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Increasing physical activity (PA) is recognised as an efficacious approach for preventing and treating cardiometabolic diseases. Recently, the composition of microorganisms living within the gut has been proposed as an important appropriate target for treating these diseases. Whether PA is related to faecal microbiota diversity and composition in humans remains to be ascertained. Thus, we examined the association of the time spent in objectively measured PA with faecal microbiota diversity and composition in young adults. A cross-sectional study enrolled 88 young adults aged 22.0 ± 2.3 years (72.7% women), whose time spent in PA at different intensities was objectively measured with a wrist-worn accelerometer for 7 consecutive days. Faecal microbiota diversity and composition were analysed with hypervariable tag sequencing of the V3-V4 region of the 16S rRNA gene. The mean Euclidean Norm of the raw accelerations Minus One (mg) during waking time, considered as overall PA, and the time spent in vigorous PA were positively correlated with alpha diversity indexes (all rho ≥ 0.23, P ≤ 0.034). Regarding faecal microbiota composition, participants with low time spent in vigorous PA had higher relative abundance of the Gammaproteobacteria class (q = 0.021, FDR = q-value) compared to the participants with high time spent in vigorous PA, and lower relative abundance of the Porphyromonadaceae family (q = 0.031) and the Alistipes genus (q = 0.015) compared to the individuals with high and intermediate time spent in vigorous PA, respectively. Our results suggest that PA, especially of vigorous intensity, is related to faecal microbiota diversity and the Gammaproteobacteria class and Porphyromonadaceae family in young adults.
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http://dx.doi.org/10.5114/biolsport.2025.139850 | DOI Listing |
Probiotics Antimicrob Proteins
September 2025
Key Laboratory of the Ministry of Education for Wildlife and Plant Resources Conservation in Southwest China, College of Life Sciences, China West Normal University, Nanchong, Sichuan, China.
Enterotoxigenic Escherichia coli (ETEC) is a prevalent intestinal pathogen that significantly impacts both human and animal health. G83, isolated from giant panda feces, has demonstrated notable probiotic properties. In this study, C57BL/6 J mice were randomly divided into Control, ETEC, and G83 groups.
View Article and Find Full Text PDFGut Microbes
December 2025
Clinical Microbiome Unit, Laboratory of Host Immunity and Microbiome, Division of Intramural Research, National Institute of Allergy and Infectious Disease, National Institute of Health, Bethesda, MD, USA.
Parity, the number of pregnancies carried beyond 20 weeks, influences the maternal gut microbiome. However, whether parity modulates the infant microbiome longitudinally remains underexplored. To address this, 746 infants in a longitudinal cohort study were assessed.
View Article and Find Full Text PDFKnee Surg Sports Traumatol Arthrosc
September 2025
International Joint Center, Acibadem Mehmet Ali Aydınlar University, Istanbul, Turkey.
Despite undisputed success of orthopaedic procedures, surgical site infections (SSI) such as periprosthetic joint infection (PJI) continues to compromise the outcome and result in major clinical and economic burden. The overall rate of infection is expected to rise in the future resulting in significant associated mortality and morbidity. Traditional concepts have largely attributed the source of PJI to exogenous pathogens.
View Article and Find Full Text PDFJ Anim Sci
September 2025
Department of Animal Biotechnology, Dankook University, Cheonan, 31116, Republic of Korea.
The post-weaning period is stressful for pigs due to changes in their environment and diet. The occurrence of diarrhea at this stage is high. Growth promoters such as antibiotics and zinc oxide (ZnO) have been used to not only reduce post-weaning diarrhea but also improve growth performance of weaning pigs.
View Article and Find Full Text PDFBrain Behav
September 2025
Department of Neurosurgery, First Medical Center of the Chinese PLA General Hospital, Beijing, People's Republic of China.
Background: The gut microbiota plays a crucial role in the development of glioma. With the evolution of artificial intelligence technology, applying AI to analyze the vast amount of data from the gut microbiome indicates the potential that artificial intelligence and computational biology hold in transforming medical diagnostics and personalized medicine.
Methods: We conducted metagenomic sequencing on stool samples from 42 patients diagnosed with glioma after operation and 30 non-intracranial tumor patients and developed a Gradient Boosting Machine (GBM) machine learning model to predict the glioma patients based on the gut microbiome data.