1.Research progress on the association between physical activity and sleep quality in adolescents
WANG Jinxian*, LIU Yuan, WU Jian, WU Huipan, WANG Zhe, ZHANG Yingkun, WANG Yi, YIN Xiaojian
Chinese Journal of School Health 2026;47(1):140-143
Abstract
To promote adolescents active participation in physical activity and improve sleep quality, the article analyzes the relationship of adolescent physical activity with subjective sleep satisfaction, sleep latency, sleep continuity, sleep efficiency, and sleep duration. It explores potential mechanisms underlying the link between physical activity and sleep quality, including physiological mechanisms (circadian rhythms, body temperature, neuroendocrine systems, and immune function), and psychological mechanisms (stress relief, improvement of negative emotions, and promotion of mental relaxation). Based on existing research, it is recommended that adolescents engage in moderate to vigorous physical activity daily to promote improved sleep quality.
2.Explainable Machine Learning Model for Predicting Prognosis in Patients with Malignant Tumors Complicated by Acute Respiratory Failure: Based on the eICU Collaborative Research Database in the United States
Zihan NAN ; Linan HAN ; Suwei LI ; Ziyi ZHU ; Qinqin ZHU ; Yan DUAN ; Xiaoting WANG ; Lixia LIU
Medical Journal of Peking Union Medical College Hospital 2026;17(1):98-108
To develop and validate a model for predicting intensive care unit (ICU) mortality risk in patients with malignant tumors complicated by acute respiratory failure (ARF) based on an explainable machine learning framework. Clinical data of patients with malignant tumors and ARF were extracted from the eICU Collaborative Research Database in the United States, including demographic characteristics, comorbidities, vital signs, laboratory test indicators, and major interventions within the first 24 hours after ICU admission.The study outcome was ICU death.Enrolled patients were randomly divided into a training set and a validation set at a ratio of 7:3.Predictor variables were selected using least absolute shrinkage and selection operator (LASSO) regression.Five machine learning algorithms-extreme gradient boosting (XGBoost), support vector machine (SVM), Logistic regression, multilayer perceptron (MLP), and C5.0 Decision Tree-were employed to construct predictive models.Model performance was evaluated based on the area under the receiver operating characteristic curve (AUC), accuracy, sensitivity, and other metrics.The optimal model was further interpreted using the Shapley additive explanations (SHAP) algorithm. A total of 3196 patients with malignant tumors complicated by ARF were included.The training set comprised 2, 261 patients and the validation set 935 patients; 683 patients died during ICU stay, while 2513 survived.LASSO regression ultimately selected 12 variables closely associated with patient ICU outcomes, including sepsis comorbidity, use of vasoactive drugs, and within the first 24 hours after ICU admission: minimum mean arterial pressure, maximum heart rate, maximum respiratory rate, minimum oxygen saturation, minimum serum bicarbonate, minimum blood urea nitrogen, maximum white blood cell count, maximum mean corpuscular volume, maximum serum potassium, and maximum blood glucose.After model evaluation, the XGBoost model demonstrated the best performance.The AUCs for predicting ICU mortality risk in the training and validation sets were 0.940 and 0.763, respectively; accuracy was 88.3% and 81.2%;sensitivity was 98.5% and 95.9%.Its predictive performance also remained optimal in sensitivity analyses.SHAP analysis indicated that the top five variables contributing to the model's predictions were minimum oxygen saturation, minimum serum bicarbonate, minimum mean arterial pressure, use of vasoactive drugs, and maximum white blood cell count. This study successfully developed a mortality risk prediction model for ICU patients with malignant tumors complicated by ARF based on a large-scale dataset and performed explainability analysis.The model aids clinicians in early identification of high-risk patients and implementing individualized interventions.
3.Predictive modle for violence risk in hospitalized schizophrenia patients based on support vector machine
Huan LIU ; Peifang SHI ; Kun ZHANG ; Li KANG ; Yan ZHANG ; Long NA ; Binhong WANG ; Meiqing HE
Sichuan Mental Health 2026;39(1):27-35
BackgroundThe violent aggressive behaviors of patients with schizophrenia usually have the characteristics of suddenness, unpredictability, high severity, and great difficulty in prevention. Early identification and accurate assessment of their risk of violent aggression have significant clinical significance. ObjectiveTo construct a predictive model for the violence risk in hospitalized patients with schizophrenia, to identify the key factors influencing the occurrence of violent behavior in these patients, so as to provide references for clinical precise quantitative assessment and early intervention. MethodsA total of 200 patients with schizophrenia who were hospitalized at Taiyuan Psychiatric Hospital from March 2022 to September 2024 and met the diagnostic criteria of the International Classification of Diseases, eleventh edition (ICD-11) were collected to form the modeling cohort. They were randomly divided into a training set (n=140) and a test set (n=60) at a ratio of 7∶3. Based on the least absolute shrinkage and selection operator (LASSO) regression algorithm, the feature variables were screened and dimension-reduced. The support vector machine (SVM) from machine learning was selected for model training and prediction. The discrimination efficacy of the model was evaluated by the area under the receiver operating characteristic (ROC) curve (AUC), accuracy, precision, sensitivity, specificity, F1 value, and Brier value. ResultsLASSO regression screening identified 16 feature variables. Pearson correlation analysis revealed a positive correlation between prior violent behavior frequency and clinical psychiatric symptom scores (r=0.580, P<0.01), a positive correlation between hospitalization compliance and current disease status (r=0.550, P=0.003), and a positive correlation between educational level and family per capita monthly income (r=0.367, P<0.01). The SVM model achieved an AUC of 0.853, accuracy of 0.800, precision of 0.810, sensitivity of 0.895, specificity of 0.636, F1 value of 0.850, and Brier value of 0.168. ConclusionThe SVM model has a relatively high level of applicability and overall predictive performance in the assessment of violent risk in schizophrenia patients, which is helpful for the early identification of violent risks in such patients. [Funded by Specialized Research Project for Enhancing the Competence of Health Professionals in Taiyuan City (number, Y2023006)]
4.Association between sleep quality and mental health among middle school students
WU Huipan, LIU Yuan, YIN Xiaojian, WANG Jinxian, WANG Yi, GUO Yaru, XU Dingkun
Chinese Journal of School Health 2025;46(6):770-773
Objective:
To explore the relationship between sleep quality and mental health among middle school students, so as to provide scientific basis for improving mental health among adolescents.
Methods:
From September to December 2023, a stratified cluster random sampling method was employed to select 5 713 middle school students aged 13-18 from Shanghai, Suzhou, Taiyuan, Wuyuan, Xingyi, and Urumqi. Sleep quality and mental health were assessed using the Pittsburgh Sleep Quality Index (PSQI) and the Brief Adolescent Mental Health Assessment Questionnaire. Spearman correlation analysis and linear regression analysis were used to explore the relationship between sleep quality and various dimensions of mental health among middle school students.
Results:
There was a statistically significant difference in the total PSQI score among middle school students of different age groups ( H=226.49, P <0.01), and there was no statistically significant difference in the psychological health scores of middle school students in different age groups ( H=5.37, P >0.05). In terms of gender, the total PSQI score for girls [5.00 (3.00, 6.00)] was higher than that for boys [4.00 (2.00, 6.00)]; additionally, boys had higher mental health scores [85.00 (75.00, 90.00)] than females [83.00 (70.00, 89.00)], with statistically significant differences ( Z=-10.90, -8.16, P <0.01). Spearman correlation analysis revealed a negative correlation between total PSQI scores and mental health scores ( r=-0.51, P <0.05) among middle school students. After controlling for variables such as maximum oxygen uptake, physical activity and nutritional status, linear regression analysis further confirmed that higher PSQI scores were associated with lower mental health scores ( B=-3.76, 95%CI = -4.15 to -3.38, P <0.01).
Conclusion
There is a negative correlation between PSQI scores and mental health scores among middle school students, indicating that improving sleep quality may contribute to better mental health among middle school students.
5.Antidepressant effects of Ziziphi Spinosae Semen extract on depressive-like behaviors in sleep deprivation rats based on integrated serum metabolomics and gut microbiota.
Liang-Lei SONG ; Ya-Yu SUN ; Ze-Jia NIU ; Jia-Ying LIU ; Xiang-Ping PEI ; Yan YAN ; Chen-Hui DU
China Journal of Chinese Materia Medica 2025;50(16):4510-4524
Based on serum metabolomics and gut microbiota technology, this study explores the effects and mechanisms of the water extract of Ziziphi Spinosae Semen(SZRW) and the petroleum ether extract of Ziziphi Spinosae Semen(SZRO) in improving depressive-like behaviors induced by sleep deprivation. A modified multi-platform water environment method was employed to establish a rat model of sleep deprivation. Depressive-like behaviors in rats were assessed through the sucrose preference test and forced swim test. The expression of barrier proteins, such as Occludin, in the colon was determined by immunofluorescence. UPLC-Q-Orbitrap MS was utilized to analyze the serum metabolic profiles of sleep-deprived rats, screen for differential metabolites, and analyze metabolic pathways. The diversity of the gut microbiota was detected using 16S rRNA gene sequencing. Spearman correlation coefficient analysis was conducted to assess the correlation between differential metabolites and gut microbiota. The results indicated that SZRO significantly increased the sucrose preference index and decreased the immobility time in the forced swim test in rats. A total of 34 differential metabolites were identified through serum metabolomics. SZRW and SZRO shared five metabolic pathways, including phenylalanine metabolism. SZRW uniquely featured taurine and hypotaurine metabolism, while SZRO uniquely featured linoleic acid metabolism and tyrosine metabolism. Correlation analysis revealed that SZRW could upregulate the abundance of Bilophila, promoting the production of indole-3-propionic acid and subsequently upregulating the expression levels of intestinal tight junction proteins such as ZO-1, Occludin, and Claudin-1. SZRO could indirectly influence metabolic pathways such as arginine metabolism and linoleic acid metabolism by upregulating the abundance of gut microbiota such as Coprococcus and Eubacterium species. Both SZRW and SZRO can regulate endogenous metabolism, including amino acids, energy, and lipids, alter the gut microbiota microecology, and improve depressive-like behaviors. SZRO demonstrated superior effects in regulating metabolic pathways and gut microbiota structure compared to SZRW. The findings of this study provide a scientific basis for elucidating the pharmacodynamic material basis of Ziziphi Spinosae Semen.
Animals
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Rats
;
Gastrointestinal Microbiome/drug effects*
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Male
;
Metabolomics
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Drugs, Chinese Herbal/administration & dosage*
;
Depression/blood*
;
Rats, Sprague-Dawley
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Sleep Deprivation/complications*
;
Ziziphus/chemistry*
;
Antidepressive Agents/administration & dosage*
;
Behavior, Animal/drug effects*
;
Humans
6.Controllability and predictability of riboflavin-ultraviolet A collagen cross-linking: advances in experimental techniques and theoretical research.
Xiaona LIU ; Xiaona LI ; Weiyi CHEN
Journal of Biomedical Engineering 2025;42(1):212-218
Riboflavin-ultraviolet A (UVA) collagen cross-linking has not only achieved good clinical efficacy in the treatment of corneal diseases such as dilatation keratopathy, bullae keratopathy, infectious keratopathy, and in the combined treatment of corneal refractive surgeries, but also its efficacy and safety in scleral collagen cross-linking have been initially confirmed. To better promote the application of cross-linking in the clinical treatment of corneal and scleral diseases, exploring controllability and predictability of the surgical efficacy are both important for evaluating the surgical efficacy and personalized precision treatment. In this paper, the progress on the cross-linking depth of riboflavin-UVA collagen cross-linking, and its relationship with the cross-linking effect will be reviewed. It will provide the reference for further application of this procedure in ophthalmology clinics.
Riboflavin/pharmacology*
;
Humans
;
Collagen/radiation effects*
;
Ultraviolet Rays
;
Cross-Linking Reagents
;
Corneal Diseases/drug therapy*
;
Photosensitizing Agents/therapeutic use*
7.Design and analysis of human arm pathological tremor simulation system.
Zixin HE ; Haiping LIU ; Qingsheng LIU ; Yu JIANG ; Zhu ZHU
Journal of Biomedical Engineering 2025;42(4):790-798
In order to characterize the characteristics of pathological tremor of human upper limb, a simulation system of pathological tremor of human arm was provided and its dynamic response was analyzed. Firstly, in this study, a two-degree-of-freedom human arm dynamic model was established and linearized according to the arbitrary initial angle of joints. After solving the analytical solutions of steady-state responses of the joints, the numerical solution was used to verify it. The results of theoretical analysis show that the two natural frequencies of the developed dynamic model are 2.9 Hz and 5.4 Hz, respectively, which meet the characteristic frequency range of pathological tremors. Then, combined with the measured parameters of human arm, a tremor simulation system was built, and the measured results of joint responses are in good agreement with the theoretical and simulation analysis results, which verifies the effectiveness of the theoretical model. The results show that the human arm pathological tremor simulation system designed in this paper can characterize the frequency and response amplitude of the human upper limb pathological tremor. Moreover, the relevant research lays a theoretical foundation and experimental conditions for the subsequent development of wearable tremor suppression devices.
Humans
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Tremor/physiopathology*
;
Computer Simulation
;
Arm/physiopathology*
;
Joints/physiopathology*
;
Biomechanical Phenomena
;
Upper Extremity/physiopathology*
;
Models, Biological
8.An adaptive multi-label classification model for diabetic retinopathy lesion recognition.
Xina LIU ; Jun XIE ; Junjun HOU ; Xinying XU ; Yan GUO
Journal of Biomedical Engineering 2025;42(5):892-900
Diabetic retinopathy is a common blinding complication in diabetic patients. Compared with conventional fundus color photography, fundus fluorescein angiography can dynamically display retinal vessel permeability changes, offering unique advantages in detecting early small lesions such as microaneurysms. However, existing intelligent diagnostic research on diabetic retinopathy images primarily focuses on fundus color photography, with relatively insufficient research on complex lesion recognition in fluorescein angiography images. This study proposed an adaptive multi-label classification model (D-LAM) to improve the recognition accuracy of small lesions by constructing a category-adaptive mapping module, a label-specific decoding module, and an innovative loss function. Experimental results on a self-built dataset demonstrated that the model achieved a mean average precision of 96.27%, a category F1-score of 91.21%, and an overall F1-score of 94.58%, with particularly outstanding performance in recognizing small lesions such as microaneurysms (AP = 1.00), significantly outperforming existing methods. The research provides reliable technical support for clinical diagnosis of diabetic retinopathy based on fluorescein angiography.
Diabetic Retinopathy/diagnostic imaging*
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Humans
;
Fluorescein Angiography
;
Microaneurysm/diagnostic imaging*
;
Retinal Vessels
;
Algorithms
9.Three-dimensional printed scaffolds with sodium alginate/chitosan/mineralized collagen for promoting osteogenic differentiation.
Bo YANG ; Xiaojie LIAN ; Haonan FENG ; Tingwei QIN ; Song LYU ; Zehua LIU ; Tong FU
Journal of Biomedical Engineering 2025;42(5):1036-1045
The three-dimensional (3D) printed bone tissue repair guide scaffold is considered a promising method for treating bone defect repair. In this experiment, chitosan (CS), sodium alginate (SA), and mineralized collagen (MC) were combined and 3D printed to form scaffolds. The experimental results showed that the printability of the scaffold was improved with the increase of chitosan concentration. Infrared spectroscopy analysis confirmed that the scaffold formed a cross-linked network through electrostatic interaction between chitosan and sodium alginate under acidic conditions, and X-ray diffraction results showed the presence of characteristic peaks of hydroxyapatite, indicating the incorporation of mineralized collagen into the scaffold system. In the in vitro collagen release experiments, a weakly alkaline environment was found to accelerate the release rate of collagen, and the release amount increased significantly with a lower concentration of chitosan. Cell experiments showed that scaffolds loaded with mineralized collagen could significantly promote cell proliferation activity and alkaline phosphatase expression. The subcutaneous implantation experiment further verified the biocompatibility of the material, and the implantation of printed scaffolds did not cause significant inflammatory reactions. Histological analysis showed no abnormal pathological changes in the surrounding tissues. Therefore, incorporating mineralized collagen into sodium alginate/chitosan scaffolds is believed to be a new tissue engineering and regeneration strategy for achieving enhanced osteogenic differentiation through the slow release of collagen.
Chitosan/chemistry*
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Alginates/chemistry*
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Tissue Scaffolds/chemistry*
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Printing, Three-Dimensional
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Osteogenesis
;
Collagen/chemistry*
;
Cell Differentiation
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Animals
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Tissue Engineering/methods*
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Cell Proliferation
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Biocompatible Materials
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Glucuronic Acid/chemistry*
;
Hexuronic Acids/chemistry*
10.Expert consensus on the diagnosis and treatment of cemental tear.
Ye LIANG ; Hongrui LIU ; Chengjia XIE ; Yang YU ; Jinlong SHAO ; Chunxu LV ; Wenyan KANG ; Fuhua YAN ; Yaping PAN ; Faming CHEN ; Yan XU ; Zuomin WANG ; Yao SUN ; Ang LI ; Lili CHEN ; Qingxian LUAN ; Chuanjiang ZHAO ; Zhengguo CAO ; Yi LIU ; Jiang SUN ; Zhongchen SONG ; Lei ZHAO ; Li LIN ; Peihui DING ; Weilian SUN ; Jun WANG ; Jiang LIN ; Guangxun ZHU ; Qi ZHANG ; Lijun LUO ; Jiayin DENG ; Yihuai PAN ; Jin ZHAO ; Aimei SONG ; Hongmei GUO ; Jin ZHANG ; Pingping CUI ; Song GE ; Rui ZHANG ; Xiuyun REN ; Shengbin HUANG ; Xi WEI ; Lihong QIU ; Jing DENG ; Keqing PAN ; Dandan MA ; Hongyu ZHAO ; Dong CHEN ; Liangjun ZHONG ; Gang DING ; Wu CHEN ; Quanchen XU ; Xiaoyu SUN ; Lingqian DU ; Ling LI ; Yijia WANG ; Xiaoyuan LI ; Qiang CHEN ; Hui WANG ; Zheng ZHANG ; Mengmeng LIU ; Chengfei ZHANG ; Xuedong ZHOU ; Shaohua GE
International Journal of Oral Science 2025;17(1):61-61
Cemental tear is a rare and indetectable condition unless obvious clinical signs present with the involvement of surrounding periodontal and periapical tissues. Due to its clinical manifestations similar to common dental issues, such as vertical root fracture, primary endodontic diseases, and periodontal diseases, as well as the low awareness of cemental tear for clinicians, misdiagnosis often occurs. The critical principle for cemental tear treatment is to remove torn fragments, and overlooking fragments leads to futile therapy, which could deteriorate the conditions of the affected teeth. Therefore, accurate diagnosis and subsequent appropriate interventions are vital for managing cemental tear. Novel diagnostic tools, including cone-beam computed tomography (CBCT), microscopes, and enamel matrix derivatives, have improved early detection and management, enhancing tooth retention. The implementation of standardized diagnostic criteria and treatment protocols, combined with improved clinical awareness among dental professionals, serves to mitigate risks of diagnostic errors and suboptimal therapeutic interventions. This expert consensus reviewed the epidemiology, pathogenesis, potential predisposing factors, clinical manifestations, diagnosis, differential diagnosis, treatment, and prognosis of cemental tear, aiming to provide a clinical guideline and facilitate clinicians to have a better understanding of cemental tear.
Humans
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Dental Cementum/injuries*
;
Consensus
;
Diagnosis, Differential
;
Cone-Beam Computed Tomography
;
Tooth Fractures/therapy*


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