrating these high-dimensional and heterogeneous datasets poses significant computational challenges, including batch effects, sparsity, and modality alignment.
View Article and Find Full Text PDFIEEE Trans Comput Biol Bioinform
September 2025
The rapid advancement of single-cell sequencing technology has generated vast amounts of multi-omics data, presenting unprecedented opportunities for single-cell multi-omics clustering analysis. However, existing single-cell clustering algorithms focus on extracting shared representations, overlooking the interactions and correlations among cells. This oversight inevitably leads to biased or confounded cell clustering results.
View Article and Find Full Text PDFIEEE J Biomed Health Inform
September 2025
The tumor microenvironment is a dynamic eco system where cellular interactions drive cancer progression. However, inferring cell-cell communication from non-spatial scRNA-seq data remains challenging due to incomplete li gand-receptor databases and noisy cell type annotations. H ere, we propose scGraphDap, a graph neural network frame work that integrates functional state pseudo-labels and graph structure learning to improve both cell type annotation an d CCC inference.
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