A gapless, telomere-to-telomere reference genome of Capsella bursa-pastoris reveals extensive subgenome divergence and large structural variations, providing a pivotal resource for polyploid plant evolution and functional genomic research.

Protecting old-growth forests significantly boosts soil physical–biochemical quality, dissolved organic matter chemodiversity, and beneficial mycorrhizal fungi, offering a proven pathway to safeguard endangered Ocotea porosa and mitigate climate change.

Researchers have developed an innovative method that uses light and artificial intelligence (AI) to measure and control the fabrication of ultra-thin optical fibers in real time. By interpreting light interference patterns—akin to reading the growth rings of a tree—the system reconstructs the fiber's entire shape with nanometer precision. This breakthrough enables intelligent, precise manufacturing crucial for next-generation photonic devices in communications, computing, and sensing.

Ependymoma is a central nervous system tumor that occurs primarily in children and can arise in the supratentorial region, posterior fossa, or spinal cord. Although molecular classification has substantially improved disease stratification and prognostic assessment, the metabolic phenotypes associated with the major pediatric subtypes have remained poorly defined. Because pediatric ependymoma is rare, assembling a cohort that spans multiple molecularly defined subtypes for systematic metabolic comparison is itself challenging.

How does the innate immune system distinguish pathogens from self-components while avoiding excessive immune response and inflammation? Toll-like receptors (TLRs) have provided the answer to this central question over four decades of research. This review synthesizes the multilayered and interactive regulatory mechanisms—from post-translational modifications to phase separation—that ensure balanced TLR signaling, and explores the translational promise of targeting these pathways in infectious diseases, autoimmune diseases, cancer, and inflammatory aging.

A multicenter study found that the advanced lung cancer inflammation index (ALI) predicts outcomes in acute ischemic stroke patients receiving thrombolysis. Lower ALI levels were strongly linked to poorer functional recovery, with a non-linear J-shaped relationship and a threshold effect. Derived from routine clinical measures, ALI offers a simple, accessible biomarker for early risk stratification.