Objective: To explore the isotemporal substitution effects among different intensities of physical activity within a 10 minute recess period on the mental health of junior high school students, aiming to provide evidence based references for targeted practical interventions. Methods: From May to November 2024, a total of 845 junior high school students from Tianjin,Taiyuan and L Liang in Shaanxi Province,Puyang in Henan Province,Xi an in Shaanxi Province,Quzhou in Zhejiang Province,and Chaoyang in Liaoning Province were selected by using a combination of stratified random sampling and convenience sampling. ActiGraph wGT3X-BT accelerometers was used to measure physical activity during a 10 minute recess period. Mental health status was assessed with the Depression Anxiety Stress Scale (DASS-21). An isotemporal substitution model was constructed in 1 minute increments to predict the effects of substituting different physical activity behaviors on students mental health. Results: During recess, sedentary behavior (SB) was predominant among junior high school students, with an average duration of [7.08(5.85,7.98)] minutes, while moderate to vigorous physical activity (MVPA) accounted for the shortest duration at [0.42(0.21,0.85)] minutes. There were statistically significant differences in MVPA,LPA and SB time between students of different genders and grades( Z/H =-9.08,-8.34,-9.51;84.87,126.82,135.27,all P <0.01). Isotemporal substitution analysis, adjusted for gender and age, showed that replacing 1 minute of SB with 1 minute of MVPA significantly improved anxiety levels ( β =-0.29, 95% CI =-0.53 to -0.04) and overall mental health ( β =-0.72, 95% CI =-1.39 to -0.04), with both results reaching statistical significance (both P <0.05). No significant effects were observed for other substitution patterns (both P >0.05). Conclusions Substituting SB with MVPA during a 10 minute recess period exerts a positive impact on the mental health of junior high school students. It is recommended to optimize the daily recess activity structure in schools to enhance students mental well being.

Objective: To explore the association between mental health and muscle strength among Chinese adolescents aged 13- 18, providing a theoretical foundation and intervention strategies for mental health promotion. Methods: Data were obtained from the 2019 Chinese National Survey on Students Constitution and Health, including 98 631 Chinese adolescents aged 13- 18. Psychological distress was assessed by using the Kessler Psychological Distress Scale (K10), and mental well being was measured with the Warwick-Edinburgh Mental Well being Scale (WEMWBS). Based on the gender and age specific Z scores of various test items [grip strength, standing long jump, pull ups (for males), and sit ups (for females)], muscle strength index (MSI) was constructed to evaluate the comprehensive level of muscle strength in adolescents. According to the Dual factor Model (DFM) of mental health, participants were categorized into four groups:troubled, symptomatic but content, vulnerable, and complete mental health. Gender differences were analyzed by using Chi-square tests, trends were tested with Cochran-Armitage tests, and multinomial Logistic regression models were applied to assess associations between muscle strength and mental health among adolescents. Results: In 2019, 37.4% of Chinese adolescents aged 13-18 were reported of high mental distress, and 59.9% were reported of low mental well being. Boys had significantly lower rates of high mental distress (35.3%) and low mental well being (55.6%) compared to girls (39.4%, 64.3%), and the differences were of statistical significance ( χ 2=176.13, 780.42, both P <0.05). In 2019, the rate of complete mental health among adolescents showed a downward trend with increasing age ( χ 2 trend = 258.47) and a gradual upward trend with increasing muscle strength levels ( χ 2 trend =123.14)，and both boys and girls exhibited similar trends ( χ 2 trend =103.83, 168.46; 57.00 , 67.34) (all P <0.05). The results of the unordered multiclass Logistic regression model showed that after controlling for confounding factors such as age and gender, when the completely pathological group as a reference, for every 1 unit increase in MSI in adolescents, the likelihood of being in a completely mental health state increased by 29% ( OR = 1.29); for every unit increase in the Z-score for pull ups, the likelihood of being in a completely mental health state increased by 6% ( OR =1.06) among boys; for every 1 unit increase in sit up Z score, the likelihood of being in a completely mental health state increased by 19% ( OR =1.19) among girls (all P <0.05). Conclusions The mental health status of Chinese adolescents is not good enough. Muscle strength is positively associated with mental health.

The general models for intermediates quality analysis in the production process of Yaobitong capsule were established by near infrared spectroscopy (NIRS) combined with chemometrics, realizing the rapid determination of notoginsenoside R1, ginsenoside Rg1, ginsenoside Re, ginsenoside Rb1, ginsenoside Rd and moisture. The spray-dried fine powder and total mixed granule were selected as research objects. The contents of five saponins were determined by high performance liquid chromatography and the moisture content was determined by drying method. The measured contents were used as reference values. Meanwhile, NIR spectra were collected. After removing abnormal samples by Monte Carlo cross validation (MCCV), Monte Carlo uninformative variables elimination (MC-UVE) and competitive adaptive reweighted sampling (CARS) were used to select feature variables respectively. Based on the feature variables, quantitative models were established by partial least squares regression (PLSR), extreme learning machine (ELM) and ant lion optimization least squares support vector machine (ALO-LSSVM). The results showed that CARS-ALO-LSSVM model had the optimum effect. The correlation coefficients of the six index components were greater than 0.93, and the relative standard errors were controlled within 6%. ALO-LSSVM was more suitable for a large number of samples with rich information, and the prediction effect and stability of the model were significantly improved. The general models with good predicting effect can be used for the rapid quality determination of Yaobitong capsule intermediates.

Cardiovascular disease (CVD), chronic kidney disease (CKD), and metabolic disorders are the 3 major chronic diseases threatening human health, which are closely related and often coexist, significantly increasing the difficulty of disease management. In response, the American Heart Association (AHA) proposed a novel disease concept of “cardiovascular-kidney-metabolic (CKM) syndrome” in October 2023, which has triggered widespread concern about the co-treatment of heart and kidney diseases and the prevention and treatment of metabolic disorders around the world. This review posits that effectively managing CKM syndrome requires a new and multidimensional paradigm for diagnosis and risk prediction that integrates biological insights, advanced technology and social determinants of health (SDoH). We argue that the core pathological driver is a “metabolic toxic environment”, fueled by adipose tissue dysfunction and characterized by a vicious cycle of systemic inflammation and oxidative stress, which forms a common pathway to multi-organ injury. The at-risk population is defined not only by biological characteristics but also significantly impacted by adverse SDoH, which can elevate the risk of advanced CKM by a factor of 1.18 to 3.50, underscoring the critical need for equity in screening and care strategies. This review systematically charts the progression of diagnostic technologies. In diagnostics, we highlight a crucial shift from single-marker assessments to comprehensive multi-marker panels. The synergistic application of traditional biomarkers like NT-proBNP (reflecting cardiac stress) and UACR (indicating kidney damage) with emerging indicators such as systemic immune-inflammation index (SII) and Klotho protein facilitates a holistic evaluation of multi-organ health. Furthermore, this paper explores the pivotal role of non-invasive monitoring technologies in detecting subclinical disease. Techniques like multi-wavelength photoplethysmography (PPG) and impedance cardiography (ICG) provide a real-time window into microcirculatory and hemodynamic status, enabling the identification of early, often asymptomatic, functional abnormalities that precede overt organ failure. In imaging, progress is marked by a move towards precise, quantitative evaluation, exemplified by artificial intelligence-powered quantitative computed tomography (AI-QCT). By integrating AI-QCT with clinical risk factors, the predictive accuracy for cardiovascular events within 6 months significantly improves, with the area under the curve (AUC) increasing from 0.637 to 0.688, demonstrating its potential for reclassifying risk in CKM stage 3. In the domain of risk prediction, we trace the evolution from traditional statistical tools to next-generation models. The new PREVENT equation represents a major advancement by incorporating key kidney function markers (eGFR, UACR), which can enhance the detection rate of CKD in primary care by 20%-30%. However, we contend that the future lies in dynamic, machine learning-based models. Algorithms such as XGBoost have achieved an AUC of 0.82 for predicting 365-day cardiovascular events, while deep learning models like KFDeep have demonstrated exceptional performance in predicting kidney failure risk with an AUC of 0.946. Unlike static calculators, these AI-driven tools can process complex, multimodal data and continuously update risk profiles, paving the way for truly personalized and proactive medicine. In conclusion, this review advocates for a paradigm shift toward a holistic and technologically advanced framework for CKM management. Future efforts must focus on the deep integration of multimodal data, the development of novel AI-driven biomarkers, the implementation of refined SDoH-informed interventions, and the promotion of interdisciplinary collaboration to construct an efficient, equitable, and effective system for CKM screening and intervention.

OBJECTIVE: To determine whether monotropein has an anticancer effect and explore its potential mechanisms against colorectal cancer (CRC) through network pharmacology and molecular docking combined with experimental verification. METHODS: Network pharmacology and molecular docking were used to predict potential targets of monotropein against CRC. Cell counting kit assay, plate monoclonal assay and microscopic observation were used to investigate the antiproliferative effects of monotropein on CRC cells HCT116, HT29 and LoVo. Flow cytometry and scratch assay were used to analyze apoptosis and cell cycle, as well as cell migration, respectively in HCT116, HT29, and LoVo cells. Western blotting was used to detect the expression of proteins related to apoptosis, cell cycle, and cell migration, and the expression of proteins key to the Akt pathway. RESULTS: The Gene Ontology and Reactome enrichment analyses indicated that the anticancer potential of monotropein against CRC might be involved in multiple cancer-related signaling pathways. Among these pathways, RAC-beta serine/threonine-protein kinase (Akt1, Akt2), cyclin-dependent kinase 6 (CDK6), matrix metalloproteinase-9 (MMP9), epidermal growth factor receptor (EGFR), cell division control protein 42 homolog (CDC42) were shown as the potential anticancer targets of monotropein against CRC. Molecular docking suggested that monotropein may interact with the 6 targets (Akt1, Akt2, CDK6, MMP9, EGFR, CDC42). Subsequently, cell activity of HCT116, HT29 and LoVo cell lines were significantly suppressed by monotropein (P<0.05). Furthermore, our research revealed that monotropein induced cell apoptosis by inhibiting Bcl-2 and increasing Bax, induced G₁-S cycle arrest in colorectal cancer by decreasing the expressions of CyclinD1, CDK4 and CDK6, inhibited cell migration by suppressing the expressions of CDC42 and MMP9 (P<0.05), and might play an anticancer role through Akt signaling pathway. CONCLUSION Monotropein exerts its antitumor effects primarily by arresting the cell cycle, causing cell apoptosis, and inhibiting cell migration. This indicates a high potential for developing novel medication for treating CRC.
Humans ; Proto-Oncogene Proteins c-akt/metabolism* ; Cell Proliferation ; Matrix Metalloproteinase 9 ; Molecular Docking Simulation ; Cell Cycle ; ErbB Receptors ; Apoptosis ; Colorectal Neoplasms/pathology* ; Cell Line, Tumor

Astrocytes are the largest glial population in the mammalian brain. However, we have a minimal understanding of astrocyte development, especially fate specification in different regions of the brain. Through lineage tracing of the progenitors of the third ventricle (3V) wall via in-utero electroporation in the embryonic mouse brain, we show the fate specification and migration pattern of astrocytes derived from radial glia along the 3V wall. Unexpectedly, radial glia located in different regions along the 3V wall of the diencephalon produce distinct cell types: radial glia in the upper region produce astrocytes and those in the lower region produce neurons in the diencephalon. With genetic fate mapping analysis, we reveal that the first population of astrocytes appears along the zona incerta in the diencephalon. Astrogenesis occurs at an early time point in the dorsal region relative to that in the ventral region of the developing diencephalon. With transcriptomic analysis of the region-specific 3V wall and lateral ventricle (LV) wall, we identified cohorts of differentially-expressed genes in the dorsal 3V wall compared to the ventral 3V wall and LV wall that may regulate astrogenesis in the dorsal diencephalon. Together, these results demonstrate that the generation of astrocytes shows a spatiotemporal pattern in the developing mouse diencephalon.
Mice ; Animals ; Astrocytes ; Neuroglia/physiology* ; Diencephalon ; Brain ; Neurons ; Mammals

Objective: The association between school bullying and attention deficit hyperactivity disorder (ADHD) symptoms among students in primary schools and the moderating role of gender was explored to provide scientific evidence for the prevention and control of school bullying. Methods: A total of 4 764 students from 2 primary schools in Wuhan were selected using the convenience sampling method in March 2023. The Olweus Bully/Victim Questionnaire and Strengths and Difficulties Questionnaire were used. A Pearson χ 2 test was used to compare differences in school bullying rates among children with and without ADHD symptoms. Pearson correlation analysis and Process 3.3 were used to analyse the association between ADHD symptoms, and school bullying behaviour and the moderating role of gender. Results: The reported rate of bullying victims in primary schools was 24.2% and the rate of bullying perpetration was 3.8%. The rate of ADHD symptom detection among primary school students was 5.9%. ADHD symptoms were positively associated with bullying and bullying victim behaviour ( r =0.16, 0.27, P <0.01). Specifically, the association between ADHD symptoms and bullying behavior tended to be stronger among boys than girls ( β boy =0.17, t =11.13; β girl =0.07, t =4.11, P <0.01). Conclusions ADHD symptoms are an important factor influencing school bullying behaviors in students, and gender moderates the association. In the process of preventing and controlling school bullying, ADHD symptoms and gender differences should be emphasized and comprehensive interventions should be implemented.