Magnesium (Mg) is an essential mineral that plays a critical role in the human body. It takes part in the process of energy metabolism and assists the maintenance of normal muscle function. A number of studies evaluated the association between Mg status/supplementation and exercise performance and found that the need for Mg increased as individuals’ physical activity level went up. Animal studies indicated that Mg might improve exercise performance via enhancing glucose availability in the brain, muscle and blood; and reducing/delaying lactate accumulation in the muscle. The majority of human studies focused on physiological effects in blood pressure, heart rate and maximal oxygen uptake (VO₂ max), rather than direct functional performances. Some cross-sectional surveys demonstrated a positive association between Mg status and muscle performance, including grip strength, lower-leg power, knee extension torque, ankle extension strength, maximal isometric trunk flexion, rotation, and jumping performance. Additionally, findings from intervention studies showed that Mg supplementation might lead to improvements in functional indices such as quadriceps torque. Moreover, Mg supplementation could improve gait speed and chair stand time in elderly women. This comprehensive review summarized the literature from both animal and human studies and aimed to evaluate scientific evidence on Mg status/supplementation in relation to exercise performance.

Insufficient physical activity and prolonged sedentary behavior have emerged as major global public health challenges. Short bouts (≤10 min) of accumulated exercise (SBAE) throughout the day may be a promising strategy to mitigate the adverse effects of prolonged sitting and promote physical activity, ultimately promoting overall health. However, previous ambiguity in defining this concept has resulted in a fragmented and inconsistent evidence base, impeding practical applications, the development of guidelines, and policymaking. The purpose of this study is to establish an operational definition of SBAE by synthesizing systematic reviews and research trials alongside an expert consensus. Additionally, it seeks to evaluate acute and long-term efficacy and feasibility, providing evidence-based recommendations for practice and future research directions. A literature search was performed across PubMed and Web of Science, followed by systematic screening and summarization of eligible studies based on predefined inclusion criteria. Inclusion criteria encompassed various modes/types of SBAE (bouts lasting ≤10 min, performed multiple times daily with ≥30 min intervals); both aerobic and resistance exercise were considered. Relevant systematic reviews and research trials were included. Methodological quality, risk of bias, and evidence certainty were assessed. Expert consensus was obtained through a survey to evaluate recommendations and agreement levels on findings. After analyzing 27 systematic reviews, 135 research studies, and an expert consensus involving 48 researchers from 11 countries, SBAE is defined as any exercise mode of activity, regardless of intensity, that is accumulated in either continuous or intermittent bouts lasting ≤10 min per session (including multiple intermittent sets) that are performed multiple times (≥2 sessions/day) per day, with intervals of ≥30 min between bouts or otherwise sufficient time for recovery. When used to interrupt prolonged periods of sedentary time, SBAE mitigates the acute adverse effects of sedentary behavior on more than 10 clinical biomarkers of endocrine, cardiovascular, and brain health/function among adults of diverse ages and conditions. Moreover, SBAE was superior for improving acute glycemic control compared to a single continuous exercise session. As a long-term intervention (average of 11 weeks), SBAE can improve over 20 health outcomes, including peak oxygen uptake, resting blood pressure, and metabolic health. Additionally, SBAE might be more effective than continuous exercise for improving longer-term glycemic control and body composition. Long-term completion rates for SBAE interventions are generally high (95%), with low dropout rates (12%) and high adherence rates even without supervision (85%), and its safety has been preliminarily validated. An operational definition of SBAE is provided along with its classification and acute and long-term efficacy. Practical exercise prescription recommendations and evidence-based strategies for various populations and contexts are provided. Future research should focus on generating high-quality evidence for SBAE in 5 key areas: quantification and monitoring, population-specific responses, optimization of exercise prescriptions, intervention efficacy, and practical implementation. Additionally, addressing policy, environmental, and promotional barriers is crucial for transitioning from expert consensus to public consensus, and for facilitating the application of this strategy in real-world environments.

Trichoderma spp. are diverse fungi with wide distribution. In this study, we report on three new species of Trichoderma, namely T. nigricans, T. densissimum and T. paradensissimum, collected from soils in China. Their phylogenetic position of these novel species was determined by analyzing the concatenated sequences of the second largest nuclear RNA polymerase subunit encoding gene (rpb2) and the translation elongation factor 1– alpha encoding gene (tef1). The results of the phylogenetic analysis showed that each new species formed a distinct clade: T. nigricans is a new member of the Atroviride Clade, and T. densissimum and T. paradensissimum belong to the Harzianum Clade. A detailed description of the morphology and cultural characteristics of the newly discovered Trichoderma species is provided, and these characteristics were compared with those of closely related species to better understand the taxonomic relationships within the Trichoderma.

Diabetes poses a considerable global health challenge, with varying levels of diabetes knowledge among healthcare professionals, highlighting the importance of diabetes training. Large Language Models (LLMs) provide new insights into diabetes training, but their performance in diabetes-related queries remains uncertain, especially outside the English language like Chinese. We first evaluated the performance of ten LLMs: ChatGPT-3.5, ChatGPT-4.0, Google Bard, LlaMA-7B, LlaMA2-7B, Baidu ERNIE Bot, Ali Tongyi Qianwen, MedGPT, HuatuoGPT, and Chinese LlaMA2-7B on diabetes-related queries, based on the Chinese National Certificate Examination for Primary Diabetes Care in China (NCE-CPDC) and the English Specialty Certificate Examination in Endocrinology and Diabetes of Membership of the Royal College of Physicians of the United Kingdom. Second, we assessed the training of primary care physicians (PCPs) without and with the assistance of ChatGPT-4.0 in the NCE-CPDC examination to ascertain the reliability of LLMs as medical assistants. We found that ChatGPT-4.0 outperformed other LLMs in the English examination, achieving a passing accuracy of 62.50%, which was significantly higher than that of Google Bard, LlaMA-7B, and LlaMA2-7B. For the NCE-CPFC examination, ChatGPT-4.0, Ali Tongyi Qianwen, Baidu ERNIE Bot, Google Bard, MedGPT, and ChatGPT-3.5 successfully passed, whereas LlaMA2-7B, HuatuoGPT, Chinese LLaMA2-7B, and LlaMA-7B failed. ChatGPT-4.0 (84.82%) surpassed all PCPs and assisted most PCPs in the NCE-CPDC examination (improving by 1 %-6.13%). In summary, LLMs demonstrated outstanding competence for diabetes-related questions in both the Chinese and English language, and hold great potential to assist future diabetes training for physicians globally.