This paper aimed to systematically evaluate the effects of hypoxic training at different fraction of inspired oxygen (FiO₂) on body composition, glucose metabolism, and lipid metabolism in obese individuals, and to determine the optimal oxygen concentration range to provide scientific evidence for personalized and precise hypoxic exercise prescriptions. A systematic search was conducted in the Cochrane Library, PubMed, Web of Science, Embase, and CNKI databases for randomized controlled trials and pre-post intervention studies published up to March 31, 2025, involving hypoxic training interventions in obese populations. Meta-analysis was performed using RevMan 5.4 software to assess the effects of different fraction of inspired oxygen (FiO₂≤14% vs. FiO₂>14%) on BMI, body fat percentage, waist circumference, fasting blood glucose, insulin, HOMA-IR, triglycerides (TG), low-density lipoprotein cholesterol (LDL-C), and high-density lipoprotein cholesterol (HDL-C), with subgroup analyses based on oxygen concentration. A total of 22 studies involving 292 participants were included. Meta-analysis showed that hypoxic training significantly reduced BMI (mean difference (MD)=-2.29,95%CI: -3.42 to -1.17, P<0.000 1), body fat percentage (MD=-2.32, 95%CI: -3.16 to -1.47, P<0.001), waist circumference (MD=-3.79, 95%CI: -6.73 to -0.85, P=0.01), fasting blood glucose (MD=-3.58, 95%CI: -6.23 to -0.93, P=0.008), insulin (MD=-1.60, 95%CI: -2.98 to -0.22, P=0.02), TG (MD=-0.18, 95%CI: -0.25 to -0.12, P<0.001), and LDL-C (MD=-0.25, 95%CI: -0.39 to -0.11, P=0.000 3). Greater improvements were observed under moderate hypoxic conditions with FiO₂>14%. Changes in HOMA-IR (MD=-0.74, 95%CI: -1.52 to 0.04,P=0.06) and HDL-C (MD=-0.09, 95%CI: -0.21 to 0.02, P=0.11) were not statistically significant. Hypoxic training can significantly improve body composition, glucose metabolism, and lipid metabolism indicators in obese individuals, with greater benefits observed under moderate hypoxia (FiO>14%). As a key parameter in hypoxic exercise interventions, the precise setting of oxygen concentration is crucial for optimizing intervention outcomes.

ObjectiveTo investigate the expression of scaffold protein PDLIM5 in multiple sclerosis （MS） patients and the mouse microglial cell line BV2， and to explore its effects on the phagocytosis of microglial cells. MethodsPeripheral blood samples were collected from 24 MS patients and 6 healthy volunteers as controls. The expression levels of PDLIM5 were detected by real-time quantitative PCR. A neuroinflammation cell model was established by treating the mouse microglial cell line BV2 with lipopolysaccharide （LPS， 1 µg/mL）. The expression levels of PDLIM5 were measured by Western Blot. The effect of PDLIM5 expression on phagocytosis was analyzed by transfecting BV2 cells with PDLIM5 shRNA plasmids or PDLIM5 overexpression plasmids. ResultsReal-time quantitative PCR results showed that compared with the healthy control group， the expression level of PDLIM5 from the MS patients was significantly increased in monocytes ［2.78 （0.70-6.86） vs. 0.54 （0.39-1.51）， P=0.036］ and lymphocytes ［1.62 （0.90-2.26） vs. 0.11 （0.05-0.21）， P<0.001］. Western Blot results indicated that PDLIM5 expression was significantly upregulated in BV2 cells following LPS stimulation （P<0.05）. Plasmid transfection experiments demonstrated that knockdown of PDLIM5 inhibited the phagocytic capacity of BV2 cells as measured by trypan blue uptake （P<0.05）， while overexpression of PDLIM5 enhanced the phagocytic ability of BV2 cells （P<0.001）. ConclusionUnder neuroinflammatory conditions， PDLIM5 expression is elevated， and this upregulation promotes the phagocytosis of microglial cell.

Objective To explore the mechanism of the gut-lung axis in paraquat-induced lung injury in mice, with a focus on analyzing the changes in intestinal gene expression and their potential roles. Methods Specific pathogen-free C57BL/6 wild-type mice were randomly divided into control, low-dose, and high-dose groups, with 10 mice in each group. Mice in the three groups received a single intragastric administration of paraquat solution at doses of 0, 25, or 50 mg/kg body weight. The mice were euthanized on day 21. Lung histopathological changes were assessed, and the differentially expressed genes (DEGs) in the intestinal tissues of mice in these two groups were analyzed through transcriptomics. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were conducted to explore potential mechanisms of the gut-lung axis in paraquat-induced lung injury and fibrosis. Results Paraquat exposure induced dose-dependent pulmonary injury and fibrosis in the mice. The Ashcroft score of lung tissue was higher in the mice of low-dose group than that in the control group (P<0.05). Both the lung organ coefficient and Ashcroft score of lung tissues in the mice of high-dose group were higher than those in the control group and the low-dose group (all P<0.05). The result of transcriptomic analysis showed 146 DEGs, including 91 upregulated and 55 downregulated genes, in intestinal tissues of mice in the low-dose group, and 57 DEGs, including 47 upregulated and 10 downregulated genes in the high-dose group, compared with the control group. Notably, 19 DEGs were commonly altered in both low- and high-dose groups. The result of GO enrichment analysis showed that the DEGs were primarily involved in biological processes including "immune response", "oxidative stress" and "cell differentiation". The result of KEGG enrichment analyses showed that DEGs were primarily involved in key processes including "oxidative stress response path way", "immune response path way" and "digestion and absorption path way". Conclusion Paraquat exposure alters intestinal gene expression, particularly in genes in biological processes related to immune responses and oxidative stress. These changes may mediate inflammatory signaling via the gut-lung axis and contribute to the development of paraquat-induced pulmonary fibrosis.

Objective: To explore relationship of sleep quality with overweight and obesity among middle school students, so as to provide a reference basis for improving adolescent sleep health. Methods: From September to December 2023, 5 713 middle school students aged 13 to 18 were selected by stratified cluster random sampling method in six regions, including Shanghai, Suzhou, Taiyuan, Wuyuan, Xingyi and Urumqi. Sleep quality survey was conducted on middle school students by Pittsburgh Sleep Quality Index. Height and weight were measured, and World Health Organization s standards for growth and development of children and adolescents was used to evaluate their nutritional status. Both χ 2 test and Logistic regression analysis were used to analyze the association between sleep quality and nutritional status of middle school students. Results: The non compliance detection rate of sleep quality was 38.4% among girls, but 29.2% among boys, and the difference was of statistical significance( χ 2=54.08, P < 0.01 ). The detection rate of substandard sleep quality was 34.2% in the group with normal nutritional status, 38.3% in the group with overweight, 43.7% in the group with obesity and 26.0% in the group with emaciation, and the difference in the rates of substandard sleep quality among middle school students of different nutritional status was statistically significant ( χ 2=68.15, P <0.01). Logistic regression analysis showed that, after controlling for mental health and physical activity, the detection rate of substandard sleep quality in the obese groups was 1.30 times higher than that in the normal group, respectively( OR =1.30, 95% CI =1.06- 1.59 , P <0.01). Conclusions Sleep quality is correlated with overweight and obesity among middle school students, and there are gender differences. Intervention policies should be formulated according to the characteristics of different genders.

Objective: To investigate the indoor fine particulate matter (PM 2.5 ) pollution and its influencing factors in children s bedrooms using solid fuel, so as to provide evidence for effective strategy to reduce PM 2.5 pollution. Methods: From December 2019 to November 2020, 198 households (108 in the north, 90 in the south) from two pilots in the north(Jiamusi in Heilongjiang Province) and south of China (Mianyang in Sichuan Province) were selected, and status of solid fuels using were obtained through home visits, dynamic changes in PM 2.5 concentrations in children s bedrooms were monitored by using real time online instruments, and the influencing factors of PM 2.5 pollution were analyzed by using a mixed effects model. Results: During the monitoring period, the daily PM 2.5 concentrations in the northern and southern pilot were 78.33 (40.50, 154.80) and 38.54(26.20, 58.46) μg/m 3, respectively, exceeding standard rates of 44.57% and 33.22%. During the heating period, the daily PM 2.5 concentrations in the northern and southern pilot were 212.50(133.60,244.10) and 104.42(73.97, 134.90) μg/m 3, respectively, with over standard rates of 96.75% and 86.96%. The mixed effects model analysis results showed that children s bedroom PM 2.5 concentrations were associated with solid fuel usage duration, window opening time, room layout (shared entrance door between kitchen and bedroom), indoor smoking, indoor humidity, and solid fuel use in the bedroom ( β =0.19, -0.05, 1.20, 0.43, 0.02, 0.35, all P <0.05). Conclusion Solid fuel combustion significantly comtributes to PM 2.5 pollution in children s bedrooms, with more pronounced impacts observed in northern China compared to southern regions.

Objective: To explore the relationship between positive parenting styles and academic emotions in junior high school students, as well as the chain mediation effects of parent-child communication and peer relationships, providing a theoretical basis for family education interventions. Methods: Using stratified cluster random sampling, 1 063 students from four junior high schools in a city in Anhui Province were selected for questionnaire surveys, form March to April, 2025. Core variables were measured using the Short form Parenting Style Scale, Adolescent Parent-Child Communication Scale, Peer Relationship Scale, and Adolescent Academic Emotion Questionnaire. Group comparison was conducted using t-test or analysis of variance, and Pearson correlation analysis was used to examine the correlation between positive parenting styles, peer relationships, parent-child communication and positive academic emotions. Multiple linear regression analysis was used to examine the effects of positive parenting styles, peer relationships and parent-child communication on positive academic emotions. A mediation effect model and Bootstrap method were employed to test the chain mediation effects. Results: Students who were class leaders, had parents with higher education levels, or came from intact families scored significantly higher on positive academic emotions ( t/F =7.23, 13.73, 10.67, 4.45, all P < 0.01 ). Positive parenting styles, peer relationships, and parent-child communication were all positively correlated with positive academic emotions ( r =0.45, 0.41, 0.38), and all three positively predicted positive academic emotions ( β =0.24, 0.23, 0.12) (all P < 0.01 ). Further analysis showed that positive parenting styles directly predicted positive academic emotions ( β =0.40) and also indirectly influenced academic emotions through parent-child communication ( β =0.07), peer relationships ( β =0.05), and the chain mediation path of "parent-child communication → peer relationships" ( β =0.04) (all P <0.05), with the total indirect effect accounting for 40.55%. Conclusion Positive parenting styles enhance junior high school students academic emotions through the chain mediation path of "parent-child communication → peer relationships", providing theoretical support for interventions within the educational ecosystem.

Background With the progression of industrialization, an increasing number of emerging contaminants are entering aquatic environments, posing significant threats to the safety of drinking water. Therefore, establishing a system for identifying unknown hazardous factors and implementing safety warning mechanisms for drinking water is of paramount importance. Among these efforts, non-target screening plays a critical role, but its effectiveness is largely constrained by the scope of coverage of sample pre-treatment methods. Objective To integrate modern chromatography/mass spectrometry techniques with advanced data mining methods to develop a non-discriminatory sample pre-treatment method for comprehensive enrichment of unknown contaminants in drinking water, laying a technical foundation for the discovery and identification of unknown organic hazardous factors in drinking water. Methods A non-discriminatory pre-treatment method based on supramolecular and solid-phase extraction was developed. The final target compounds including 333 pesticides, 194 pharmaceuticals and personal care products (PPCPs), and 59 per- and polyfluoroalkyl substances (PFASs) were used for optimizing the pre-treatment method, confirming its coverage. The impacts of different eluents on the absolute recovery rates of target compounds were compared to select the conditions with the highest recovery for sample pre-treatment. The effects of different supramolecular solvents and salt concentrations on target compound recovery were also evaluated to determine the most suitable solvent and salt concentration. Results The solid-phase extraction elution solvents, supramolecular extraction solvents, and salt concentrations were optimized based on the target compound recovery rates. The optimal recovery conditions were achieved using 2 mL methanol, 2 mL methanol (containing 1% formic acid), 2 mL ethyl acetate, 2 mL dichloromethane, hexanediol supramolecular solvent, and 426 mg salt. The detection method developed based on these conditions showed a good linear relationship for all target compounds in the range of 0.1-100.0 ng·mL⁻¹, with R² > 0.99. The method’s limit of detection ranged from 0.01 ng⁻¹ to 0.95 ng⁻¹, and 95% of target compounds were recovered in the range of 20%-120%, with relative standard deviation (RSD) less than 30%, indicating good precision. Conclusion The combined pre-treatment method of solid-phase extraction and supramolecular solvent extraction can effectively enrich contaminants in drinking water across low, medium, and high polarities, enabling broad-spectrum enrichment of diverse trace contaminants in drinking water. It provides technical support for broad-spectrum, high-throughput screening and identification of organic pollutants in drinking water, and also serves as a reference for establishing urban drinking water public safety warning systems.

Eukaryotic translation initiation factor 5A (eIF5A) is the only known protein in eukaryotes that contains a hydroxyputrescine lysine modification. Only the modified form of eIF5A is biologically active and is widely involved in protein translation, mRNA degradation, autophagy, and other intracellular processes. Epithelial-mesenchymal transition (EMT) is a process in which epithelial cells transform into mesenchymal phenotype cells through a highly regulated program. It plays a key role in embryonic development, tissue regeneration, and wound healing. Based on its biological functions, EMT can be classified into three types: I, II, and III. Type III EMT is the core mechanism underlying malignant tumor cell invasion and metastasis. This EMT mechanism involves the canonical pathway induced by transforming growth factor-β (TGF-β) and is regulated by various growth factors (TRAF6, EGF, IGF, HGF, VEGF), transcription factors (Twist, Slug, NF-κB, E12/E47, SIP1, ZEB1, etc.), and signaling pathways such as Wnt/β-catenin and PEAK1. eIF5A can influence tumor cell proliferation, invasion, and metastasis by regulating EMT-related signaling pathways. The known signaling pathways through which eIF5A regulates EMT include the canonical Smad signaling pathway and non-canonical pathways such as Rho/Rac1, Twist, STAT3, and MAT1. Additionally, certain miRNA family members, such as miR-30b, miR-599, and miR-203, can bind to the 3'-UTR of eIF5A2, inhibiting its expression and subsequently suppressing the EMT process in cancer cells, including gastric cancer and colorectal cancer. GC7, an inhibitor targeting the key enzyme DHPS involved in eIF5A modification, has been shown to reverse the EMT mechanism in oral squamous cell carcinoma, lung cancer, and breast cancer by regulating cytokine-mediated signaling pathways, including HIF-1α, STAT3/c-MYC, and Twist. However, to date, no inhibitors directly targeting eIF5A have been developed. In recent years, the mechanism of eIF5A activation catalyzed by DHPS and DOHH has become increasingly clear. As the only protein involved in lysine deoxyhydroxymethylation, DHPS may play a more critical role than eIF5A in the overall signal transduction process. Through in-depth analysis of the DHPS protein structure and its active site, researchers have shifted their approach to DHPS inhibitor development from substrate analog inhibitors (such as GC7, CNI-1493, DHSI-15, etc.) to allosteric inhibitors (11g, 26d, 8m, GL-1, etc.). GC7 is not suitable for clinical trials due to its lack of specificity and low bioavailability, and the therapeutic potential of novel allosteric inhibitors has yet to be clarified. Therefore, there is a significant gap in the development of covalent drugs targeting DHPS for cancer treatment in clinical settings. This paper reviews the research progress on eIF5A in regulating EMT, focusing on the molecular mechanisms by which eIF5A influences tumor cell invasion and migration. It also discusses the characteristics and current limitations of inhibitors targeting the hypusine pathway, aiming to provide insights for studying tumor metastasis mechanisms and drug discovery.

ObjectiveTo investigate the relationship between mitochondrial DNA copy number (mtDNAcn) and cognitive dysfunction, and its mediating role between type 2 diabetes mellitus (T2DM) and cognitive dysfunction. MethodsA case-control study was conducted from May 2019 to April 2021 at the Shanghai Yangpu District Central Hospital, China. A total of 193 subjects were recruited and divided into two groups based on the Montreal Cognitive Assessment (MoCA): normal control (NC) group (n=95) and cognitive impairment group (n=98). The prevalence of T2DM was determined on the basis of medical history, while mtDNAcn in peripheral blood samples was quantified using realtime fluorescent quantitative polymerase chain reaction. ResultsUnivariate analyses revealed that the mean mtDNAcn in the cognitive impairment group was 0.76±0.37, significantly lower than that in the NC group (1.06±0.45) (P<0.05). Logistic regression analyses showed that higher mtDNAcn was associated with a reduced risk of cognitive impairment (OR=0.315, 95%CI: 0.125‒0.795). Additionaly, a statistically significant positive correlation was observed between mtDNAcn and the total MoCA score (r=0.381, P<0.01). Morever, T2DM history (OR=2.741, 95%CI: 1.002‒7.497) and elevated glycosylated hemoglobin (HbA1c) levels (OR=1.796, 95%CI: 1.190‒2.711) were identified as risk factors for cognitive impairment. Mediation analyses indicated that mtDNAcn served as a mediator between T2DM/HbA1c and the risk of cognitive impairment, with proportions of mediating effect of 9.04% and 9.18%, respectively. ConclusionPatients with mild and moderate cognitive impairment have significantly lower mtDNAcn than those with normal cognitive function. Reduced mtDNAcn is an influencing factor for cognitive dysfunction and may play a mediating role in the association between T2DM and mild to moderate cognitive impairment.

Dormant tumor cells constitute a population of cancer cells that reside in a non-proliferative or low-proliferative state, typically arrested in the G0/G1 phase and exhibiting minimal mitotic activity. These cells are commonly observed across multiple cancer types, including breast, lung, and ovarian cancers, and represent a central cellular component of minimal residual disease (MRD) following surgical resection of the primary tumor. Dormant cells are closely associated with long-term clinical latency and late-stage relapse. Due to their quiescent nature, dormant cells are intrinsically resistant to conventional therapies—such as chemotherapy and radiotherapy—that preferentially target rapidly dividing cells. In addition, they display enhanced anti-apoptotic capacity and immune evasion, rendering them particularly difficult to eradicate. More critically, in response to microenvironmental changes or activation of specific signaling pathways, dormant cells can re-enter the cell cycle and initiate metastatic outgrowth or tumor recurrence. This ability to escape dormancy underscores their clinical threat and positions their effective detection and elimination as a major challenge in contemporary cancer treatment. Hypoxia, a hallmark of the solid tumor microenvironment, has been widely recognized as a potent inducer of tumor cell dormancy. However, the molecular mechanisms by which tumor cells sense and respond to hypoxic stress—initiating the transition into dormancy—remain poorly defined. In particular, the lack of a systems-level understanding of the dynamic and multifactorial regulatory landscape has impeded the identification of actionable targets and constrained the development of effective therapeutic strategies. Accumulating evidence indicates that hypoxia-induced dormancy tumor cells are accompanied by a suite of adaptive phenotypes, including cell cycle arrest, global suppression of protein synthesis, metabolic reprogramming, autophagy activation, resistance to apoptosis, immune evasion, and therapy tolerance. These changes are orchestrated by multiple converging signaling pathways—such as PI3K-AKT-mTOR, Ras-Raf-MEK-ERK, and AMPK—that together constitute a highly dynamic and interconnected regulatory network. While individual pathways have been studied in depth, most investigations remain reductionist and fail to capture the temporal progression and network-level coordination underlying dormancy transitions. Systems biology offers a powerful framework to address this complexity. By integrating high-throughput multi-omics data—such as transcriptomics and proteomics—researchers can reconstruct global regulatory networks encompassing the key signaling axes involved in dormancy regulation. These networks facilitate the identification of core regulatory modules and elucidate functional interactions among key effectors. When combined with dynamic modeling approaches—such as ordinary differential equations—these frameworks enable the simulation of temporal behaviors of critical signaling nodes, including phosphorylated AMPK (p-AMPK), phosphorylated S6 (p-S6), and the p38/ERK activity ratio, providing insights into how their dynamic changes govern transitions between proliferation and dormancy. Beyond mapping trajectories from proliferation to dormancy and from shallow to deep dormancy, such dynamic regulatory models support topological analyses to identify central hubs and molecular switches. Key factors—such as NR2F1, mTORC1, ULK1, HIF-1α, and DYRK1A—have emerged as pivotal nodes within these networks and represent promising therapeutic targets. Constructing an integrative, systems-level regulatory framework—anchored in multi-pathway coordination, omics-layer integration, and dynamic modeling—is thus essential for decoding the architecture and progression of tumor dormancy. Such a framework not only advances mechanistic understanding but also lays the foundation for precision therapies targeting dormant tumor cells during the MRD phase, addressing a critical unmet need in cancer management.