1.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.
2.Study on the measurable and traceable standards of quality markers for Compound xiebai capsules
Yueheng LIU ; Guoliang DAI ; Xuewen SHAO ; Ziyi YANG ; Wenzheng JU
China Pharmacy 2026;37(4):444-449
OBJECTIVE To explore and predict the quality markers (Q-markers) of Compound xiebai capsules for the treatment of chronic obstructive pulmonary disease (COPD) by constituents analysis combined with network pharmacology and molecular docking studies, and to establish the quality standard of Compound xiebai capsules. METHODS UHPLC-TOF-MS was used for qualitative analysis of Compound xiebai capsules, and the candidate Q-markers of Compound xiebai capsules were screened by combining network pharmacology and molecular docking technology. Further, HPLC was applied to establish the fingerprints of 15 batches of Compound xiebai capsules and to conduct quantitative analysis of the main components. RESULTS A total of 51 components were identified from Compound xiebai capsules. Among them, 15 components, namely oxyberberine, methylworenine, coptisine, tetrahydroberberine, epiberberine, berberine, magnoflorine, gandensin, cucurbitacin D, hydroxygenkwan, jatrorrhizine, columbamine, quercetin, cucurbitacin R, and palmatine, were determined as the candidate Q-markers for Compound xiebai capsules in the treatment of COPD. A total of 13 common peaks were calibrated in the fingerprints of 15 batches of Compound xiebai capsules for COPD treatment, with similarity values ranging from 0.976 to 0.999 compared to the reference fingerprint. Seven components were identified among these peaks, namely peak 5 (magnoflorine), peak 8 (jatrorrhizine), peak 9 (epiberberine), peak 10 (columbamine), peak 11 (coptisine), peak 12 (palmatine), and peak 13 (berberine). Their respective contents were (0.267±0.048), (0.453±0.084), (0.572±0.160), (0.392±0.074), (1.076±0.273), (1.477±0.271), and (6.664±1.249) mg/g ( n =3). CONCLUSIONS This study predicted 15 candidate Q-markers of Compound xiebai capsules in the treatment of COPD and established the fingerprint along with a quantitative determination method for seven major components.
3.Association between urinary levels of six per- and poly-fluoroalkyl substances in early pregnancy and risk of gestational diabetes mellitus
Ziyi LIU ; Luming YAN ; Tingting JIANG ; Yaling LI ; Chao ZHANG ; Jiahu HAO
Journal of Environmental and Occupational Medicine 2026;43(2):174-181
Background Per- and poly-fluoroalkyl substances (PFAS) can influence gestational diabetes mellitus (GDM); however, current studies on their association are limited and have yielded inconsistent findings. Objective To investigate the association between maternal exposure to PFAS, as measured by urinary concentrations in early pregnancy, and the risk of developing GDM. Methods Based on the Wuhu Birth Cohort in Anhui Province conducted between 2020 and 2023, this study included
4.Pharmacoeconomic evaluation of culmerciclib combined with fulvestrant in the second-line treatment of HR+/HER2− locally advanced or metastatic breast cancer
Ran LIU ; Shengnan GAO ; Congxin LI ; Yuxi ZHANG ; Ranran ZHANG ; Yue WANG ; Ziyi LIU ; Guoqiang LIU
China Pharmacy 2026;37(8):1033-1038
OBJECTIVE To evaluate the cost-effectiveness of culmerciclib combined with fulvestrant as second-line treatment for patients with hormone receptor-positive(HR+)/human epidermal growth factor receptor 2-negative (HER2–) locally advanced or metastatic breast cancer, within the context of the Chinese healthcare system. METHODS A partitioned survival model was established based on the CULMATE-1 study, with a simulation time horizon set at 15 years and a cycle length of 28 days. The incremental cost-effectiveness ratio (ICER) of culmerciclib combined with fulvestrant versus fulvestrant monotherapy as second-line treatment for HR+/HER2– breast cancer was calculated. One-way sensitivity analysis and probabilistic sensitivity analysis were performed to assess the robustness of the model. Meanwhile, scenario analysis of culmerciclib price reduction was conducted; the required price reduction and price to reach the willingness-to-pay (WTP) threshold in this study were calculated. RESULTS The results of the base-case analysis indicated that, compared with the fulvestrant monotherapy regimen, culmerciclib combined with fulvestrant yielded an additional 0.823 quality-adjusted life year (QALY), with a corresponding ICER of 371 696.26 yuan/QALY, which exceeded the WTP threshold (199 330 yuan/QALY). The results of the univariate sensitivity analysis indicated that the cost of culmerciclib, the discount rate, the utility values for progression disease and progression free survival status were significant factors influencing the ICER; both the univariate sensitivity analysis and the probabilistic sensitivity analysis validated the robustness of the model results. Scenario analysis indicated that when the price of culmerciclib was reduced by 30%, 55% and 85% respectively, the corresponding ICER values fell below 3, 2, and 1 times China’s per capita GDP in 2025, with the probability of cost-effectiveness being 3.00%, 94.90%, 100%. When the cost of culmerciclib (60 mg) was reduced by 52.6% to 50.96 yuan, the ICER value met the WTP threshold established in this study. CONCLUSIONS When the WTP threshold is set at twice China’s per capita GDP in 2025, second-line treatment with culmerciclib combined with fulvestrant for HR+/HER2– locally advanced or metastatic breast cancer does not exhibit cost-effectiveness advantage over fulvestrant monotherapy. Therefore, a reasonable price reduction is required to alleviate the financial burden on patients.
5.Erchentang Ameliorates SiO2-induced Lung Injury by Regulating Oxidative Stress and Metabolic Disorders via Nrf2/HO-1 Signaling Pathway
Jun LU ; Xinyi ZHU ; Ziyi LIU ; Jixia HU ; Jialu CHEN ; Rong XIAO ; Zhibin WANG ; Chang LIU ; Fangguo LU
Chinese Journal of Experimental Traditional Medical Formulae 2026;32(13):32-42
ObjectiveTo observe the protective effect of Erchentang (ECT) on SiO2-induced lung injury in rats and to explore its underlying mechanism. MethodsA rat model of lung injury was established by a single intratracheal instillation of 50 mg·mL-1 SiO2 suspension. Thirty male Sprague-Dawley (SD) rats were randomly assigned to five groups: control, model, low and high-dose (4.5 g·kg-1·d-1 and 9 g·kg-1·d-1, respectively) ECT, and dexamethasone (0.2 mg·kg-1·d-1). All the groups were treated for 4 consecutive weeks. Histopathological alterations in the lung tissue were examined by hematoxylin and eosin (HE) staining. The levels of malondialdehyde (MDA), superoxide dismutase (SOD), and glutathione peroxidase (GSH-Px) in the lung tissue were measured through biochemical assays. The expression of key molecules in the nuclear factor erythroid 2-related factor 2 (Nrf2)/heme oxygenase-1 (HO-1) pathway was determined by Real-time fluorescence quantitative polymerase chain reaction (Real-time PCR), Western blot, and immunofluorescence assay. The primary active components of ECT were identified by ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS), and their binding affinity to Nrf2/HO-1 was assessed by molecular docking. Untargeted metabolomics of the lung tissue was performed based on UPLC-quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF-MS), and correlation analysis was performed to identify differential metabolites and parameters closely associated with the Nrf2/HO-1 pathway. ResultsCompared with the control group, the model group exhibited a reduction in body weight gain, an increase in lung index, increased MDA content, weakened SOD and GSH-Px activities in the lung tissue, down-regulated mRNA and protein levels of Nrf2 and protein levels of HO-1 and GPX4, and an up-regulated protein level of Keap1 (P<0.05, P<0.01). Treatment with ECT attenuated the SiO2-induced decline in body weight (P<0.05), alleviated inflammatory cell infiltration and silicotic nodule formation in alveoli, and reduced the MDA content and enhanced the SOD and GSH-Px activities in the lung tissue (P<0.05, P<0.01). UPLC-MS/MS and molecular docking revealed that core components of ECT, such as hesperidin and glycyrrhizic acid, displayed strong binding affinity to Nrf2/HO-1. Molecular biological experiments demonstrated that ECT promoted nuclear translocation of Nrf2, up-regulated the mRNA and protein levels of HO-1 and GPX4, and down-regulated Keap1 expression (P<0.05, P<0.01). Metabolomic analysis indicated that ECT reversed the SiO2-induced aberrant expression of metabolites, including linoleic acid and glutamine (P<0.05, P<0.01). Correlation analysis showed that Nrf2 and HO-1 were positively correlated with SOD and GSH-Px (P<0.05, P<0.01), but negatively correlated with glutamine and serine (P<0.05, P<0.01). ConclusionECT may activate the Nrf2/HO-1 pathway through its core active components, thereby regulating oxidative stress and metabolic disorders to ameliorate SiO2-induced lung injury in rats. This study provides experimental evidence for ECT in the prevention and treatment of occupational lung injury.
6.Progress of researches on Triatoma rubrofasciata-transmitted trypanosomes
Ziyi WANG ; Yong SHEN ; Lirong HUANG ; Yuanyuan LI ; Di WU ; Qin LIU
Chinese Journal of Schistosomiasis Control 2026;38(2):213-218
Triatoma rubrofasciata is currently the most widely distributed species of Triatoma worldwide, and it is also widespread in southern China. T. rubrofasciata has been proven to transmit Trypanosoma cruzi, and is one of vectors transmitting Chagas disease, which poses a potential risk for transmission of imported Chagas disease in China. Findings from latest studies have shown that T. rubrofasciata naturally infects T. lewisi, T. conorhini, and T. rangeli, which undoubtedly increases significant risks of and challenges to trypanosomiasis control in China. This article briefly describes the species of T. rubrofasciata-transmitted trypanosomes, and summarizes the epidemiological characteristics of trypanosomiasis, so as to provide insights into T. rubrofasciata-transmitted trypanosomiasis surveillance and control, and prevention of trypanosomiasis development and transmission in China.
7.DIA Proteomic Profiling on Staged Regulatory Effect of Tonifying Deficiency and Dredging Collaterals Method on Liver Fibrosis in Rats Based on Theory of "Zhu Ke Jiao"
Xin WANG ; Pengyu ZHU ; Li WEN ; Jibin LIU ; Aochun YUE ; Ziyi CHEN ; Jing ZHANG ; Li ZHU ; Quansheng FENG ; Cen JIANG
Chinese Journal of Experimental Traditional Medical Formulae 2026;32(14):119-132
ObjectiveThis paper aims to investigate the differential mechanisms underlying the staged therapeutic effects of Qijia Rougan formula on liver fibrosis using proteomic technology. MethodsThe staged rat model of liver fibrosis was established by subcutaneous injection of carbon tetrachloride (CCl4) and olive oil. One hundred and four SD rats were randomized into thirteen groups:a normal group,a two-week model group,a four-week model group,a six-week model group,an eight-week model group,a two-week Qijia Rougan formula group,a four-week Qijia Rougan formula group,a six-week Qijia Rougan formula group,an eight-week Qijia Rougan formula group,a two-week compound Biejia Ruangan tablet group,a four-week Compound Biejia Ruangan Tablet group,a six-week Compound Biejia Ruangan Tablet group,and an eight-week compound Biejia Ruangan tablet group. After two weeks of drug intervention,liver tissue and abdominal aortic blood samples were collected from the rats for testing. Hematoxylin-eosin (HE) staining,Masson staining,and Picro Sirius red staining were used to observe pathological damage and collagen fiber deposition in liver tissues. Immunohistochemistry (IHC) was employed to detect the contents of fibrosis markers in liver tissues. The contents of liver function indicators in the serum were measured using a fully automated biochemical analyzer,and the levels of liver fibrosis indicators in the serum were assessed by enzyme-linked immunosorbent assay (ELISA). Liver tissues from the normal group,each model group,and each Qijia Rougan formula group were subjected to label-free quantitative proteomic analysis to identify differential proteins among the groups,with key proteins validated by Western blot. Finally,bioinformatics analysis was performed on the differential proteins. Results(1) The staged rat model of liver fibrosis constructed with CCl4 and olive oil showed pathological results at the 2nd,4th,6th,and 8th weeks of modeling that were consistent with the Metavir standards for the F1,F2,F3,and F4 stages. Compared with those in the normal control group,the protein expressions of α-smooth muscle actin (α-SMA) and Collagen Ⅰ were significantly increased in each stage (P<0.05). The levels of liver function indicators in the serum,including alanine aminotransferase (ALT),aspartate aminotransferase (AST),alkaline phosphatase (ALP),direct bilirubin (DBIL),and total bilirubin (TBil) in each model group,were significantly elevated in each stage (P<0.01). The levels of liver fibrosis indicators in the serum,including procollagen Ⅲ peptide (PⅢP),type Ⅳ collagen(Ⅳ-C),hyaluronic acid (HA),and laminin (LN) in each model group,were significantly increased in each stage (P<0.05,P<0.01). This study successfully established a staged rat model of liver fibrosis. (2) Compared with the model groups at each stage,the administration groups showed a reduction in hepatocyte ballooning degeneration,a more orderly arrangement of hepatocytes,and a decrease of inflammatory cell infiltration. The blue-stained collagen fibers became significantly thinner and finer,with reduced and narrowed fibrous septa. The areas of collagen fibers and Picro Sirius red staining were reduced (P<0.05). The positive areas of α-SMA and Collagen Ⅰ expression were significantly decreased (P<0.05). The levels of ALT,AST,ALP,DBIL,and TBil in the rats of the model groups at each stage were significantly reduced (P<0.05,P<0.01). The levels of PⅢP,Ⅳ-C,HA,and LN in the rats of the model groups at each stage were significantly decreased (P<0.05). Among these,the improvements in all indicators were most significant in the F3 stage (P<0.01).(3) The proteomic results show that a total of 165 differential proteins exhibit a callback trend when comparing the model groups at four stages with the normal group,and when comparing the Qijia Rougan formula group with the model group. Western blot analysis reveals that the levels of NAD(P)H:quinone oxidoreductase 1 (NQO1),mitogen-activated protein kinase 1 (MAPK1),arginase 1 (Arg1),and glutathione S-transferase α1 (GSTA1) were consistent with the proteomic results. Bioinformatics results reveal that 165 differentially expressed proteins are enriched in multiple signaling pathways. Notably,signaling pathways such as drug metabolism-cytochrome P450,arginine biosynthesis,and the peroxisome proliferator-activated receptor (PPAR) signaling pathway were found to be closely associated with liver fibrosis,suggesting that the Qijia Rougan formula may exert its staged regulatory effects on liver fibrosis by regulating these pathways. ConclusionThe Qijia Rougan formula may achieve staged regulation of liver fibrosis by regulating drug metabolism-cytochrome P450,arginine biosynthesis,and the PPAR signaling pathway.
8.Buqi-Tongluo Decoction inhibits osteoclastogenesis and alleviates bone loss in ovariectomized rats by attenuating NFATc1, MAPK, NF-κB signaling.
Yongxian LI ; Jinbo YUAN ; Wei DENG ; Haishan LI ; Yuewei LIN ; Jiamin YANG ; Kai CHEN ; Heng QIU ; Ziyi WANG ; Vincent KUEK ; Dongping WANG ; Zhen ZHANG ; Bin MAI ; Yang SHAO ; Pan KANG ; Qiuli QIN ; Jinglan LI ; Huizhi GUO ; Yanhuai MA ; Danqing GUO ; Guoye MO ; Yijing FANG ; Renxiang TAN ; Chenguang ZHAN ; Teng LIU ; Guoning GU ; Kai YUAN ; Yongchao TANG ; De LIANG ; Liangliang XU ; Jiake XU ; Shuncong ZHANG
Chinese Journal of Natural Medicines (English Ed.) 2025;23(1):90-101
Osteoporosis is a prevalent skeletal condition characterized by reduced bone mass and strength, leading to increased fragility. Buqi-Tongluo (BQTL) decoction, a traditional Chinese medicine (TCM) prescription, has yet to be fully evaluated for its potential in treating bone diseases such as osteoporosis. To investigate the mechanism by which BQTL decoction inhibits osteoclast differentiation in vitro and validate these findings through in vivo experiments. We employed MTS assays to assess the potential proliferative or toxic effects of BQTL on bone marrow macrophages (BMMs) at various concentrations. TRAcP experiments were conducted to examine BQTL's impact on osteoclast differentiation. RT-PCR and Western blot analyses were utilized to evaluate the relative expression levels of osteoclast-specific genes and proteins under BQTL stimulation. Finally, in vivo experiments were performed using an osteoporosis model to further validate the in vitro findings. This study revealed that BQTL suppressed receptor activator of NF-κB ligand (RANKL)-induced osteoclastogenesis and osteoclast resorption activity in vitro in a dose-dependent manner without observable cytotoxicity. The inhibitory effects of BQTL on osteoclast formation and function were attributed to the downregulation of NFATc1 and c-fos activity, primarily through attenuation of the MAPK, NF-κB, and Calcineurin signaling pathways. BQTL's inhibitory capacity was further examined in vivo using an ovariectomized (OVX) rat model, demonstrating a strong protective effect against bone loss. BQTL may serve as an effective therapeutic TCM for the treatment of postmenopausal osteoporosis and the alleviation of bone loss induced by estrogen deficiency and related conditions.
Animals
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NFATC Transcription Factors/genetics*
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Drugs, Chinese Herbal/pharmacology*
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Ovariectomy
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Osteoclasts/metabolism*
;
Female
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Osteogenesis/drug effects*
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Rats, Sprague-Dawley
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Rats
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NF-kappa B/genetics*
;
Osteoporosis/genetics*
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Signal Transduction/drug effects*
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Bone Resorption/genetics*
;
Cell Differentiation/drug effects*
;
Humans
;
RANK Ligand/metabolism*
;
Mitogen-Activated Protein Kinases/genetics*
;
Transcription Factors
9.VenusMutHub: A systematic evaluation of protein mutation effect predictors on small-scale experimental data.
Liang ZHANG ; Hua PANG ; Chenghao ZHANG ; Song LI ; Yang TAN ; Fan JIANG ; Mingchen LI ; Yuanxi YU ; Ziyi ZHOU ; Banghao WU ; Bingxin ZHOU ; Hao LIU ; Pan TAN ; Liang HONG
Acta Pharmaceutica Sinica B 2025;15(5):2454-2467
In protein engineering, while computational models are increasingly used to predict mutation effects, their evaluations primarily rely on high-throughput deep mutational scanning (DMS) experiments that use surrogate readouts, which may not adequately capture the complex biochemical properties of interest. Many proteins and their functions cannot be assessed through high-throughput methods due to technical limitations or the nature of the desired properties, and this is particularly true for the real industrial application scenario. Therefore, the desired testing datasets, will be small-size (∼10-100) experimental data for each protein, and involve as many proteins as possible and as many properties as possible, which is, however, lacking. Here, we present VenusMutHub, a comprehensive benchmark study using 905 small-scale experimental datasets curated from published literature and public databases, spanning 527 proteins across diverse functional properties including stability, activity, binding affinity, and selectivity. These datasets feature direct biochemical measurements rather than surrogate readouts, providing a more rigorous assessment of model performance in predicting mutations that affect specific molecular functions. We evaluate 23 computational models across various methodological paradigms, such as sequence-based, structure-informed and evolutionary approaches. This benchmark provides practical guidance for selecting appropriate prediction methods in protein engineering applications where accurate prediction of specific functional properties is crucial.
10.Development trajectory of mobile phone dependence in middle school students and its association with loneliness and self-control
LUO Xiangyu, ZHANG Tiancheng, WANG Aolun, ZHANG Fulan, LIU Yang, YAN Chuqi, CHEN Ziyi
Chinese Journal of School Health 2025;46(5):624-629
Objective:
To analyze the heterogeneity of mobile phone dependence development trajectory in middle school students and its association with loneliness and selfcontrol ability, so as to provide reference for the prevention of mobile phone dependence in middle school students.
Methods:
A total of 941 grade 1 students from 4 public middle schools in Xiangxi Autonomous Prefecture, Hunan Province were selected for the followup survey by random cluster sampling from October 2023 to April 2024 and October 2024. Mobile Phone Addiction Index (MPAI), University of California, Los Angeles Loneliness Scale-20 (UCLA-20) and Selfcontrol Scales (SCS) were used for questionnaire survey. The heterogeneity of the developmental trajectory of middle school students mobile phone dependence was analyzed by the latent growth curve model (LGMM), and the influencing factors of the developmental trajectory of middle school students mobile phone dependence were explored by multiple Logistic regression analysis.
Results:
The development trajectory of middle school students mobile phone dependence could be divided into four categories: C1 "low risk slow decline group (n=438,44.6%)", C2 "medium risk slow rise group (n=272,29.7%)", C3 "high risk rapid decline group (n=73,8.6%)" and C4 "high risk rapid rise group (n=158,17.1%)". There were significant differences in the distribution of mobile phone dependence development track heterogeneity subgroups among sex, only child, lodging, and leftbehind students (χ2=117.79, 44.88, 37.09, 130.50, P <0.01). The results of the multinomial Logistic regression model analysis showed that, with C1 group as the reference, C2, C3, and C4 were positively correlated with students loneliness [OR(95%CI)=1.04 (1.02-1.06), 1.11(1.08-1.14), 1.12(1.09-1.14)]; C2 and C4 groups were negatively correlated with students selfcontrol [OR(95%CI)=0.97(0.96-0.99), 0.95(0.93-0.97)] (P<0.01).
Conclusions
The development trajectory of mobile phone dependence among middle school students is heterogeneous. Reducing the loneliness of individuals and cultivating good selfcontrol ability are helpful to alleviate mobile phone dependence behavior among middle school students.


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