A single-cell RNA sequencing dataset of peripheral blood cells in long COVID patients on herbal therapy.

Following the coronavirus disease 2019 (COVID-19) pandemic, the rise of long COVID, characterized by persistent respiratory and cognitive dysfunctions, has become a significant health concern. This leads to an increased role of complementary and alternative medicine in addressing this condition. However, our comprehension of the effectiveness and safety of herbal medicines for long COVID remains limited.

Uterine organoids reveal insights into epithelial specification and plasticity in development and disease.

Understanding how epithelial cells in the female reproductive tract (FRT) differentiate is crucial for reproductive health, yet the underlying mechanisms remain poorly defined. At birth, FRT epithelium is highly malleable, allowing differentiation into various epithelial types, but the regulatory pathways guiding these early cell fate decisions are unclear. Here, we use neonatal mouse endometrial organoids and assembloid coculture models to investigate how innate cellular plasticity and external mesenchymal signals influence epithelial differentiation.

Fully automated segmentation and classification of renal tumors on CT scans via machine learning.

Background: To develop and test the performance of a fully automated system for classifying renal tumor subtypes via deep machine learning for automated segmentation and classification.

Materials And Methods: The model was developed using computed tomography (CT) images of pathologically proven renal tumors collected from a prospective cohort at a medical center between March 2016 and December 2020. A total of 561 renal tumors were included: 233 clear cell renal cell carcinomas (RCCs), 82 papillary RCCs, 74 chromophobe RCCs, and 172 angiomyolipomas.