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Gharials (Gavialis gangeticus) produce a sudden, high amplitude, pulsatile, underwater sound called a POP. In this study, gharial POPs ranged from 9 to 55 ms, and were clearly audible on land and water, at ≥500 m. POPs were only performed underwater by adult males possessing a sex-specific, cartilaginous narial excrescence, termed the ghara.

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Background: Knee Osteoarthritis (KOA) is a prevalent condition worldwide, significantly diminishing quality of life and productivity. Except for the alignment change, muscle activation patterns (MAP) have garnered increasing attention as another crucial factor contributing to KOA.

Objective: This study explores the factors, characteristics, and effects of MAP changes caused by KOA, providing a neuromuscular-based causal analysis for the rehabilitation treatment of KOA.

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Regulation of circadian gene activity in fibroblasts from ADHD patients through Rosiglitazone: a pilot study.

J Neural Transm (Vienna)

January 2025

Chair of Vascular Neurology, Dementia and Ageing, University Hospital Essen, Essen University Medical School, University of Duisburg-Essen, 45147, Essen, Germany.

Attention-deficit/hyperactivity disorder (ADHD) is a frequently observed condition, with about 70% of individuals diagnosed with ADHD experiencing irregular sleep-wake patterns. Beyond the primary symptoms of ADHD, there is a significant overlap with sleep-related issues, indicating that disrupted sleep patterns may exacerbate ADHD symptoms. ADHD-related sleep problems can be traced to a delayed circadian rhythm and a later onset of melatonin production.

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The energetic cost of human walking as a function of uneven terrain amplitude.

J Exp Biol

January 2025

Department of Biomedical Engineering, University of Calgary, Calgary, Alberta T2N 1N4, Canada.

Humans expend more energy walking on uneven terrain, but the amount varies across terrains. Few experimental characterizations exist, each describing terrain qualitatively without any relation to others or flat ground. This precludes mechanistic explanation of the energy costs.

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An AI-assisted algorithm has been developed to improve the detection of significant coronary artery disease (CAD) in high-risk individuals who have normal electrocardiograms (ECGs). This retrospective study analyzed ECGs from patients aged ≥ 18 years who were undergoing coronary angiography to obtain a clinical diagnosis at Chang Gung Memorial Hospital in Taiwan. Utilizing 12-lead ECG datasets, the algorithm integrated features like time intervals, amplitudes, and slope between peaks, a total of 561 features, with the XGBoost model yielding the best performance.

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