This study investigates how 6:2 chlorinated polyfluorinated ether sulfonic acid (6:2 Cl-PFESA)—a widely used alternative to perfluorooctane sulfonate (PFOS)—exacerbates antibiotic resistance gene (ARG) proliferation during anaerobic digestion. The research demonstrates that PFESA exposure significantly increases both intracellular and extracellular ARGs, particularly tetracycline and sulfonamide resistance genes, through multiple mechanisms including enhanced mobile genetic element proliferation, extracellular polymeric substance restructuring that immobilizes DNA, oxidative stress-induced membrane damage, and selective enrichment of resistant microbial taxa. These findings reveal that emerging PFAS alternatives pose overlooked ecological and health risks by amplifying antimicrobial resistance spread in wastewater treatment systems, highlighting the need to incorporate resistance indicators into environmental risk assessment frameworks for persistent contaminants.

The article reframes dams as basin governance platforms through three interconnected pathways: engineering safety as the baseline, addressing sedimentation and structural risks; system operations as the core, shifting from single-purpose management to multiobjective coordination across safety, ecology, and public benefits; and digital-intelligent governance as the frontier, institutionalizing transparent and anticipatory decision-making. Drawing on China's experience with approximately 95,000 reservoirs, the authors demonstrate how this platform model can enhance resilience, ecological integrity, and public accountability. The framework offers transferable principles for global hydraulic infrastructure governance, contingent upon enabling institutional, financial, and data conditions.

A novel EMS-induced barley male-sterile mutant (N13401) was identified and characterized, and it shows defective pollen starch accumulation. The male sterility gene msg_N13401 was fine-mapped to a 576.9 kb region on chromosome 2H using a wild-cultivated barley cross to overcome the low polymorphism of cultivated barley.

Researchers developed an exosome-loaded microneedle patch that significantly accelerates oral ulcer healing. By enabling localized and sustained delivery, the patch reduces inflammation and promotes tissue regeneration. Multi-omics analysis reveals that the treatment works by modulating macrophage–epithelial interactions through the TSP-1/CD47/NF-κB signaling pathway.

Researchers found that a small change in 3D-printing settings can help produce better-fitting permanent dental crowns. Crowns printed at moderate angles performed best overall. Thinner layers improved accuracy and fit, while thicker layers produced more consistent results across repeated prints.

A new review maps out how polymer-based electrodes could help solve persistent safety, stability, and sustainability problems in solid-state metal-ion batteries. Unlike conventional designs that rely on flammable liquid electrolytes and rigid inorganic materials, polymer electrodes offer mechanical flexibility, chemical tunability, and superior interfacial contact. The analysis synthesizes recent advances in conducting and redox-active polymers, highlighting their potential to enable all-organic solid-state batteries that are lightweight, intrinsically safe, and compatible with low-energy manufacturing. The authors also identify key design strategies—including molecular engineering, composite formation, and interface modification—that could accelerate the transition from laboratory prototypes toward practical, scalable energy storage devices.

Promoters are key DNA regions that control gene transcription, but their activity varies greatly across different cell types. This heterogeneity makes it difficult for existing computational methods to identify promoters reliably. A team led by Professors Zhangyu Mei and Hao Wu from Shandong University, China, has developed MuSE‑Promoter, a deep ensemble learning framework that combines multi‑scale feature fusion, transformer attention, and a learnable weighted ensemble of neural network and random forest. The system outperforms state‑of‑the‑art methods on human cell lines from different tissues and on Arabidopsis thaliana datasets, and shows excellent generalization in cross‑cell‑line and promoter–enhancer discrimination tasks.