A 72-year-old man developed aggressive skin cancer on his left thumb 30 years after a burn injury, illustrating the decades-long latency of Marjolin ulcer. This rare but deadly cancer behaves far more aggressively than common skin cancers, underscoring the critical need for lifelong monitoring of old scars and immediate biopsy of any suspicious changes.

Researchers have demonstrated the world’s first simultaneous generation of 3,070 optical vortices at megawatt-class peak power (58 MW). By reformulating Hermite–Gaussian to Laguerre–Gaussian mode conversion and implementing it through a compact multibeam interference architecture, the team achieved more than three orders of magnitude improvement in both vortex number and peak power. The work establishes a scalable framework for high-intensity structured-light generation.

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.

Natural biomass hydrogels are emerging as promising building blocks for intelligent sensors because they combine softness, water-rich structures, tunable networks, and abundant functional groups. A new review brings together recent progress in turning materials such as cellulose, chitosan, sodium alginate, gelatin, starch, hemicellulose, proteins, and lignin into responsive sensing platforms. By focusing on the correlation between crosslinking networks and sensor behavior, the review connects material design with practical performance, including sensitivity, response speed, durability, and environmental stability. The work offers a clearer roadmap for developing sustainable sensors for wearable electronics, healthcare monitoring, environmental sensing, and smart human–machine interfaces.

A comprehensive review published in Skin outlines the emergence of “Dermatology AI 2.0”, a fundamental transition from pattern recognition to cognitive and actionable intelligence. Built on four core pillars—causal inference, skin digital twins, predictive intervention, and distributed autonomous networks—this new paradigm enables AI to diagnose rare diseases 30% more accurately, predict disease flares with >90% accuracy, and deliver full-lifecycle skin health management. The review emphasizes that AI will not replace clinicians but will automate routine tasks, allowing physicians to focus on complex cases and patient care.

This study establishes a comprehensive three-level data standardization framework for integrating Western medicine (WM) and traditional Chinese medicine (TCM) electronic medical records in psoriasis research. It resolves the “data-rich, information-poor” paradox in dermatology and enables real-world evidence generation and AI-assisted clinical decision support for integrated therapies.

This review proposes a new generation of biodegradable, tissue-based carriers made from chitin nanofibrils and nanolignin. These carriers improve the stability, skin penetration, and controlled release of key anti-aging ingredients while eliminating the need for single-use plastics, addressing both clinical performance and environmental sustainability in the cosmetics industry.

New 2026 Chinese guidelines introduce a groundbreaking multidimensional severity assessment for alopecia areata (AA) that moves beyond simple scalp involvement. Covering 3.49 million Chinese patients, the guidelines integrate psychosocial impact and extra-scalp features to guide personalized care, establishing JAK inhibitors as first-line systemic therapy for severe cases and addressing long-unmet clinical needs.

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.