Objective: To review the relationship between 24 hour movement behaviors and physical and mental health among college students, in order to provide evidence to support health promotion and further research in universities. Methods: Following the Joanna Briggs Institude(JBI) scoping review guidelines, relevant studies published in databases from inception date to December 26, 2025 were searched, including PubMed, Embase, Cochrane Library, Web of Science, China National Knowledge Infrastructure (CNKI) and Wanfang Data. For studies meeting the inclusion and exclusion criteria, a descriptive analysis was conducted to summarize the measurement tools used, adherence rates with guidelines, and the relationship between physical and mental health. Results: A total of 30 studies were included. Measurement tools exhibited a high heterogeneity, with questionnaires being the primary method. The rate of full adherence with 24 hour movement behaviors among college students was less than 30%. Moderate to vigorous physical activity and high quality sleep were associated with improvements in physical fitness, cardiopulmonary function, and mental health, while prolonged sitting was negatively associated with obesity and depression. Equivalent time substitution analysis indicated that increasing moderate to vigorous physical activity and reducing prolonged sitting could significantly improve health outcomes. Conclusions The adherence rate for 24 hour movement behaviors among college students is low and it is closely associated with physical and mental health. Future studies should standardize measurement tools, and implement targeted interventions based on the optimization of daily activity patterns.

ObjectiveZheng’s San Qi San (ZSQS) power, a classic traditional Chinese medicine (TCM) formula, is used for treating soft tissue injuries involving muscles, tendons, and ligaments. However, its underlying therapeutic mechanisms remain unclear. This study aimed to screen and identify pharmaceutically active ingredients and their candidate biomolecule targets, and further elucidate the molecular mechanism of ZSQS in the treatment of skeletal muscle injury. MethodsNetwork pharmacology was employed to construct “ZSQS-component-target”, “protein-protein interaction (PPI)” and “active ingredient-core protein-pathway” networks to predict the key active ingredients and potential core targets of ZSQS for skeletal muscle injury. The predicted results were then validated via microarray data from the GEO database. Molecular docking was then performed to assess the binding ability between the screened active ingredients of ZSQS and the candidate core targets. Moreover, liquid chromatography-mass spectrometry (LC-MS) was used for qualitative and quantitative analysis to verify the active components of the drug and ZSQS serum. Finally, an animal model of eccentric exercise-induced skeletal muscle injury and a myotube cell model of oxidative stress-induced injury were established to validate the effects of ZSQS and its interventional effects on the biological functions of critical targets, thereby demonstrating the potential therapeutic mechanism of ZSQS. ResultsAmong the 111 active components identified in ZSQS and their corresponding 204 targets related to the skeletal muscle injury repair process, 14 core targets (including AKT1) and 4 core active components (quercetin, luteolin, kaempferol, and β‑sitosterol) were screened out, while the corresponding metabolites of quercetin, luteolin and kaempferol were detected in the ZSQS serum. Among these targets, 5 candidate genes (IL-6, CASP3, HIF1A, STAT3, and JUN) overlapped with the differential expression screening results with GEO data, and IL-6 was confirmed to be enriched in the PI3K/AKT pathway. Combined with the prediction results of the AKT expression levels, these findings suggest that the phosphorylation level of AKT1 plays a core role in the therapeutic mechanism of ZSQS. Molecular docking analysis further revealed that the PH domain of AKT1 had high binding energy with all 4 core active components, as verified by LC-MS. Finally, animal model studies have shown the promoting effect of ZSQS administration on skeletal muscle injury repair and its possible antioxidant damage mechanism. Cell model studies further demonstrated that ZSQS-containing serum, core active ingredient combination therapy, and quercetin monomer could increase the phosphorylation level of AKT, promote the nuclear translocation of Nrf2, upregulate the expression of downstream antioxidant enzymes (SOD, GPx, and GR), and inhibit the expression of inflammatory factors (IL-6 and TNF-α), thereby alleviating oxidative stress and the inflammatory response. ConclusionZSQS alleviates skeletal muscle injury mainly by activating the AKT/Nrf2 signaling pathway, enhancing cellular antioxidant and anti-inflammatory capabilities. The results of this study provide a scientific basis for the clinical application and modernized development of ZSQS.

Renal lymphatic vessel density is clinically relevant in kidney disease but is still assessed by slow, subjective visual estimation. We evaluated a weakly supervised, attention-based multiple-instance learning framework for automated detection and quantification of renal lymphatic vessel density on D2-40-stained whole-slide images (WSIs). Methods: Two independent internal datasets from Tongji Hospital were collected, including 198 cases of chronic kidney disease (CKD) and 50 cases of hypertensive nephropathy (HTN). All biopsies were immunohistochemically stained for D2-40 and digitized as WSIs. Pathologists provided only slide-level labels (D2-40 high vs. D2-40 low). Tissue regions were automatically segmented, tiled into patches, and encoded using a pretrained convolutional neural network. Patch embeddings were then analyzed with a clustering-constrained attention multiple-instance learning (CLAM) model. Unlike conventional multiple-instance learning (MIL) methods that only weight instances, CLAM jointly performs attention-based instance selection and instance-level clustering to distinguish positive from negative evidence within each slide, yielding more discriminative slide-level features and interpretable attention maps. Performance was compared with a classic MIL model trained on the same features. Results: CLAM achieved area under the receiver operating characteristic curves of 0.942 and 0.858 on the CKD and HTN datasets, respectively, outperforming classic MIL (0.866 and 0.801). Attention maps highlighted lymphatic-rich regions consistent with renal pathologists’ assessments. Conclusions: This clustering-constrained, attention-based weakly supervised framework enables fully automated, reproducible quantification of renal lymphatic vessel density from WSIs, providing renal pathologists with rapid visual and numerical support for diagnosis and risk stratification in CKD and HTN.

Metabolic-associated fatty liver disease (MAFLD) and osteoporosis (OP) are two very common metabolic diseases. A growing body of experimental evidence supports a pathophysiological link between MAFLD and OP. MAFLD is often associated with the development of OP. Rutaecarpine (RUT) is one of the main active components of Chinese medicine Euodiae Fructus. Our previous studies have demonstrated that RUT has lipid-lowering, anti-inflammatory and anti-atherosclerotic effects, and can improve the OP of rats. However, whether RUT can improve both fatty liver and OP symptoms of MAFLD mice at the same time remains to be investigated. In this study, we used C57BL/6 mice fed a high-fat diet (HFD) for 4 months to construct a MAFLD model, and gave the mice a low dose (5 mg·kg^-1) and a high dose (15 mg·kg^-1) of RUT by gavage for 4 weeks. The effects of RUT on liver steatosis and bone metabolism were then evaluated at the end of the experiment [this experiment was approved by the Experimental Animal Ethics Committee of Institute of Medicinal Biotechnology, Chinese Academy of Medical Sciences (approval number: IMB-20190124D₃03)]. The results showed that RUT treatment significantly reduced hepatic steatosis and lipid accumulation, and significantly reduced bone loss and promoted bone formation. In summary, this study shows that RUT has an effect of improving fatty liver and OP in MAFLD mice.

ObjectiveTo investigate the influence of histone deacetylase 3 (HDAC3) on the occurrence, development of psoriasis-like inflammation in mice, and the relative immune mechanisms. MethodsHealthy C57BL/6 mice aged 6-8 weeks were selected and randomly divided into 3 groups: control group (Control), psoriasis model group (IMQ), and HDAC3 inhibitor RGFP966-treated psoriasis model group (IMQ+RGFP966). One day prior to the experiment, the back hair of the mice was shaved. After a one-day stabilization period, the mice in Control group was treated with an equal amount of vaseline, while the mice in IMQ group was treated with imiquimod (62.5 mg/d) applied topically on the back to establish a psoriasis-like inflammation model. The mice in IMQ+RGFP966 group received intervention with a high dose of the HDAC3-selective inhibitor RGFP966 (30 mg/kg) based on the psoriasis-like model. All groups were treated continuously for 5 d, during which psoriasis-like inflammation symptoms (scaling, erythema, skin thickness), body weight, and mental status were observed and recorded, with photographs taken for documentation. After euthanasia, hematoxylin-eosin (HE) staining was used to assess the effect of RGFP966 on the skin tissue structure of the mice, and skin thickness was measured. The mRNA and protein expression levels of HDAC3 in skin tissues were detected using reverse transcription real-time quantitative polymerase chain reaction (RT-qPCR) and Western blot (WB), respectively. Flow cytometry was employed to analyze neutrophils in peripheral blood and lymph nodes, CD4⁺ T lymphocytes, CD8⁺ T lymphocytes in peripheral blood, and IL-17A secretion by peripheral blood CD4⁺ T lymphocytes. Additionally, spleen CD4⁺ T lymphocyte expression of HDAC3, CCR6, CCR8, and IL-17A secretion levels were analyzed. Immunohistochemistry was used to detect the localization and expression levels of HDAC3, IL-17A, and IL-10 in skin tissues. ResultsCompared with the Control group, the IMQ group exhibited significant psoriasis-like inflammation, characterized by erythema, scaling, and skin wrinkling. Compared with the IMQ group, RGFP966 exacerbated psoriasis-like inflammatory symptoms, leading to increased hyperkeratosis. The psoriasis area and severity index (PASI) skin symptom scores were higher in the IMQ group than those in the Control group, and the scores were further elevated in the IMQ+RGFP966 group compared to the IMQ group. Skin thickness measurements showed a trend of IMQ+RGFP966>IMQ>Control. The numbers of neutrophils in the blood and lymph nodes increased sequentially in the Control, IMQ, and IMQ+RGFP966 groups, with a similar trend observed for CD4⁺ and CD8⁺ T lymphocytes in the blood. In skin tissues, compared with the Control group, the mRNA and protein levels of HDAC3 decreased in the IMQ group, but RGFP966 did not further reduce these expressions. HDAC3 was primarily located in the nucleus. Compared with the Control group, the nuclear HDAC3 content decreased in the skin tissues of the IMQ group, and RGFP966 further reduced nuclear HDAC3. Compared with the Control and IMQ groups, RGFP966 treatment decreased HDAC3 expression in splenic CD4⁺ and CD8⁺ T cells. RGFP966 treatment increased the expression of CCR6 and CCR8 in splenic CD4⁺ T cells and enhanced IL-17A secretion by peripheral blood and splenic CD4⁺ T lymphocytes. Additionally, compared with the IMQ group, RGFP966 reduced IL-10 protein levels and upregulated IL-17A expression in skin tissues. ConclusionRGFP966 exacerbates psoriatic-like inflammatory responses by inhibiting HDAC3, increasing the secretion of the cytokine IL-17A, and upregulating the expression of chemokines CCR8 and CCR6.

Electroencephalogram (EEG) is a non-invasive, high temporal-resolution technique for monitoring brain activity. However, affected by the volume conduction effect, EEG has a low spatial resolution and is difficult to locate brain neuronal activity precisely. The surface Laplacian (SL) technique obtains the Laplacian EEG (LEEG) by estimating the second-order spatial derivative of the scalp potential. LEEG can reflect the radial current activity under the scalp, with positive values indicating current flow from the brain to the scalp (“source”) and negative values indicating current flow from the scalp to the brain (“sink”). It attenuates signals from volume conduction, effectively improving the spatial resolution of EEG, and is expected to contribute to breakthroughs in neural engineering. This paper provides a systematic overview of the principles and development of SL technology. Currently, there are two implementation paths for SL technology: current source density algorithms (CSD) and concentric ring electrodes (CRE). CSD performs the Laplace transform of the EEG signals acquired by conventional disc electrodes to indirectly estimate the LEEG. It can be mainly classified into local methods, global methods, and realistic Laplacian methods. The global method is the most commonly used approach in CSD, which can achieve more accurate estimation compared with the local method, and it does not require additional imaging equipment compared with the realistic Laplacian method. CRE employs new concentric ring electrodes instead of the traditional disc electrodes, and measures the LEEG directly by differential acquisition of the multi-ring signals. Depending on the structure, it can be divided into bipolar CRE, quasi-bipolar CRE, tripolar CRE, and multi-pole CRE. The tripolar CRE is widely used due to its optimal detection performance. While ensuring the quality of signal acquisition, the complexity of its preamplifier is relatively acceptable. Here, this paper introduces the study of the SL technique in resting rhythms, visual-related potentials, movement-related potentials, and sensorimotor rhythms. These studies demonstrate that SL technology can improve signal quality and enhance signal characteristics, confirming its potential applications in neuroscientific research, disease diagnosis, visual pathway detection, and brain-computer interfaces. CSD is frequently utilized in applications such as neuroscientific research and disease detection, where high-precision estimation of LEEG is required. And CRE tends to be used in brain-computer interfaces, that have stringent requirements for real-time data processing. Finally, this paper summarizes the strengths and weaknesses of SL technology and envisages its future development. SL technology boasts advantages such as reference independence, high spatial resolution, high temporal resolution, enhanced source connectivity analysis, and noise suppression. However, it also has shortcomings that can be further improved. Theoretically, simulation experiments should be conducted to investigate the theoretical characteristics of SL technology. For CSD methods, the algorithm needs to be optimized to improve the precision of LEEG estimation, reduce dependence on the number of channels, and decrease computational complexity and time consumption. For CRE methods, the electrodes need to be designed with appropriate structures and sizes, and the low-noise, high common-mode rejection ratio preamplifier should be developed. We hope that this paper can promote the in-depth research and wide application of SL technology.

Objective To analyze the prevalence status of cardiometabolic risk factor (CMRF) and its aggregation among workers engaged in new forms of employment. Methods A total of 5 429 new employment workers (including couriers, online food delivery workers, and ride hailing drivers) who underwent health medical examinations at a tertiary hospital in Beijing City were selected as the research subjects using the judgment sampling method. Data on waist circumference, blood pressure, blood glucose, and blood lipid levels were collected to analyze their CMRF [central obesity, elevated blood pressure, elevated blood glucose, elevated triglycerides, and reduced high-density lipoprotein cholesterol (HDL-C)] and their aggregation (with ≥ 2 of the above 5 risk factors) status. Results The detection rates of central obesity, elevated blood pressure, elevated blood glucose, elevated triglycerides, and reduced HDL-C were 61.2%, 38.2%, 29.5%, 40.9% and 22.6%, respectively. The detection rates of CMRF aggregation was 57.8%. The result of multivariable logistic regression analysis showed that male, age ≥45 years, smoking, overweight, and obesity were risk factors for CMRF aggregation (all P<0.05). Conclusion The detection rate of CMRF and its aggregation among workers with new forms of employment in Beijing City is relatively high. Targeted prevention and control efforts should be strengthened for high-risk populations, especially males, workers aged ≥45 years, smokers, and those who are overweight or obese.

Objective To investigate the factors associated with unplanned readmission within 30 days after discharge in adult patients who underwent coronary artery bypass grafting (CABG) and to develop and validate a risk prediction model. Methods A retrospective analysis was conducted on the clinical data of patients who underwent isolated CABG at the Nanjing First Hospital between January 2020 and June 2024. Data from January 2020 to August 2023 were used as a training set, and data from September 2023 to June 2024 were used as a validation set. In the training set, patients were divided into a readmission group and a non-readmission group based on whether they had unplanned readmission within 30 days post-discharge. Clinical data between the two groups were compared, and logistic regression was performed to identify independent risk factors for unplanned readmission. A risk prediction model and a nomogram were constructed, and internal validation was performed to assess the model’s performance. The validation set was used for validation. Results A total of 2 460 patients were included, comprising 1 787 males and 673 females, with a median age of 70 (34, 89) years. The training set included 1 932 patients, and the validation set included 528 patients. In the training set, there were statistically significant differences between the readmission group (79 patients) and the non-readmission group (1 853 patients) in terms of gender, age, carotid artery stenosis, history of myocardial infarction, preoperative anemia, and heart failure classification (P<0.05). The main causes of readmission were poor wound healing, postoperative pulmonary infections, and new-onset atrial fibrillation. Multivariable logistic regression analysis revealed that females [OR=1.659, 95%CI (1.022, 2.692), P=0.041], age [OR=1.042, 95%CI (1.011, 1.075), P=0.008], carotid artery stenosis [OR=1.680, 95%CI (1.130, 2.496), P=0.010], duration of first ICU stay [OR=1.359, 95%CI (1.195, 1.545), P<0.001], and the second ICU admission [OR=4.142, 95%CI (1.507, 11.383), P=0.006] were independent risk factors for unplanned readmission. In the internal validation, the area under the curve (AUC) was 0.806, and the net benefit rate of the clinical decision curve analysis (DCA) was >3%. In the validation set, the AUC was 0.732, and the DCA net benefit rate ranged from 3% to 48%. Conclusion Females, age, carotid artery stenosis, duration of first ICU stay, and second ICU admission are independent risk factors for unplanned readmission within 30 days after isolated CABG. The constructed nomogram demonstrates good predictive power.

Objective To observe the value of MRI quantified uterine indictors in late pregnancy for predicting uterine inertia in delivery.Methods A total of 182 pregnant women were retrospectively collected and were divided into uterine inertia group(inertia group,n=67)and non-uterine inertia group(non-inertia group,n=115)based on delivery or cesarean section records.MRI quantified uterine indicators were compared between groups,and those being statistically different were included to build a multivariate logistic regression model for predicting uterine inertia in delivery.The predictive performance of this model was evaluated using receiver operating characteristic(ROC)curve and the area under the curve(AUC).Results The inertia group had more previous uterine surgeries,also higher proportion of in vitro fertilization and embryo transfer(IVF-ET)and cesarean sections compared to the non-inertia group(all P＜0.05).In late pregnancy,the longitudinal diameter of the uterus,cervical length and the thickness of the myometrium at the placental attachment site in inertia group were larger than those in non-inertia group(all P＜0.05).Increased times of previous uterine surgeries,undergoing IVF-ET,as well as increased longitudinal diameter of the uterus and cervical length in late pregnancy were all independent predictors of uterine inertia in delivery(all P＜0.05).AUC of the multivariate logistic regression model established based on the above factors for predicting uterine inertia in delivery was 0.733.Conclusion MRI quantified uterine indictors in late pregnancy could be used to predict uterine inertia in delivery.

Objective To investigate the status quo,driving factors and clinical intervention measures of intrinsic capacity(IC)in elderly patients with cerebrovascular disease.Methods Clinical data of 206 elderly patients with cerebrovascular disease admitted to our hospital from January to December 2024 were retrospectively collected.According to the IC score,they were divided into a low IC group(123 cases,IC score＜4)and a good IC group(83 cases,IC score≥4).The IC scores were compared between the two groups,and the driving factors affecting the IC were analyzed.Results The low IC group exhibited significantly lower IC score than the good IC group(1.94±0.49 vs 4.52±0.15,P＜0.01).The age ≥80 years,dysfunctions,three or more chronic diseases,frailty,albumin ≤ 35 g/L,pre-albumin ≤280 mg/L,rehabilitation guidance and regular exercises were the influencing factors of IC in elderly patients with cerebrovascular disease(P＜0.05,P＜0.01).Conclusion The IC of elderly patients with cerebrovascular disease is associated with many factors,and corresponding clinical intervention measures should be implemented to promote the improvement of patient's IC.