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Forty first-trimester human hearts were studied to lay groundwork for further studies of the mechanisms underlying congenital heart defects. We first sampled 49,227 cardiac nuclei from three fetuses at 8.6, 9.0, and 10.7 post-conceptional weeks (pcw) for single-nucleus RNA sequencing, enabling the distinction of six classes comprising 21 cell types. Improved resolution led to the identification of previously unappreciated cardiomyocyte populations and minority autonomic and lymphatic endothelial transcriptomes, among others. After integration with 5-7 pcw heart single-cell RNA-sequencing data, we identified a human cardiomyofibroblast progenitor preceding the diversification of cardiomyocyte and stromal lineages. Spatial transcriptomic analysis (six Visium sections from two additional hearts) was aided by deconvolution, and key spatial markers validated on sectioned and whole hearts in two- and three-dimensional space and over time. Altogether, anatomical-positional features, including innervation, conduction and subdomains of the atrioventricular septum, translate latent molecular identity into specialized cardiac functions. This atlas adds unprecedented spatial and temporal resolution to the characterization of human-specific aspects of early heart formation.
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http://dx.doi.org/10.1242/dev.204555 | DOI Listing |
Neurotrauma Rep
August 2025
Department of Rehabilitation and Human Performance, Icahn School of Medicine at Mount Sinai, New York, New York, USA.
Recent investments in large-scale mortem tissue collection have accelerated opportunities to understand the neuropathology of traumatic brain injury (TBI) and post-traumatic neurodegeneration (PTND). Clinicopathological correlation requires ante-mortem clinical information. Post-mortem family interviews (PFIs) are an established method to capture comprehensive ante-mortem clinical information.
View Article and Find Full Text PDFFront Bioeng Biotechnol
August 2025
The Third Department of Orthopedic Surgery, Fuxin Mining General Hospital of Liaoning Health Industry Group, Liaoning, China.
Tendon/ligament (T/L) injuries sustained during motion are highly prevalent and severely impact athletes' careers and quality of life. Current treatments, including autografts, allografts, and synthetic ligaments, have limitations such as donor site morbidity, immune rejection, and biomechanical mismatch, especially under dynamic loading conditions encountered in motion. 3D bioprinting offers a revolutionary approach for constructing patient-specific T/L grafts.
View Article and Find Full Text PDFbioRxiv
August 2025
Department of Neuroscience, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA.
Probe-based hybridization spatial transcriptomics has emerged as a state-of-the-art for neuroscience research. Accurate segmentation of neurons and non-neuronal cells, a critical step for downstream analysis, remains a big challenge. Using human sensory ganglia neurons as an example, we systematically explore this problem.
View Article and Find Full Text PDFBiology (Basel)
July 2025
Department of Integrated Traditional Chinese and Western Medicine, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China.
The zebrafish () has emerged as a powerful model organism for investigating the mechanisms of post-traumatic stress disorder (PTSD), offering unique advantages in translational relevance, genetic trackability, and cost-effectiveness. As a logical continuation of our recent systematic review, this manuscript critically examines the spectrum of experimental strategies used to model PTSD in zebrafish, with a focus on the comparative efficacy and validity of acute, chronic, and complex stress paradigms. Among these, 14-15-day chronic unpredictable stress (CUS/UCS) protocols are identified as the gold standard, reliably inducing core PTSD-like phenotypes-such as anxiety-like behavior, cortisol dysregulation, and neuroinflammatory gene activation.
View Article and Find Full Text PDFFront Oncol
August 2025
Department of Medical Oncology, The First People's Hospital of Xiaoshan District, Hangzhou, China.
Gastric cancer (GC) remains a major global health challenge, particularly in its advanced stages where prognosis is poor, and treatment responses are heterogeneous. Precision oncology aims to tailor therapies, but current biomarkers have limitations. Artificial Intelligence (AI), encompassing machine learning (ML) and deep learning (DL), offers powerful tools to analyze complex, multi-dimensional data from advanced GC patients, including clinical records, genomics, imaging (radiomics), and digital pathology (pathomics).
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