A new review shows that AI, teledermatology, and mobile follow-up tools can help family doctors in China manage chronic skin diseases and related mental health and metabolic issues—shifting care from one-off visits to continuous, whole-life support.

Lineage tracing is a powerful tool to study development, tissue homeostasis, aging, and disease progression. Over the past decades, lineage tracing techniques have progressed substantially by employing new genetic engineering tools. However, due to their invasive nature, these approaches are difficult to apply to humans. Although endogenous DNA mutations can be used for in vivo lineage tracing in humans, their extremely low mutation rate presents substantial technical challenges. Mitochondrial DNA mutations are an alternative, but their inheritance may suffer from neutral drift or undergo both positive and negative selection, and their analysis is plagued by excessive data noise. Thus, developing non-invasive, high-resolution lineage tracing methods for human tissues is crucial.

Over the past decades, lineage tracing has been fundamental to unraveling how diverse cell types arise during development and how tumors evolve through clonal expansion. Traditional approaches largely depend on exogenous DNA barcodes, fluorescent proteins, or CRISPR-based recorders engineered into model organisms. However, these synthetic strategies require genetic manipulation, making them difficult to apply to native human clinical samples. Thus, developing versatile, non-invasive methods that can reconstruct the genealogical history of individual cells directly from patient tissues is crucial. The ideal approach should leverage endogenous, heritable markers that accumulate naturally within cells.

A research team at St. Jude Children's Research Hospital, has introduced a downstream analytical framework for STAMP (Single-cell Transcriptomics Analysis and Multimodal Profiling), an emerging technology that preserves cell morphology alongside gene and protein expression. In a perspective published in EXO – Beyond the Cell, the team demonstrates how STAMP data can be analyzed using standard Python-based single-cell tools to link molecular profiles directly with image-derived phenotypes—such as cell area, shape, and marker localization.

A new study uses 3D tumor spheroid models to screen 365 human cytokines, finding TGFB1 inhibits pancreatic ductal adenocarcinoma (PDAC) growth specifically in 3D cultures. Researchers also identify PADI2 as a critical survival factor induced by TGFB1 in 3D, offering potential therapeutic targets for this lethal cancer.

Environmental DNA (eDNA) metabarcoding is transforming biodiversity monitoring by allowing scientists to identify fish species from diverse aquatic ecosystems. To assess reliability of the method, researchers from South Korea analyzed 59 mock community datasets from 30 independent studies, comparing the performance of universal fish primers and reference databases. They found that eDNA metabarcoding is highly effective for detecting fish diversity, but quantitative estimates of fish biomass remain challenging due to methodological biases and database limitations.

A groundbreaking multidisciplinary study reveals that the abundant mangrove fern Acrostichum aureum in Hainan Island harbors moderate genetic diversity but faces hidden vulnerability, providing critical evidence for targeted mangrove ecosystem conservation strategies.