MPFToD lifts SOTA 56.3%→61% via three modular tasks and transfers to dialogue acts & more

 SSL-powered EFAM: bi-path fusion and channel attention elevate SED accuracy while cutting labeled-data needs

CAS-FEND distills comment knowledge into a content-only student, beating comment-aware rivals with a quarter of comments for timely fake-news catch

A new study published in Microbiome Research Reports reveals that a polyphenol-rich dietary pattern can significantly reduce inflammation and improve gut microbiota composition in adults aged 60 years and older with elevated inflammatory markers. Conducted as part of the MaPLE (Microbiome mAnipulation through Polyphenols for managing Leakiness in the Elderly) trial, this research showed that an eight-week polyphenol-rich diet decreased key inflammatory markers such as IL-6 and CRP, enhanced microbial diversity, and increased beneficial bacteria including Blautia and Dorea. Metabolomic analyses indicated notable shifts in polyphenol-derived metabolites associated with anti-inflammatory effects. These findings highlight the potential of polyphenol-rich diets as personalized nutritional strategies to counteract “inflammaging” and promote healthy aging.

 

Autonomous driving systems increasingly rely on data-driven approaches, yet many still struggle with reasoning, handling rare scenarios, and transparently explaining their actions. A new study introduces DriveMLM, a multi-modal large language model framework that aligns language-based reasoning with structured behavioral planning states, enabling full closed-loop driving in realistic simulators. By integrating multi-view images, LiDAR inputs, traffic rules, and natural-language instructions, DriveMLM generates both driving decisions and human-readable explanations that map directly to vehicle control. The system significantly improves safety, adaptability, and interpretability, demonstrating how large language models (LLMs) can advance the next generation of autonomous driving technology.

Understanding how sound travels through the middle ear is essential for designing reliable hearing implants. Traditional measurements of the middle ear transfer function (METF) can be affected by inner ear impedance and surgical manipulation, limiting their accuracy. This study introduces a new technique that eliminates inner ear interference while precisely capturing stapes footplate vibrations at multiple points. By accessing the vestibular side of the stapes through a trans-petrous approach, the researchers generated a stable and reproducible METF reference range using human temporal bone specimens. This refined method offers more reliable data for evaluating implant performance and enhances the biomechanical understanding of auditory transmission.

Eustachian tube dysfunction often determines whether a routine ear infection clears quickly or develops into a persistent condition. This study reveals that the mitochondrial enzyme SIRT3 plays a crucial protective role during acute inflammation. Using a mouse model of otitis media, the researchers show that loss of SIRT3 transforms a typical inflammatory reaction into a more severe pathological process—characterized by excessive mucus buildup, ciliary damage, increased resistance to tube opening, and impaired mucociliary transport. These findings highlight SIRT3 as an unrecognized stabilizer of middle-ear physiology and help explain why some infections resolve smoothly while others progress toward chronic disease.

A comprehensive review in Current Molecular Pharmacology highlights how machine learning, molecular dynamics simulations, and hybrid AI-MD platforms are revolutionizing antimicrobial discovery. These computational strategies can drastically reduce development time and costs while enabling the design of novel antibiotics and antimicrobial peptides. The authors propose an integrated “computation-experiment-clinical translation” framework to overcome current bottlenecks and combat the global AMR crisis.