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Abstract Background Knee osteoarthritis (KOA) has become a public health issue. Several systematic reviews (SRs) and meta-analyses (MAs) indicate that traditional Chinese exercise (TCE) may be an effective treatment for reducing pain and stiffness and improving physical function in people with knee osteoarthritis (KOA). Objectives To evaluate the literature quality and evidence for the systematic reviews of TCE for KOA and provide evidence to support the clinical application of TCE for KOA. Methods Eight databases were searched from their inception to January 3, 2023, to retrieve relevant literature, including China National Knowledge Infrastructure (CNKI), Wanfang, Chinese Scientific Journal Database (VIP), China Biology Medical literature database (CBM), PubMed, Embase, Web of Science and Cochrane Library, without restrictions on publication date or language. AMSTAR-2 and PRISMA 2020 assessed the methodological and reporting quality of included SRs/MAs. The Grading of Recommendations Assessment, Development, and Evaluation (GRADE) system was utilized to evaluate the quality of evidence. Results A total of 18 SRs/MAs were included. The methodological quality was “very low” based on AMSTAR-2. The overall reporting quality was deficient based on PRISMA 2020. The quality of Chinese and English literature differed, with English literature being superior in methodological and reporting quality. Among 93 pieces of evidence obtained, 46 (49.46%) were of very low quality, 34 (36.56%) were of low quality, 13 (13.98%) were of moderate quality, and none were of high quality. TCE was supported by 76 pieces of evidence (81.72%). Conclusion TCE appears beneficial and safe for managing KOA. However, due to the relatively low methodological and evidentiary quality of included SRs/MAs, clinicians should interpret these findings cautiously.

The coastal areas of the lower reaches of Oujiang River Basin are rich in groundwater resources. However, the unsustainable exploitation and utilization of groundwater have led to significant changes in the groundwater environment. Understanding the characteristics and genesis of groundwater salinization is crucial for preventing its deterioration and ensuring sustainable utilization. In this study, a comprehensive approach combining the ion ratio method, mineral saturation index method and multivariate statistical analysis was employed to investigate the hydrochemical characteristics and main controlling factors in the study area. The findings reveal that: (1) Groundwater samples in study area exhibit a neutral to slightly alkaline pH. The predominant chemical types of unconfined water are HCO3-Ca·Na, HCO3·Cl-Na·Ca and HCO3·SO4-Ca·Na, while confined water mainly exhibits Cl·HCO3-Na and Cl-Na types. (2) Salinity coefficients indicate an increase in salinity from unconfined to confined water. TDS, Na+ and Cl– concentrations show an increasing trend from mountainous to coastal areas in unconfined water, while confined water displays variability in TDS, Na+ and Cl– concentrations. (3) Groundwater salinity is mainly influenced by water-rock interactions, including the dissolution of halite and gypsum, cation exchange, and seawater intrusion etc. Additionally, human activities and carbonate dissolution contribute to salinity in unconfined water. Seawater intrusion is identified as the primary factor leading to higher salinity in confined water compared to unconfined water, with increasing cation exchange and seawater interaction observed from unconfined to confined water.

Abstract In hydrothermal high-temperature abnormal mines, the composite heat-insulation zone structure, formed through a combination of guniting and grouting, serves to mitigate heat dissipation from the surrounding rock into the airflow. To comprehensively understand the thermal insulation performance of the composite heat-insulation zone structure, this study employs numerical simulation to analyze the following aspects: the variation in the temperature field within the surrounding rock of the roadway without insulation, the influence of structural parameters of the composite heat-insulation zone on temperature distribution in the surrounding rock of the roadway, and the thermal insulation effectiveness of the composite heat-insulation zone with varying structures. The findings indicate that the temperature distribution within the surrounding rock of the roadway lacking a heat-insulation zone is relatively uniform. However, as ventilation time extends, the heat regulation zone within the surrounding rock gradually extends deeper, ultimately forming an elliptical cooling area. The composite heat-insulation zone structure effectively mitigates heat transfer from deeper surrounding rock to the roadway wall, consequently altering the scope of the roadway's heat regulation zone. Enhancing the thermal insulation performance of the composite heat-insulation zone structure can be achieved by increasing the thickness of the thermal insulation layer, adjusting grouting rate and depth, and reducing the thermal conductivity of insulation materials. The thermal insulation effectiveness of the thermal insulation layer surpasses that of the grouting layer, with its performance primarily influenced by the thermal conductivity of the materials used. Simulation results demonstrate that the composite heat-insulation zone structure reduces the maximum heat flux on the roadway wall from 47.4 to 37.7 W/m2, resulting in a 20% reduction in heat transfer from deeper surrounding rock. These findings offer valuable insights for implementing thermal insulation techniques in hydrothermal high-temperature anomaly mines.

Abstract Efficient milk production in mammals confers evolutionary advantages by facilitating the transmission of energy from mother to offspring. However, the regulatory mechanism responsible for the gradual establishment of milk production efficiency in mammals, from marsupials to eutherians, remains elusive. Here, we find that mammary gland of the marsupial sugar glider contained milk components during adolescence, and that mammary gland development is less dynamically cyclic compared to that in placental mammals. Furthermore, fused in sarcoma (FUS) is found to be partially responsible for this establishment of low efficiency. In mouse model, FUS inhibit mammary epithelial cell differentiation through the cyclin-dependent kinase inhibitor p57Kip2, leading to lactation failure and pup starvation. Clinically, FUS levels are negatively correlated with milk production in lactating women. Overall, our results shed light on FUS as a negative regulator of milk production, providing a potential mechanism for the establishment of milk production from marsupial to eutherian mammals.

Abstract Background Living things from microbes to their hosts (plants, animals and humans) interact with each other, and their relationships may be described with complex network models. The present study focuses on the critical network structures, specifically the core/periphery nodes and backbones (paths of high-salience skeletons) in animal gastrointestinal microbiomes (AGMs) networks. The core/periphery network (CPN) mirrors nearly ubiquitous nestedness in ecological communities, particularly dividing the network as densely interconnected core-species and periphery-species that only sparsely linked to the core. Complementarily, the high-salience skeleton network (HSN) mirrors the pervasive asymmetrical species interactions (strictly microbial species correlations), particularly forming heterogenous pathways in AGM networks with both “backbones” and “rural roads” (regular or weak links). While the cores and backbones can act as critical functional structures, the periphery nodes and weak links may stabilize network functionalities through redundancy. Results Here, we build and analyze 36 pairs of CPN/HSN for the AGMs based on 4903 gastrointestinal-microbiome samples containing 473,359 microbial species collected from 318 animal species covering all vertebrate and four major invertebrate classes. The network analyses were performed at host species, order, class, phylum, kingdom scales and diet types with selected and comparative taxon pairs. Besides diet types, the influence of host phylogeny, measured with phylogenetic (evolutionary) timeline or “age”, were integrated into the analyses. For example, it was found that the evolutionary trends of three primary microbial phyla (Bacteroidetes/Firmicutes/Proteobacteria) and their pairwise abundance-ratios in animals do not mirror the patterns in modern humans phylogenetically, although they are consistent in terms of diet types. Conclusions Overall, the critical network structures of AGMs are qualitatively and structurally similar to those of the human gut microbiomes. Nevertheless, it appears that the critical composition (the three phyla of Bacteroidetes, Firmicutes, and Proteobacteria) in human gut microbiomes has broken the evolutionary trend from animals to humans, possibly attributable to the Anthropocene epoch and reflecting the far-reaching influences of agriculture and industrial revolution on the human gut microbiomes. The influences may have led to the deviations between modern humans and our hunter-gather ancestors and animals.

As the pace of industrialization and urbanization accelerates, water quality management faces increasing challenges, with traditional methods for pollutant source apportionment often proving inadequate in handling complex environmental data. This study enhances the precision and reliability of pollutant source identification by integrating Positive Matrix Factorization (PMF) models with diverse machine learning techniques. Utilizing data from 17 water quality monitoring stations along the Wuding River from 2017 to 2021, we employed Random Forest (RF), Support Vector Machine (SVM), Elastic Net (EN), and Extreme Gradient Boosting (XGBoost) models to predict the Water Quality Index (WQI) during dry and wet seasons. Results indicate that the RF model exhibited optimal performance in the dry season (R2 = 0.93), while the SVM was superior in the wet season (R2 = 0.94). SHAP (SHapley Additive exPlanations) value analysis identified CODMn and NH3-N as significant influencers on WQI in the dry season, whereas COD, BOD, and TP gained prominence during the wet season. SHAP values reveal the contribution of each feature to the model output, thereby enhancing the model’s transparency and interpretability. Additionally, feature importance identified by machine learning was utilized as weights to optimize the contribution rates predicted by the PMF model. The optimised model was able to identify the contribution of domestic and farm effluent discharges more accurately in the dry season, with a significant increase in the percentage of identification from 19.4 % to 45.4 %, and an increase in the percentage of contribution from agricultural non-point sources and domestic effluent in the rainy season. This research offers a novel perspective on the characteristics of river water pollution and holds significant implications for formulating data-driven environmental management strategies.

ObjectiveExplore the plasticity of the frontal associative areas in children and adolescents induced by exercise and potential moderating variables.MethodsComputer searches of CNKI, WOS, PubMed and EBSCO databases were conducted, and statistical analyses were performed based on SPSS 25.0, Stata 12.0 and Ginger ALE 2.3 software after literature screening, data extraction and quality assessment were performed independently by two researchers.ResultsA total of 13 articles, including 425 participants aged 8.9∼16.8 years, were included. Frequency analysis revealed that exercise induced enhanced activation in frontal, parietal, occipital, limbic system and cerebellum (P < 0.01). Activation Likelihood Estimation (ALE) meta-analysis revealed that exercise altered the activation status of the frontal association (medial frontal gyrus, middle frontal gyrus, inferior frontal gyrus and precentral gyrus), cuneus, lingual gyrus, cingulate gyrus, parahippocampal gyrus, caudate nucleus and cerebellar apex, with the volume of activation in the frontal association accounting for 61.81% of the total activation cluster volume and an enhanced activation effect. Additionally, the study design, age, gender, nationality, cognitive tasks, as well as exercise intensity, intervention time, and type of exercise may be potential moderating variables. Particularly, sustained exercise induced a decrease in activation in the left parahippocampal gyrus, culmen, and lingual gyrus, while variable exercise induced an increase in activation in the left middle frontal gyrus.ConclusionExercise-induced activation increase in the frontal associative areas of children and adolescents is dominant, especially longer periods of moderate-intensity variable exercise can induce more brain region activation. However, some of the included studies are cross-sectional, and the accuracy of the results still requires further verification.Systematic review registrationhttps://www.crd.york.ac.uk/prospero/, identifier PROSPERO, CRD42022348781.

The objectives of this study were to measure the mediation effect of plasma proteins and to clarify their mediating role in the relationship between stroke risk and particulate matter 2.5 (PM2.5) exposure. The possible mediating role of plasma proteins on the causative link between PM2.5 exposure and stroke incidence were examined using a two-step Mendelian randomization (MR) approach based on two-sample Mendelian randomization (TSMR). The findings revealed a significant positive causal relationship between PM2.5 exposure and stroke, with an inverse variance weighted odds ratio of 1.219 (95 % CI: 1.002 – 1.482, P < 0.05). Additionally, a positive causal association was identified between PM2.5 exposure and several plasma proteins, including FAM134B, SAP, ITGB7, Elafin, and DCLK3. Among these, FAM134B, ITGB7, Elafin, and DCLK3 also demonstrated a positive causal association with stroke, whereas only SAP was found to be negatively causally associated with stroke. Remarkably, four plasma proteins, namely DCLK3, FAM134B, Elafin, and ITGB7, were identified as mediators, accounting for substantial proportions (14.5 %, 13.6 %, 11.1 %, and 9.9 %) of the causal association between PM2.5 and stroke. These results remained robust across various sensitivity analyses. Consequently, the study highlights the significant and independent impact of PM2.5 on stroke risk and identifies specific plasma proteins as potential targets for preventive interventions against PM2.5-induced stroke.