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.

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.

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.

ObjectiveTo investigate whether there are differences in the efficacy of Gegen Qinliantang with different contents of Puerariae Lobatae Radix on the acute enteritis （AE） model mice and provide a scientific basis for the interpretation of Gegen Qinliantang in the treatment of "Xie Re Li". MethodsA total of 112 male BALB/c mice were randomly divided into a blank group，model group，single Puerariae Lobatae Radix group，non-Puerariae Lobatae Radix group，regular dose Gegen Qinliantang group （regular dose group），half-dose Puerariae Lobatae Radix group，and doubled-dose Puerariae Lobatae Radix group， with 16 mice in each group. Hematoxylin-eosin （HE） staining was used to observe the pathological changes of the colon tissue. Western blot was employed to detect the expression of ZO-1 （a protein in the tight junction） and Occludin in the colon tissue， as well as the changes of tumor necrosis factor-α （TNF-α） and interleukin-1β （IL-1β）. ResultsCompared with the blank group，the DAI scores of the mice in the model group were significantly higher （P<0.05），and the histopathological sections of their colon tissues showed mucosal damage，glandular atrophy，disordered arrangement，and a large number of inflammatory cells infiltration，and the expression of ZO-1 and Occludin proteins in their colon tissues was significantly down-regulated （P<0.05，P<0.01）. The expression of inflammatory factors TNF-α and IL-1β was significantly up-regulated （P<0.05，P<0.01）. Compared with the model group，the DAI scores of mice in all dosing groups decreased significantly （P<0.05），with the most significant effect in the regular dose group. After 7 d of drug administration，the regular dose group had the best impact on the repair of colonic mucosa in the AE mouse model. The regular dose group significantly down-regulated the expression of TNF-α （P<0.05） and significantly up-regulated the expression of ZO-1 protein （P<0.05）. The doubled-dose Puerariae Lobatae Radix group significantly down-regulated the expression of IL-1β protein （P<0.01），and there was no significant difference between all dosing groups and the model group in terms of the expression of Occludin protein. After 14 d of drug administration，the best effect on the repair of colonic mucosa in the AE mouse model was observed in the doubled dose Puerariae Lobatae Radix group. All groups except the non-Puerariae Lobatae Radix group significantly down-regulated the expression of TNF-α （P<0.01）. Meanwhile，the regular dose group and doubled-dose Puerariae Lobatae Radix group significantly elevated the expression level of Occludin protein （P<0.01）. The doubled-dose Puerariae Lobatae Radix group also significantly inhibited the expression of IL-1β protein （P<0.05） and up-regulated ZO-1 protein expression （P<0.05）. ConclusionGegen Qinliantang can reduce the pathological damage of colon tissue， protect the barrier function and structure of intestinal epithelial cells， and reduce the expression of inflammatory factors， so as to achieve the therapeutic effect of AE model mice. When comparing the therapeutic efficacy of Gegen Qinliantang containing different Gegen contents， Gegen Qinliantang with the proportion of the original formula of Zhongjing was the most effective in AE model mice.

Objective To analyze the trend of global cellulitis disease burden from 1990 to 2019, and to provide a theoretical basis for the prevention and control of cellulitis disease. Methods The Global Burden of Disease 2021 (GBD2021) data were collected, and data on the incidence, mortality, and disability-adjusted life year (DALY) of cellulitis were analyzed for each country worldwide. The estimated annual percentage change (EAPC) and age-standardized rate (ASR) were used to estimate the trend change of cellulitis from 1990 to 2021. Results The global burden of cellulitis increased significantly in 2021, with 55.96 million cases, 28.9 million deaths and 876.1 million DALYs, respectively. Incidence and mortality rates were generally higher in males than in females. The incidence and DALYs were higher in high SDI regions, with the highest burden observed in South Asia. In contrast, East Asia exhibited the lowest burden and demonstrated a declining trend. There were significant differences between countries, with India having the highest prevalence, the United States having the highest incidence, and Bahrain having the fastest growing rate.In 2021, China had the lowest age-standardised incidence of cellulitis in the world and the fastest declining age-standardised incidence and age-standardised DALYs. Conclusion The global disease burden of cellulitis is increasing from 1990-2021, and cellulitis remains an an important global public health problem. Targeted preventive meausres should be taken in areas with different economical levels. Men, middle-aged and elderly people, and newborns are the key groups in need of attention and health education.

ObjectiveTo investigate whether there are differences in the efficacy of Gegen Qinliantang with different contents of Puerariae Lobatae Radix on the acute enteritis （AE） model mice and provide a scientific basis for the interpretation of Gegen Qinliantang in the treatment of "Xie Re Li". MethodsA total of 112 male BALB/c mice were randomly divided into a blank group，model group，single Puerariae Lobatae Radix group，non-Puerariae Lobatae Radix group，regular dose Gegen Qinliantang group （regular dose group），half-dose Puerariae Lobatae Radix group，and doubled-dose Puerariae Lobatae Radix group， with 16 mice in each group. Hematoxylin-eosin （HE） staining was used to observe the pathological changes of the colon tissue. Western blot was employed to detect the expression of ZO-1 （a protein in the tight junction） and Occludin in the colon tissue， as well as the changes of tumor necrosis factor-α （TNF-α） and interleukin-1β （IL-1β）. ResultsCompared with the blank group，the DAI scores of the mice in the model group were significantly higher （P<0.05），and the histopathological sections of their colon tissues showed mucosal damage，glandular atrophy，disordered arrangement，and a large number of inflammatory cells infiltration，and the expression of ZO-1 and Occludin proteins in their colon tissues was significantly down-regulated （P<0.05，P<0.01）. The expression of inflammatory factors TNF-α and IL-1β was significantly up-regulated （P<0.05，P<0.01）. Compared with the model group，the DAI scores of mice in all dosing groups decreased significantly （P<0.05），with the most significant effect in the regular dose group. After 7 d of drug administration，the regular dose group had the best impact on the repair of colonic mucosa in the AE mouse model. The regular dose group significantly down-regulated the expression of TNF-α （P<0.05） and significantly up-regulated the expression of ZO-1 protein （P<0.05）. The doubled-dose Puerariae Lobatae Radix group significantly down-regulated the expression of IL-1β protein （P<0.01），and there was no significant difference between all dosing groups and the model group in terms of the expression of Occludin protein. After 14 d of drug administration，the best effect on the repair of colonic mucosa in the AE mouse model was observed in the doubled dose Puerariae Lobatae Radix group. All groups except the non-Puerariae Lobatae Radix group significantly down-regulated the expression of TNF-α （P<0.01）. Meanwhile，the regular dose group and doubled-dose Puerariae Lobatae Radix group significantly elevated the expression level of Occludin protein （P<0.01）. The doubled-dose Puerariae Lobatae Radix group also significantly inhibited the expression of IL-1β protein （P<0.05） and up-regulated ZO-1 protein expression （P<0.05）. ConclusionGegen Qinliantang can reduce the pathological damage of colon tissue， protect the barrier function and structure of intestinal epithelial cells， and reduce the expression of inflammatory factors， so as to achieve the therapeutic effect of AE model mice. When comparing the therapeutic efficacy of Gegen Qinliantang containing different Gegen contents， Gegen Qinliantang with the proportion of the original formula of Zhongjing was the most effective in AE model mice.

Objective To analyze the trend of global cellulitis disease burden from 1990 to 2019, and to provide a theoretical basis for the prevention and control of cellulitis disease. Methods The Global Burden of Disease 2021 (GBD2021) data were collected, and data on the incidence, mortality, and disability-adjusted life year (DALY) of cellulitis were analyzed for each country worldwide. The estimated annual percentage change (EAPC) and age-standardized rate (ASR) were used to estimate the trend change of cellulitis from 1990 to 2021. Results The global burden of cellulitis increased significantly in 2021, with 55.96 million cases, 28.9 million deaths and 876.1 million DALYs, respectively. Incidence and mortality rates were generally higher in males than in females. The incidence and DALYs were higher in high SDI regions, with the highest burden observed in South Asia. In contrast, East Asia exhibited the lowest burden and demonstrated a declining trend. There were significant differences between countries, with India having the highest prevalence, the United States having the highest incidence, and Bahrain having the fastest growing rate.In 2021, China had the lowest age-standardised incidence of cellulitis in the world and the fastest declining age-standardised incidence and age-standardised DALYs. Conclusion The global disease burden of cellulitis is increasing from 1990-2021, and cellulitis remains an an important global public health problem. Targeted preventive meausres should be taken in areas with different economical levels. Men, middle-aged and elderly people, and newborns are the key groups in need of attention and health education.

Objective To investigate the impact of dietary protein intake on the prevalence of type 2 diabetes in adult residents, and to provide a reference for formulating diabetes prevention and control measures. Methods The research was based on cross-sectional survey data from the Nutrition and Health Follow-up Study of Chinese Residents in Chongqing (2021). Energy and nutrient intake was calculated in combination with the Chinese food composition table. Multivariate logistic regression was used to analyze the association between dietary protein and diabetes, and then restricted cubic spline regression (RCS) was used to analyze the dose-response relationship between dietary protein intake and the development of diabetes. Results Among the 1 415 adult residents, dietary intake of total protein, animal protein, and plant protein was 69.69g/d, 26.26g/d, and 43.43g/d, respectively. The ratio of protein to energy supply was 14.31%, and the prevalence of diabetes was 18.02%. Comparing with the residents in the first percentile of total dietary protein intake, the multivariable-adjusted odds ratios of those in the second and third percentile were 1.754 and 2.453 respectively. Comparing the residents in the third percentile with those in the first percentile, the multivariable-adjusted odds ratios of diabetes were 1.592 for protein energy supply ratio, and 1.558 for animal protein intake. Conclusion High protein intake, high protein energy supply ratio and high animal protein intake may increase the risk of diabetes, and different types of protein may have different effects on diabetes.

Background Fine particulate matter (PM_2.5) monitoring stations may generate missing data for a certain period of time due to various factors. This data loss will adversely affect air quality assessment and pollution control decision-making. Objective To propose an inverse distance weighted (IDW) spatiotemporal interpolation method based on particle swarm optimization (PSO) to interpolate and fill missing PM_2.5 spatiotemporal sequence data and increase interpolation accuracy. Methods An interpolation experiment was designed into two parts. The first part used hourly PM_2.5 observational data from four moments on January 1, 2017 in the Yangtze River Delta region. The second part employed daily PM_2.5 observational data from the first 10 d of January 2017 in the Beijing-Tianjin-Hebei region. Interpolation accuracy was evaluated using four metrics: root mean square error (RMSE), mean absolute error (MAE), mean absolute percentage error (MAPE), and mean relative error (MRE). Results IDW spatiotemporal interpolation method optimized with PSO significantly improved the accuracy of filling missing PM_2.5 spatiotemporal sequence data. In the hourly-scale experiment conducted in the Yangtze River Delta region, compared to a distance index of 2, the accuracy metrics RMSE, MAE, MAPE, and MRE generated by the proposed method improved on average by 0.17 μg·m⁻³, 0.27 μg·m⁻³, 0.17%, and 0.01%, respectively. The PM_2.5 spatial field maps generated for four moments based on this method clearly illustrated the spatiotemporal distribution characteristics of hourly PM_2.5 concentrations in the Yangtze River Delta region. In the daily-scale experiment conducted in the Beijing-Tianjin-Hebei region, the PSO-optimized distance index outperformed the traditional method, with interpolation accuracy improvements of approximately 0.215 μg·m⁻³, 0.283 μg·m⁻³, 0.174%, and 0.014%, respectively. Furthermore, the seasonal PM_2.5 spatial field maps generated by this method revealed the spatiotemporal distribution characteristics of PM_2.5 concentrations in the Beijing-Tianjin-Hebei region across different seasons, further validating the effectiveness and applicability of this method. Conclusion The IDW spatiotemporal interpolation method optimized with PSO is highly accurate and reliable for interpolating the missing data in the Yangtze River Delta region and the Beijing-Tianjin-Hebei region, providing valuable insights for air pollution control and public health protection.

Adipose tissue is a critical energy reservoir in animals and humans, with multifaceted roles in endocrine regulation, immune response, and providing mechanical protection. Based on anatomical location and functional characteristics, adipose tissue can be categorized into distinct types, including white adipose tissue (WAT), brown adipose tissue (BAT), beige adipose tissue, and pink adipose tissue. Traditionally, adipose tissue research has centered on its morphological and functional properties as a whole. However, with the advent of single-cell transcriptomics, a new level of complexity in adipose tissue has been unveiled, showing that even under identical conditions, cells of the same type may exhibit significant variation in morphology, structure, function, and gene expression——phenomena collectively referred to as cellular heterogeneity. Single-cell transcriptomics, including techniques like single-cell RNA sequencing (scRNA-seq) and single-nucleus RNA sequencing (snRNA-seq), enables in-depth analysis of the diversity and heterogeneity of adipocytes at the single-cell level. This high-resolution approach has not only deepened our understanding of adipocyte functionality but also facilitated the discovery of previously unidentified cell types and gene expression patterns that may play key roles in adipose tissue function. This review delves into the latest advances in the application of single-cell transcriptomics in elucidating the heterogeneity and diversity within adipose tissue, highlighting how these findings have redefined the understanding of cell subpopulations within different adipose depots. Moreover, the review explores how single-cell transcriptomic technologies have enabled the study of cellular communication pathways and differentiation trajectories among adipose cell subgroups. By mapping these interactions and differentiation processes, researchers gain insights into how distinct cellular subpopulations coordinate within adipose tissues, which is crucial for maintaining tissue homeostasis and function. Understanding these mechanisms is essential, as dysregulation in adipose cell interactions and differentiation underlies a range of metabolic disorders, including obesity and diabetes mellitus type 2. Furthermore, single-cell transcriptomics holds promising implications for identifying therapeutic targets; by pinpointing specific cell types and gene pathways involved in adipose tissue dysfunction, these technologies pave the way for developing targeted interventions aimed at modulating specific adipose subpopulations. In summary, this review provides a comprehensive analysis of the role of single-cell transcriptomic technologies in uncovering the heterogeneity and functional diversity of adipose tissues.