Perturbation of endoplasmic reticulum (ER) homeostasis impairs insulin biosynthesis, beta cell survival, and glucose homeostasis. We show that a murine model of diabetes is associated with the development of ER stress in beta cells and that treatment with the GLP-1R agonist exendin-4 significantly reduced biochemical markers of islet ER stress in vivo. Exendin-4 attenuated translational downregulation of insulin and improved cell survival in purified rat beta cells and in INS-1 cells following induction of ER stress in vitro. GLP-1R agonists significantly potentiated the induction of ATF-4 by ER stress and accelerated recovery from ER stress-mediated translational repression in INS-1 beta cells in a PKA-dependent manner. The effects of exendin-4 on the induction of ATF-4 were mediated via enhancement of ER stress-stimulated ATF-4 translation. Moreover, exendin-4 reduced ER stress-associated beta cell death in a PKA-dependent manner. These findings demonstrate that GLP-1R signaling directly modulates the ER stress response leading to promotion of beta cell adaptation and survival.
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http://dx.doi.org/10.1016/j.cmet.2006.10.001 | DOI Listing |
Environ Toxicol
January 2025
Department of Medical Research, Chung Shan Medical University Hospital, Taichung, Taiwan.
The epithelial-mesenchymal transition (EMT) assists in the acquisition of invasiveness, relapse, and resistance in non-small cell lung cancer (NSCLC) and can be caused by the signaling of transforming growth factor-β1 (TGF-β1) through Smad-mediated or Smad-independent pathways. (-)-Epigallocatechin-3-gallate (EGCG), a multifunctional cancer-preventing bioconstituent found in tea polyphenols, has been shown to repress TGF-β1-triggered EMT in the human NSCLC A549 cell line by inhibiting the activation of Smad2 and Erk1/2 or reducing the acetylation of Smad2 and Smad3. However, its impact on the Smad-independent pathway remains unclear.
View Article and Find Full Text PDFIUBMB Life
January 2025
Department of Reproductive Medical Center, First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan Province, China.
Abnormality of granulosa cells (GCs) is the critical cause of follicular atresia in premature ovarian failure (POF). RIPK3 is highly expressed in GCs derived from atretic follicles. We focus on uncovering how RIPK3 contributes to ovarian GC senescence.
View Article and Find Full Text PDFStem Cell Res Ther
January 2025
Applied Oral Sciences and Community Dental Care, Faculty of Dentistry, Prince Philip Dental Hospital, The University of Hong Kong, 34 Hospital Road, Sai Ying Pun, Hong Kong, Hong Kong SAR.
Background: Achieving a stable vasculature is crucial for tissue regeneration. Endothelial cells initiate vascular morphogenesis, followed by mural cells that stabilize new vessels. This study investigated the in vivo effects of Sema4D-Plexin-B1 signaling on stem cells from human exfoliated deciduous teeth (SHED)-supported angiogenesis, focusing on its mechanism in PDGF-BB secretion.
View Article and Find Full Text PDFGeroscience
January 2025
Department for Basic and Preclinical Sciences, Faculty of Biological and Veterinary Sciences, Nicolaus Copernicus University in Torun, 87-100, Torun, Poland.
Inflammaging, a state of chronic low-grade inflammation associated with aging, has been linked to the development and progression of various disorders. Cellular senescence, a state of irreversible growth arrest, is another characteristic of aging that contributes to the pathogenesis of cardiovascular pathology. Senescent cells accumulate in tissues over time and secrete many inflammatory mediators, further exacerbating the inflammatory environment.
View Article and Find Full Text PDFNat Commun
January 2025
Department of Biostatistics, University of Michigan, Ann Arbor, MI, USA.
An essential task in spatial transcriptomics is identifying spatially variable genes (SVGs). Here, we present Celina, a statistical method for systematically detecting cell type-specific SVGs (ct-SVGs)-a subset of SVGs exhibiting distinct spatial expression patterns within specific cell types. Celina utilizes a spatially varying coefficient model to accurately capture each gene's spatial expression pattern in relation to the distribution of cell types across tissue locations, ensuring effective type I error control and high power.
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