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Structural insights into the recognition of RALF peptides by FERONIA receptor kinase during Brassicaceae pollination.
Plant Mol Biol
January 2025
Department of Biological Sciences and Engineering, Indian Institute of Technology Gandhinagar, Palaj, Gujarat, 382355, India.
Ensuring species integrity and successful reproduction is pivotal for the survival of angiosperms. Members of Brassicaceae family employ a "lock and key" mechanism involving stigmatic (sRALFs) and pollen RALFs (pRALFs) binding to FERONIA, a Catharanthus roseus receptor-like kinase 1-like (CrRLK1L) receptor, to establish a prezygotic hybridization barrier. In the absence of compatible pRALFs, sRALFs bind to FERONIA, inducing a lock state for pollen tube penetration.
View Article and Find Full Text PDFReconstructing dinosaur locomotion.
Biol Lett
January 2025
School of Biological and Environmental Sciences, Liverpool John Moores University, Liverpool, UK.
Dinosaur locomotor biomechanics are of major interest. Locomotion of an animal affects many, if not most, aspects of life reconstruction, including behaviour, performance, ecology and appearance. Yet locomotion is one aspect of non-avian dinosaurs that we cannot directly observe.
View Article and Find Full Text PDFA first-in-human clinical study of an allogenic iPSC-derived corneal endothelial cell substitute transplantation for bullous keratopathy.
Cell Rep Med
December 2024
Department of Ophthalmology, Keio University School of Medicine, Shinjuku-ku 160-8582, Tokyo, Japan; Department of Clinical Regenerative Medicine, Fujita Medical Innovation Center, Fujita Health University, Ota-ku, Tokyo 144-0041, Japan. Electronic address:
A first-in-human investigator-initiated clinical study of a corneal endothelial cell substitute (CLS001) derived from a clinical-grade induced pluripotent stem cell (iPSC) line shows improvement of visual acuity and corneal stromal edema, with no adverse events for up to 1 year after surgery for the treatment of bullous keratopathy. While preclinical tests, including multiple whole-genome analysis and tumorigenicity tests adhering to the Food and Drug Administration (FDA) draft guidelines, are negative, an additional whole-genome analysis conducted on transplanted CLS001 cells reveals a de novo in-frame deletion of exon22 in the EP300 gene. No adverse events related to the mutation are observed.
View Article and Find Full Text PDFExploring the gut-inflammation connection: A Mendelian randomization study on gut microbiota, inflammatory factors, and uterine fibroids risk.
Medicine (Baltimore)
November 2024
Department of Cardiology, Center Hospital of Shandong First Medical University, Jinan, China.
This study employs Mendelian randomization (MR) approach to investigate the potential causal association between genetic variants associated with gut microbiota, inflammatory factors, and the risk of uterine fibroids development. We extracted data on 211 types of gut microbiota, 91 inflammatory factors, and uterine fibroids occurrence from genome-wide association studies and applied the inverse-variance weighted (IVW) method for analysis. To further assess the robustness of our MR analysis, we conducted sensitivity tests including Cochrane's Q test, the MR-Egger intercept test, the MR-PRESSO global test, and a leave-one-out analysis.
View Article and Find Full Text PDFDual-path neural network extracts tumor microenvironment information from whole slide images to predict molecular typing and prognosis of Glioma.
Comput Methods Programs Biomed
January 2025
School of Information Science and Technology, Fudan University, Shanghai, 200433, China; Key Laboratory of Medical Imaging, Computing and Computer Assisted Intervention, Shanghai, 200433, China. Electronic address:
Background And Objective: Utilizing AI to mine tumor microenvironment information in whole slide images (WSIs) for glioma molecular subtype and prognosis prediction is significant for treatment. Existing weakly-supervised learning frameworks based on multi-instance learning have potential in WSIs analysis, but the large number of patches from WSIs challenges the effective extraction of key local patch and neighboring patch microenvironment info. Therefore, this paper aims to develop an automatic neural network that effectively extracts tumor microenvironment information from WSIs to predict molecular typing and prognosis of glioma.
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