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Effects of Probiotics and Diet Management in Patients With Irritable Bowel Syndrome: A Systematic Review and Network Meta-analysis.
Nutr Rev
January 2025
Key Laboratory of Birth Defects and Related Diseases of Women and Children, Sichuan University, Ministry of Education, Chengdu, Sichuan 610041, China.
Context: The efficacy of probiotics and diet management in irritable bowel syndrome (IBS) is controversial, and their relative effectiveness remains unclear.
Objective: This study aimed to evaluate the effects of probiotics, diet management, and their combination on IBS.
Data Sources: PubMed, Embase, Cochrane, and Web of Science were searched from inception to July 10, 2023, for relevant studies, including symptom relief, IBS-symptom severity score (-SSS), and IBS-quality of life measure (-QOL).
Land use dynamics and their impact on hydrology and water quality of a river catchment: a comprehensive analysis and future scenario.
Environ Sci Pollut Res Int
January 2025
Department of Geography, Hong Kong Baptist University, Hong Kong SAR, China.
Land use changes profoundly affect hydrological processes and water quality at various scales, necessitating a comprehensive understanding of sustainable water resource management. This paper investigates the implications of land use alterations in the Gap-Cheon watershed, analyzing data from 2012 and 2022 and predicting changes up to 2052 using the Future Land Use Simulation (FLUS) model. The study employs the Hydrological Simulation Program-FORTRAN (HSPF) model to assess water quantity and quality dynamics.
View Article and Find Full Text PDFInvestigating the quality of European silver eels by quantifying contaminants and parasite infestation in a French Mediterranean lagoon complex.
Environ Sci Pollut Res Int
January 2025
Tour du Valat, Research Institute for the Conservation of Mediterranean Wetlands, Le Sambuc, Arles, France.
Coastal lagoons are diverse habitats with significant ecological gradients, which provide crucial ecosystem services but face threats from human activities such as invasive species and pollution. Among the species inhabiting the lagoons, the critically endangered European eel (Anguilla anguilla) is an emblematic species strongly impacted by contamination and parasitism. Several indicators were developed to assess the quality of eel at a large geographic scale.
View Article and Find Full Text PDFGrowth hormone improves the pregnancy outcomes in poor ovarian responders undergoing in vitro fertilization: an umbrella review.
J Assist Reprod Genet
January 2025
Evidence Based Medicine Center, School of Basic Medical Sciences, Lanzhou University, Lanzhou, China.
Poor ovarian response (POR) significantly impacts the success of assisted reproductive technology (ART), and growth hormone (GH) has been proposed as an adjuvant treatment to improve outcomes in POR patients undergoing in vitro fertilization (IVF). A systematic review and meta-analysis were conducted to evaluate the effectiveness of GH in enhancing pregnancy outcomes, registering a protocol on PROSPERO and searching multiple databases up to September 2023. Twelve systematic reviews/meta-analysis and 20 randomized controlled trials (RCTs) involving 1984 patients were included.
View Article and Find Full Text PDFA multiscale molecular structural neural network for molecular property prediction.
Mol Divers
January 2025
Key Laboratory for Macromolecular Science of Shaanxi Province, School of Chemistry and Chemical Engineering, Shaanxi Normal University, Xi'an, 710119, People's Republic of China.
Molecular Property Prediction (MPP) is a fundamental task in important research fields such as chemistry, materials, biology, and medicine, where traditional computational chemistry methods based on quantum mechanics often consume substantial time and computing power. In recent years, machine learning has been increasingly used in computational chemistry, in which graph neural networks have shown good performance in molecular property prediction tasks, but they have some limitations in terms of generalizability, interpretability, and certainty. In order to address the above challenges, a Multiscale Molecular Structural Neural Network (MMSNet) is proposed in this paper, which obtains rich multiscale molecular representations through the information fusion between bonded and non-bonded "message passing" structures at the atomic scale and spatial feature information "encoder-decoder" structures at the molecular scale; a multi-level attention mechanism is introduced on the basis of theoretical analysis of molecular mechanics in order to enhance the model's interpretability; the prediction results of MMSNet are used as label values and clustered in the molecular library by the K-NN (K-Nearest Neighbors) algorithm to reverse match the spatial structure of the molecules, and the certainty of the model is quantified by comparing virtual screening results across different K-values.
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