OBJECTIVE:Based on different algorithms of machine learning,the prediction model of lumbar disc herniation has become a trend and hot spot in the development of precision medicine.However,there is limited evidence on the reporting quality and methodological quality of prediction models of lumbar disc herniation outcomes using machine learning.This article is aimed to explore the performance of machine learning algorithms in predicting the prognosis of lumbar disc herniation by comprehensively analyzing the report quality and risk of bias of previous studies that developed and validated prognosis prediction models based on machine learning through a comprehensive literature search,in order to explore the performance of machine learning algorithms in predicting the prognosis of lumbar disc herniation.METHODS:The databases of CNKI,WanFang,VIP,SinOMED,PubMed,Web of Science,Embase,and The Cochrane Library were searched by computer.Studies on the use of machine learning to develop(and/or validate)prognostic prediction models for lumbar disc herniation were collected from the inception of the database to December 31,2023.Two researchers independently screened the literature,extracted data,and assessed the risk of bias of the included studies.The reporting quality and risk of bias of the included studies were assessed by the Multivariable Transparent Reporting of Predictive Models(TRIPOD)statement and the Predictive Model Risk of Bias Assessment Tool(PROBAST).The results of the evaluation were analyzed using descriptive statistics and visual charts.RESULTS:(1)A total of 23 articles were included,and the TRIPOD compliance of each study ranged from 11％to 87％,with a median compliance of 54％.The quality of reporting of titles,detailed descriptions of treatment measures,blinding of predictors,handling of missing data,details of risk stratification,specific procedures for enrollment,model interpretation,and model performance was mostly poor,with TRIPOD adherence rates ranging from 4％to 35％.(2)Of all included studies,61％had a high risk of bias and 39％had an unclear overall risk of bias.The area under the curve,accuracy,sensitivity and specificity were used to evaluate the performance of the model.The areas under the curve of 20 models were reported,ranging from 0.561 to 0.999.Three models reported the accuracy of the model,ranging from 82.07％to 89.65％.(3)Among all included studies,the statistical analysis domain was most often assessed as having a high risk of bias,mainly due to the small number of valid samples,the selection of predictors based on univariate analysis and the lack of calibration and discrimination assessment of the model in the study.CONCLUSION:These results indicate that machine learning can achieve good predictive ability in the development and validation of prognostic models for lumbar disc herniation.The commonly used algorithms include regression algorithm,support vector machine,decision tree,random forest,artificial neural network,naive Bayes and other algorithms.Reasonable algorithms combined with clinical practice can improve the accuracy of prognosis prediction of lumbar disc herniation.However,the reporting and methodological quality of prognosis prediction models based on machine learning are poor,the prediction performance of different models varies greatly,and the generalization and extrapolation of research models are unclear.There is an urgent need to improve the design,implementation and reporting of such studies.To promote the application of machine learning in the clinical practice of lumbar disc herniation prediction models,it is necessary to comprehensively consider various predictors related to the prognosis of the disease before modeling,and strictly follow the relevant standards of PROBAST tool during modeling.

BACKGROUND:Although previous studies have reported associations between lipids and the risk of osteoporotic pathological fractures,the specific causal relationships between lipid level and osteoporotic pathological fractures remain unclear.OBJECTIVE:To elucidate the causal relationship between lipids and osteoporotic pathological fractures using a two-sample bidirectional Mendelian randomization analysis.METHODS:The data for 178 lipid metabolites were obtained from the IEU-GWAS database(developed by the MRC Integrative Epidemiology Unit at the University of Bristol,UK,which provides extensive summary data from genome-wide association studies),while osteoporotic pathological fracture data(from 173 619 European participants)were acquired from the FinnGen database(constructed by the Finnish national gene research program,focusing on investigating relationships between genomics and health/disease in the Finnish population).Osteoporotic pathological fracture data were used as the outcome variable,with lipids serving as exposures,for the bidirectional Mendelian randomization study to evaluate the causal effects of different lipids on osteoporotic pathological fractures.The UK Biobank database was employed as a validation set by switching the outcome variable to verify the findings horizontally.RESULTS AND CONCLUSION:(1)The inverse variance weighted analysis indicated that each unit increase in sterol ester(27∶1/20∶2)levels was associated with a 25.55％increase in the risk of osteoporotic pathological fractures(odds ratio=1.256,95％confidence interval:1.001-1.575,P=0.049),suggesting a significant positive correlation between elevated sterol ester levels and increased fracture risk.Reverse Mendelian randomization analysis revealed a significant negative association between osteoporotic pathological fractures and three types of phosphatidylcholine.Horizontal validation yielded consistent results,confirming sterol ester as a risk factor for osteoporotic pathological fractures.(2)The results indicate that sterol ester is a risk factor for osteoporotic pathological fractures,while phosphatidylcholine serves as a protective factor.These findings strengthen the evidence supporting the effect of lipids on the risk of osteoporotic pathological fractures.Although the GWAS data used in this study were derived from European populations,given the broad commonality of human genetics,the results provide valuable reference significance for improving osteoporosis in Chinese populations through lipid regulation.

Objective: To investigate the effects of a Twin-Block appliance combined with slow maxillary expansion (SME) on transverse dental and skeletal parameters in adolescent patients with Angle Class Ⅱ division 1 malocclusion, and to provide a reference for clinical orthodontic practice. Methods: This retrospective study was approved by the Institutional Ethics Committee. A total of 21 adolescents with Class Ⅱ division 1 malocclusion who underwent two-phase treatment with a Twin-Block appliance combined with SME at the Department of Orthodontics, College & Hospital of Stomatology, Guangxi Medical University, in 2021 to 2023 were consecutively enrolled. In the first phase, a functional appliance was used to coordinate the skeletal relationship between the maxilla and mandible by leveraging growth potential. In the second phase, a fixed appliance was employed for fine adjustments of the dental arches based on the specific condition. Cone-beam computed tomography (CBCT) scans were obtained before treatment (T0) and after the first phase of functional correction (T1). Transverse measurements at the first molar region, including molar buccolingual inclination, dental arch width, and basal bone width, were performed using Dolphin 3D Imaging software. Changes between T0 and T1 were statistically analyzed. Results: After the first phase of treatment, the left and right maxillary first molars showed a significant increase in buccal inclination by 5.47° ± 1.38° and 5.35° ± 1.61°, respectively (P<0.001). The arch width in the maxillary first molar region also increased by (2.68 ± 1.14) mm, and the basal bone width increased by (1.14 ± 1.24) mm (all P<0.001). The proportion of skeletal expansion accounted for an average of 42.86%, while dental expansion accounted for 57.14%. No statistically significant changes were observed in any mandibular transverse measurements (all P>0.05). Conclusion In adolescent patients with Angle Class Ⅱ division 1 malocclusion accompanied by maxillary transverse deficiency, Twin-Block appliance combined with SME can effectively expand maxillary dental arch and basal bone width while improving sagittal relationship, thereby correcting transverse discrepancy. The maxillary width changes were predominantly dental.

[摘 要] 目的：探讨lncRNA DLEU2通过EZH2/H3K27me3途径调控IKKα介导甲状腺癌（TC）放射性碘抵抗的作用机制。方法：利用TCGA数据库分析TC中DLEU2的表达及其与EZH2的相关性。构建放射性碘抵抗的TPC-1细胞（RR-TPC-1细胞）模型及裸鼠移植瘤模型，通过敲低或过表达DLEU2（si-DLEU2/OE-DLEU2）、抑制EZH2（UNC1999）、过表达IKKα（OE-IKKα）进行干预，采用qPCR、WB、RIP、ChIP、CCK-8、流式细胞术、TUNEL染色及体内成瘤实验检测基因与蛋白表达、表观修饰、细胞增殖、凋亡及肿瘤生长。结果：TCGA分析显示，DLEU2在TC组织中显著上调（P < 0.001），与患者不良预后相关（P = 0.008 4），且与EZH2表达呈正相关（r = 0.390, P < 0.001）；RIP证实EZH2与DLEU2存在相互作用/结合（P < 0.05）。体外实验表明，敲低DLEU2可显著下调RR-TPC-1细胞中EZH2、IKKα表达及H3K27me3修饰水平，抑制NF-κB通路活化（P < 0.05或P < 0.01），抑制细胞增殖、促进凋亡（均P < 0.05）。联合敲低DLEU2与抑制EZH2进一步增强上述效应，而过表达IKKα则可部分逆转上述效应（P < 0.05或P < 0.01）。体内实验进一步证实，敲低DLEU2联合抑制EZH2可显著抑制移植瘤生长，增加肿瘤细胞凋亡（均P < 0.01）；IKKα过表达则部分逆转上述抗肿瘤效应（P < 0.05或P < 0.01）。结论：lncRNA DLEU2通过招募EZH2催化H3K27me3修饰，间接激活IKKα/NF-κB信号并形成正反馈环路，介导TPC-1细胞131I抵抗。

Objective To explore the construction of heart preservation model of empty beating donor based on extracorporeal membrane oxygenation (ECMO). Methods From January 2022 to August 2023, 20 Guangxi Bama miniature pigs weighing 25-30 kg were selected, half male and half female. Under general anesthesia and heparinization, a midline thoracotomy was performed. The pericardium was cut after freeing the anterior and posterior vena cavae, and a perfusion needle was inserted near the brachiocephalic artery in the ascending aorta, connected to a blood collection bag to collect 500-600 mL of blood. The anterior and posterior vena cavae were ligated, the aorta was blocked and perfused with HTK solution to stop the heart beating. The superior and inferior vena cavae were cut off, the right pulmonary vein was decompressed, the aorta and left and right pulmonary arteries and veins were cut off, and the whole heart was removed. An ECMO device was used to continuously perfuse a cardioprotective solution mainly composed of oxygenated warm blood, maintaining the isolated pig heart beating for 8 hours, monitoring (once/hour) ECMO perfusion parameters, blood gas indicators, perfusate electrolytes, inflammatory factors, myocardial enzymes, myoglobin, and troponin levels. Myocardial tissue was taken for hematoxylin-eosin (HE) staining to observe myocardial cell damage and evaluate the quality of heart preservation. Results Among the 20 isolated beating pig hearts, 17 successfully resumed beating, 3 experienced ventricular fibrillation, resuscitated after intracardiac electrical defibrillation, and all 20 pig hearts successfully beat for 8 hours. There was no statistical difference in ECMO perfusion parameters, blood gas indicators, perfusate electrolytes, and inflammatory factors at each time point (P>0.05). There were statistical increases in myocardial enzymes, myoglobin, and troponin levels (P<0.05). HE staining results suggested that there was no severe myocardial damage. Conclusion ECMO technology can be used for pig heart preservation with good results, and this study provides experimental evidence for improving heart preservation research in clinical heart transplantation.

Objective: To systematically evaluate the performance of machine learning (ML) models in predicting non suicidal self injury (NSSI) behavior among adolescents, providing an evidence based foundation for the development of clinically applicable risk assessment tools. Methods: A comprehensive search was conducted in PubMed, Embase, Web of Science, CNKI, and Wanfang databases for relevant studies from their inception to July 21, 2025. The Prediction Model Risk of Bias Assessment Tool (PROBAST) was used to evaluate the methodological quality of the included studies. Stata 18 software was used to calculate the area under the receiver operating characteristic curve (AUC) of the models, and publication bias assessment, sensitivity analysis, and Egger s test were performed. Results: The total of 12 studies (42 prediction models) involving 58 070 adolescents were included. There were 15 machine learning algorithms in total, among which Random Forest, Logistic Regression, XGBoost, and Support Vector Machines were the most frequently utilized. The most common predictors were gender (female), family function, depression, emotion regulation, and age. All 12 included studies exhibited a high risk of bias. The pooled AUC was 0.80 (95% CI =0.78-0.82), although heterogeneity was substantial ( I 2=95.8%, P <0.01). Sensitivity analysis confirmed the robustness of these findings (no overlap in 95% CI ), while Egger s test indicated the presence of publication bias ( P <0.05). Conclusions Machine learning demonstrates potential in the risk prediction of adolescent NSSI, but existing models have a high risk of bias. Future research should focus on improving methodological quality and optimizing model reliability through rigorous external validation.

ObjectiveTo evaluate the comprehensive intervention effects of Huangqin Qingre Chubi Capsule （黄芩清热除痹胶囊， HQC） on self-perception of patients （SPP） and immune inflammation in patients with rheumatoid arthritis （RA）， and to explore its potential mechanisms. MethodsClinical data of 452 RA patients were retrospectively collected. Patients were divided into a control group （274 cases）， treated with conventional western medicine， and an observation group （178 cases）， treated with HQC for at least 2 weeks in addition to conventional western medicine. The treatment duration was 2 weeks for both groups. Propensity score matching （PSM） was performed at a ratio of 1∶1 to match patients between groups. SPP including the Chinese version of the short form-36 health survey （SF-36）， self-rating anxiety scale （SAS）， self-rating depression scale （SDS）， visual analog scale （VAS）， and Chinese patient-reported index for rheumatoid arthritis （CPRI-RA）， as well as immune inflammatory indicators， including erythrocyte sedimentation rate （ESR）， high-sensitivity C-reactive protein （hs-CRP）， rheumatoid factor （RF）， anti-cyclic citrullinated peptide antibody （anti-CCP）， interleukin-6 （IL-6）， immunoglobulin A （IgA）， immunoglobulin G （IgG）， immunoglobulin M （IgM）， complement C3， and complement C4， were collected before and after treatment. Spearman correlation analysis was used to assess the relationships between SPP and immune inflammatory indicators. Logistic regression， association rule analysis， and mediation analysis were performed to evaluate the effects and potential pathways of HQC on SPP and immune inflammatory indicators. Network pharmacology was applied to identify the active components and core targets of HQC in the treatment of RA， followed by molecular docking verification. In cell experiments， cells were divided into normal group， model group， 20% medicated serum group， and 80 nmol/L control group. Human synovial fibroblasts （FLS） were cultured with complete medium in the normal group， while human rheumatoid arthritis fibroblast-like synoviocytes （RA-FLS） were cultured in the model group. In the 20% medicated serum group， RA-FLS were cultured with medium containing 20% HQC-medicated serum， and in the 80 nmol/L control group， RA-FLS were cultured with complete medium containing 80 nmol/L methotrexate suspension. After 48 h of culture， cell viability was detected by cell counting kit-8 （CCK-8） assay. Levels of interleukin-1β （IL-1β）， interleukin-6 （IL-6）， interleukin-8 （IL-8）， and interleukin-10 （IL-10） in the cell supernatant were measured by enzyme-linked immunosorbent assay （ELISA）. Protein levels of matrix metalloproteinase 9 （MMP9）， transcription factor AP-1 subunit （JUN）， vascular endothelial growth factor A （VEGFA）， and C-X-C motif chemokine ligand 8 （CXCL8） were detected by Western Blot， and cell migration ability was evaluated using Transwell assay. ResultsAfter PSM， 178 cases were included in each group. After treatment， SF-36 scores increased， while scores of SAS， SDS， VAS and CPRI-RA， levels of ESR， hs-CRP， IL-6， complement C3， and complement C4 levels decreased in both groups； IgG and IgM levels were also reduced in the observation group （P＜0.05）. Physical functioning （correlation coefficient -0.19， P＜0.05） and social functioning （correlation coefficient -0.18， P＜0.05） of SF-36 were negatively correlated with hs-CRP， while VAS score was positively correlated with hs-CRP （correlation coefficient 0.19， P＜0.05）. HQC showed high associations with improvements in multiple indicators of SPP and immune inflammatory， and acted as a protective factor for the improvement of several SPP； hs-CRP and ESR played partial mediating roles in the improvement of SPP induced by HQC （P＜0.05）. Network pharmacology analysis identified baicalein， quercetin， α1-sitosterol， β-sitosterol， stigmasterol， baicalin， and crocetin as the core active components， and JUN， IL-6， VEGFA， MMP9， IL-1β， and CXCL8 as the core targets. Molecular docking results showed strong binding affinities of quercetin with VEGFA， JUN， MMP9， IL-6， and IL-1β， of baicalin with VEGFA and MMP9， and of wogonin with CXCL8. Cell experiments demonstrated that HQC and methotrexate inhibited RA-FLS viability and migration， reduced levels of IL-1β， IL-6， and IL-8， decreased protein levels of MMP9， JUN， VEGFA， and CXCL8， and increased IL-10 levels （P＜0.05）. ConclusionHQC can improve SPP in RA by regulating immune inflammatory responses. Its mechanism may be related to multi-pathway and multi-target inhibition of synovial cell inflammation and migration.

BackgroundCurrently， the incidence of depression among teenagers is on the rise， and the related academic problems are becoming increasingly serious. Short video addiction has a negative impact on teenagers' emotional issues and academic achievements. However， few studies have explored the relationship between this addiction and the learning burnout of teenagers with depression， and even fewer have focused on the role paths of impulsivity and coping disposition in this process. ObjectiveTo explore the relationship between short video addiction and learning burnout in adolescent patients with depression， as well as the pathway of impulsivity and coping disposition， so as to provide references for the intervention of learning burnout in adolescent patients with depression. MethodsA total of 191 adolescent patients who were hospitalized at The Affiliated Brain Hospital of Guangzhou Medical University from December 2024 to April 2025 and met the diagnostic criteria for depression according to the International Classification of Diseases， tenth edition （ICD-10） were selected consecutively. The Short Video Addiction Measurement Scale （SVAMS）， the Brief Barratt Impulsiveness Scale （BBIS）， the Simplified Coping Style Questionnaire （SCSQ）， and the Adolescent Student Burnout Inventory （ASBI） were used for assessment. Pearson correlation analysis was employed to examine the correlations of the scores of each scale. Model 6 of the SPSS macro Process 4.2 was employed to analyze the chained mediation pathway of impulsivity and coping disposition between short video addiction and learning burnout. ResultsA total of 173 cases （90.58%） of adolescent patients with depression completed the valid questionnaire survey. Correlation analysis showed that SCSQ coping disposition score was negatively correlated with the SVAMS score， the BBIS score， and the ASBI score （r=-0.282， -0.341， -0.431， P<0.01）， the SVAMS score was positively correlated with the BBIS score and the ASBI score （r=0.339， 0.262， P<0.01）， and the BBIS score was positively correlated with the ASBI score （r=0.486， P<0.01）. The pathway analysis showed that the direct effect of short video addiction on learning burnout was not statistically significant， but the total effect and the indirect effect were statistically significant. The effect values were 0.275 （95% CI： 0.207–0.343） and 0.193 （95% CI： 0.143–0.246）， respectively， with the indirect effect accounting for 70.18%. Impulsivity and coping disposition both played independent mediating roles between short video addiction and learning burnout， with effect values of 0.122 （95% CI： 0.090–0.156） and 0.054 （95% CI： 0.032–0.079）， accounting for 44.36% and 19.64% of the total effect， respectively. The chained mediation effect of impulsivity and coping disposition was significant， with an effect value of 0.017 （95% CI： 0.011–0.026）， accounting for 6.18% of the total effect. ConclusionAlthough short video addiction does not directly affect learning burnout in adolescent patients with depression， it may indirectly influence learning burnout through independent and chain paths of impulsivity and coping disposition. ［Funded by Guangzhou Key Clinical Specialty （Clinical Medical Research Institute）］

BackgroundPersistent cognitive impairment is prevalent among patients with stable schizophrenia. While serum total bile acid （TBA） level in acute-phase patients are known to be associated with cognitive dysfunction， the relationship between serum TBA and multi-dimensional cognitive functions in stable phase patients remains unclear. ObjectiveTo investigate the correlation between serum TBA level and cognitive function in patients with stable schizophrenia， and to evaluate its predictive value for cognitive impairment， thereby providing a serological biomarker for the timely identification and objective assessment of cognitive dysfunction. MethodsA cross-sectional study was conducted on 137 inpatients with stable schizophrenia at The Fourth People's Hospital of Yancheng from March to December 2024. All participants met the diagnostic criteria of the Diagnostic and Statistical Manual of Mental Disorders， fifth edition （DSM-5）. Cognitive function was evaluated using the Chinese Brief Cognitive Test （C-BCT）， patients were categorized into four groups： normal cognition （n=28）， mild impairment （n=28）， moderate impairment （n=47）， and severe impairment （n=34）. Fasting venous blood samples were collected， and serum TBA level was quantified using an enzymatic cycle assay. Spearman correlation analysis was ultilized to determine the relationship between serum TBA level， overall cognitive function， and specific cognitive domains. Binary Logistic regression model was used （adjusting for covariates such as age， gender， and disease duration） to analyze the impact of serum TBA level on overall and individual cognitive functions. The predictive value of serum TBA level for overall cognitive impairment was evaluated using receiver operating characteristic （ROC） curve. ResultsSerum TBA levels differed significantly among the four groups （H=18.677， P<0.01）. Specifically， serum TBA levels in both the moderate and severe cognitive impairment groups were significantly higher than those in the normal cognitive group （adjusted P<0.01）. Serum TBA level was positively correlated with the severity grading of overall cognitive impairment （r_s=0.354， P<0.05）， and negatively correlated with T-scores on the trail making test （r_s=-0.328， P<0.05）， continuous performance test （r_s=-0.247， P<0.05）， digit span （r_s=-0.265， P<0.05）， and symbol coding （r_s=-0.221， P<0.05）. Binary Logistic regression analysis identified serum TBA level as an independent risk factor for overall cognitive impairment （OR=1.322， 95% CI： 1.021 - 1.713， P=0.034）， with a particularly robust predictive ability for impaired information processing speed （OR=1.325， 95% CI： 1.057 - 1.661， P=0.015）. The area under ROC curve （AUC） for serum TBA level in predicting overall cognitive impairment was 0.738， with a sensitivity of 60.61% and a specificity of 78.64%. ConclusionIn patients with stable schizophrenia， elevated serum TBA levels are associated with worse overall cognitive function， as well as deficits in information processing speed， attention， working memory， and executive function. Serum TBA serves as an independent risk factor and exhibits moderate predictive value for overall cognitive impairmen，particularly in the domain of information processing speed. ［Funded by Yancheng Municipal Health Commission Medical Research Project （number， YK2024141）］

In recent years， the incidence of depression among adolescents has increased significantly， becoming a serious global public health problem. There is a close relationship between adolescent depression and lipid metabolism abnormalities. However， the mechanisms underlying this association have not been fully elucidated. This article provides a review of the mechanisms and interventions linking adolescent depression and lipid metabolism abnormalities， aiming to offer new ideas for interventions in adolescent depression. Using computerized searches of the China National Knowledge Infrastructure （CNKI）， Wanfang Data， PubMed， and Web of Science， studies on the mechanisms and interventions related to adolescent depression and lipid metabolism were collected， with the search period extending up to October 10， 2025. Two researchers independently conducted literature screening and extracted basic information from the included studies. A total of 12 original studies were included. The results indicate that adolescent depression is associated with certain lipid metabolites. Neurobiological factors， immune inflammation， oxidative stress， and gut microbiota imbalance play important roles in this association. In addition， lipid metabolites such as omega-3 polyunsaturated fatty acids （ω-3 PUFAs） have a significant ameliorating effect on adolescent depression. ［Funded by Shenzhen Fund for Guangdong Provincial High-level Clinical Key Specialties （number， SZGSP013）； Shenzhen Science and Technology Program （number， 20210617155253001）］