The mechanism underlying how seasonal allergies recur year after year with precise timing remains largely unknown. An international team led by Professor Rudolf Valenta has identified a specific type of immune cell—the IgE-positive plasmablast (IgE⁺ plasmablast)—as the central player responsible for the seasonal recall of allergy symptoms. This discovery not only provides evidence for understanding the pathogenesis of allergy, but also points the way toward targeted, on-demand therapies.

DiaCardia, a novel artificial intelligence model that can accurately identify individuals with prediabetes using either 12-lead or single-lead electrocardiogram (ECG) data, has been recently developed. This breakthrough holds promise for future home-based prediabetes screening using consumer wearable devices, without requiring invasive blood tests. This study emphasizes the utility of the ECG as a powerful biomarker and highlights that the innovative AI model can contribute to the prevention of diabetes.

The study, published in Circulation Research, reveals that neutrophils—key immune cells—change their behavior in line with circadian rhythms, affecting cerebral perfusion and collateral circulation

A comprehensive review published in Science China Life Sciences by a collaborative team led by Prof. Wenjie Shu (Bioinformatics Center of AMMS) et al. highlights that Protein Foundation Models (pFMs) have emerged as game-changers in life science.

These AI tools, trained on large-scale datasets, can predict protein characteristics and design new proteins with desired functions. This review explores the progress, uses, challenges, and future of pFMs. It looks at the diverse data—from genetic sequences to 3D structures and functional information—that these models learn from. It covers key AI methods and highlights real-world impacts in research, protein design, and medicine. The article also discusses major challenges, including data scarcity and the complexity of validating model outputs. Looking ahead, the review highlights promising developments, such as modeling protein interactions and building virtual cell systems, which have the potential to enpower the next generation of bioengineering. This comprehensive overview serves as both a valuable resource for computational researchers and a strategic reference for scientists using these tools in related fields.

Researchers at the University of Oulu, Finland, have developed a pine‑bark–based water‑treatment medium that efficiently removes antibiotics as well as residues of blood‑pressure and antidepressant medicines from wastewater treatment plant effluent. A new doctoral thesis reports promising results with a simple and low‑cost method in which pine bark was modified with iron.