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.

[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。

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）］

ObjectiveTo investigate the effect of repetitive peripheral magnetic stimulation (rPMS) combined with upper limb intelligent robotic training on muscle tension, motor function and cortical excitability in children with unilateral spastic cerebral palsy (USCP). MethodsFrom March, 2023 to December, 2024, 90 children with USCP admitted to Children's Hospital of Soochow University were selected and randomly divided into control group (n = 30), rPMS group (n = 30) and combined group (n = 30). The control group received conventional occupational therapy. The rPMS group received rPMS intervention followed by conventional occupational therapy. The combined group received rPMS followed by upper limb intelligent robot training, for four weeks. Before and after treatment, muscle tension of biceps brachii was assessed using the modified Ashworth Scale (MAS); upper limb motor function was evaluated using the Fugl-Meyer Assessment-Upper Extremity (FMA-UE) and upper limb intelligent parameters; and cortical excitability was measured using transcranial magnetic stimulation (TMS), including resting motor threshold (RMT) and motor-evoked potential (MEP) amplitude of the affected hemisphere. ResultsAfter treatment, MAS grades improved in all groups (|Z| > 3.523, P < 0.001), and the improvement in the combined group was superior to that in the control group (P < 0.05). Significant intra-group (F > 65.21, P < 0.001), inter-group (F > 17.94, P < 0.001) and interaction effects (F > 5.36, P < 0.01) were observed in FMA-UE scores, upper limb intelligent parameters and TMS parameters. Post Hoc analysis showed that the combined group demonstrated significantly greater improvements in FMA-UE scores, upper limb intelligent parameters, and TMS parameters compared with both the control and rPMS groups (all P < 0.01). Except for FMA-UE scores, the rPMS group showed significantly greater improvements than the control group in upper limb intelligent parameters (mechanical feedback, trajectory, and range of motion) and TMS parameters (RMT and MEP amplitude) (P < 0.05). ConclusionrPMS combined with upper limb intelligent robotic training can reduce upper limb muscle tension, improve motor function, and enhance cortical excitability in children with USCP.

ObjectiveTo investigate the molecular mechanisms by which Wenyang Jiedu granules （WYJD） alleviate influenza A virus （IAV）-induced pneumonia based on single-cell transcriptome sequencing. MethodsThirty female BALB/c mice were randomly divided into a blank control group （Control）， IAV group， and WYJD low-， medium-， and high-dose groups （WYJD-L， WYJD-M， WYJD-H； 2.925， 5.85， 11.7 g·kg^-1， n=6）. Except for the Control group， all other groups were intranasally inoculated with IAV subtype H1N1 （A/PR/8/34） to establish an infection model. Two hours after modeling， drug administration was initiated and continued for 5 consecutive days， with daily monitoring of body weight and general condition. On day 6， mice were sacrificed and samples were collected. Lung index was calculated， and histopathological examination of lung tissue was performed. Lung tissues from the Control， IAV， and WYJD-H groups were subjected to single-cell transcriptome sequencing （n=3）， focusing on type I alveolar epithelial cells （AT1） to analyze changes in gene expression and signaling pathways. Western blot was used to detect the expression changes of relevant proteins to validate the single-cell sequencing results. ResultsCompared with the Control group， the IAV group exhibited significantly decreased body weight （P<0.05） and significantly increased lung index （P<0.05）. Compared with the IAV group， all WYJD-treated groups exhibited significantly increased body weight （P<0.01） and significantly decreased lung index （P<0.01）. Single-cell sequencing analysis revealed that WYJD inhibited overactivation of interferon and inflammatory signaling pathways in AT1 cells after IAV infection， including interferon-γ response， interferon-α response， tumor necrosis factor-α/nuclear factor-κB （TNF-α/NF-κB）， and interleukin-6/Janus kinase/signal transducer and activator of transcription 3 （IL-6/JAK/STAT3） pathways. Compared with the Control group， the number of AT1 cells in the IAV group showed a decreasing trend. Compared with the IAV group， the WYJD-H group showed an increasing trend， although neither difference was statistically significant. Further analysis of AT1 cell subpopulation gene expression showed that， compared with the Control group， the IAV group exhibited increased expression of pro-apoptotic genes FAS cell surface death receptor （FAS） and cyclin-dependent kinase inhibitor 1A （CDKN1A）， a significant increase in tumor protein p53 （Tp53） expression （P<0.05）， and significant decreases in expression of the AT1 marker gene advanced glycosylation end-product-specific receptor （AGER） and membrane structural gene caveolin1 （CAV1） （P<0.05， P<0.01）. Compared with the IAV group， the WYJD-H group showed significantly decreased expression of FAS， CDKN1A， and Tp53 （P<0.05， P<0.01）， and significantly increased expression of AGER and CAV1 （P<0.05， P<0.01）. Regarding interferon response-related genes， compared with the Control group， the IAV group showed increased expression of interferon-stimulated gene 15 （ISG15）， interferon-induced protein with tetratricopeptide repeats 3 （IFIT3）， signal transducer and activator of transcription 2 （STAT2）， bone marrow stromal cell antigen 2 （BST2）， and C-X-C motif chemokine ligand 10 （CXCL10）， with a significant increase in 2′，5′-oligoadenylate synthetase-like protein 1 （OASL1） （P<0.05）. Compared with the IAV group， the WYJD-H group showed significantly decreased expression of all the above genes， with highly significant differences for ISG15， IFIT3， STAT2， BST2， and OASL1 （P<0.01）， and a significant difference for CXCL10 （P<0.05）. Among inflammation-related genes， compared with the Control group， the IAV group showed significantly increased expression of intercellular adhesion molecule 1 （ICAM1）， tumor necrosis factor alpha-induced protein 3 （TNFAIP3）， keratin 8 （KRT8）， tumor necrosis factor receptor superfamily member 1A （TNFRSF1A）， and TNFRSF1B （P<0.01）， and increased expression of NFKBIA， a negative regulator of NF-κB （P<0.05）. Compared with the IAV group， the WYJD-H group showed significantly decreased expression of KRT8 and TNFRSF1B （P<0.05）， while ICAM1， NFKBIA， TNFAIP3， and TNFRSF1A showed decreasing trends without statistical significance. Western blot validation showed that， compared with the Control group， protein expression levels of ISG15， FAS， p53， and phosphorylated p65 （p-p65） in lung tissue of the IAV group were significantly increased （P<0.05， P<0.01）. Compared with the IAV group， the WYJD-H group showed significantly decreased expression of these proteins （P<0.05， P<0.01）. ConclusionWYJD may alleviate viral pneumonia by targeting gene expression in AT1 cells， inhibiting overactivated interferon and inflammatory signaling pathways after IAV infection， and downregulating pro-apoptotic signaling， thereby reducing alveolar epithelial injury.

ObjectiveThis paper aims to observe the syndrome improvement and negative antigen conversion rate of Qingxuan Daozhi formula in the treatment of influenza in children （heat accumulation in the lung and stomach syndrome）. MethodsThrough a multi-center randomized controlled methodology design，confirmed influenza cases were collected from October 2022 to April 2023 in the pediatrics department of eight hospitals，such as Dongfang Hospital of Beijing University of Chinese Medicine. A total of 180 children with influenza and heat accumulation in the lung and stomach syndrome conforming to the standard were recruited through the clinic. The sick children meeting the inclusion criteria were randomly divided into groups by a block-randomized method. The children in the experimental group were treated with Qingxuan Daozhi formula for five days，and those in the control group were treated with Oseltamivir Phosphate Granules for five days. The primary efficacy indicator was the negative conversion rate of influenza antigen detection. Secondary efficacy indicators were the Canadian acute respiratory illness and flu scale （CARIFS） and the incidence of complications，severe cases， and critical cases. Follow-up observation was conducted on the day of enrollment，48 hours after medication，72 hours after medication， and （6+1） d after medication. ResultsOne hundred and eighty participants were randomly assigned to the experimental group （90 cases） or the control group （90 cases）. All participants were followed up during the study. Comparison of influenza antigen detection results in the primary efficacy indicators showed that the average time of negative influenza antigen conversion in the experimental group was （5.29±1.25） d，and that in the control group was （5.40±1.68） d，without a statistically significant difference. After five days of intervention，52 cases in the experimental group and 51 cases in the control group converted to negative，without a statistically significant difference. CARIFS score results in the secondary efficacy indicators showed that during 72 hours after intervention，there were statistically significant differences between the experimental group and the control group in three dimensions， including headache，muscle soreness， and the need for extra care （P<0.05）. On the （6+1） days after the intervention，the differences in both the experimental group and the control group were statistically significant in 10 dimensions， including sore throat，bad sleep，uncomfortable feeling，poor spirit and fatigue，crying more than usual，the need for extra care，symptom，function，influence on parents，and total score （P<0.05）. The comparison results within the group in the dimensional scores of symptom， function， and influence on parents，as well as the CARIFS total score showed that with the delay of follow-up time，scores of both groups decreased significantly，with a statistically significant difference （P<0.01）. Inter-group comparison results showed that the mean score of the experimental group was higher than that of the control group at the time of enrollment. With the progress of intervention，the score of the experimental group was significantly decreased compared with that of the control group. At the end of follow-up，the mean score of the experimental group was lower than that of the control group，with no statistically significant difference. In terms of the incidence of complications，severe cases， and critical cases， there were no complications，severe cases， and critical cases in the two groups，without a statistically significant difference. ConclusionThe symptom improvement effect and negative antigen conversion rate of Qingxuan Daozhi formula in the treatment of influenza in children （heat accumulation in the lung and stomach syndrome） are not inferior to Oseltamivir Phosphate granules， and children's acceptance is better. It can be more widely used in clinical treatment of influenza in children （heat accumulation in the lung and stomach syndrome）.

The International Council for Harmonisation of Technical Requirements for Pharmaceuticals for Human Use （ICH） issued the ICH E6（R3）： Guideline for Good Clinical Practice on January 14， 2025， which will enhance the speed and quality of global clinical trials， including those in China. As the ethical， scientific and quality standards for global drug clinical trials， the highlights of the revision in the ICH E6 （R3） include encouraging innovation to improve efficiency and quality， motivating research participants to participate in the design and implementation of clinical trials throughout the process， emphasizing quality originating from design and based on the quality management of risks， as well as underlining proportionality and standalone chapter to data governance. ICH E6 （R3） adopts an appendix and appendix structure， enabling future revisions to be more convenient and efficient. ICH E6 （R3） restructures the principles section， adding two new principles and reducing the total from 13 to 11， while incorporating extensive explanatory notes. Major revisions also encompass multiple aspects， including regular review by ethics committees to ensure the safety， rights and interests， and well-being of research participants； diversification of informed consent methods， refinement of its processes， and clarification of detailed rules for minors’ consent； qualifications， authorization， and oversight of investigators and their service providers； risk-proportionate design and implementation by sponsors； joint data governance by investigators and sponsors； and the addition and revision of terms， along with updates to three appendices. The design， implementation， and review of drug clinical trials in China are increasingly aligning with international standards. ICH E6 （R3） will accelerate the revision of China’s Guideline for Good Clinical Practice， promote the speed and quality of drug research and development， and further facilitate the internationalization of China’s new drug research and development.

Work serves as a critical means of obtaining resources, facilitating personal growth, realizing self-worth, and engaging in social interactions. However, work-related diseases pose significant threats to workers’ health and productivity, and impose considerable economic burdens. This article categorized work-related diseases into six major types, including musculoskeletal disorders, mental and behavioral disorders, cardiovascular and metabolic diseases, digestive system diseases, reproductive system diseases, and non-specific respiratory diseases, and summarized their risk factors, assessment methods, policy regulation, and prevention and control measures. Current research in this field predominantly relies on cross-sectional studies, which present limitations in causal inference and potential risks of bias. Future studies should expand sample sizes, optimize research designs, and establish multidimensional evaluation systems to comprehensively assess the health and economic impacts of work-related diseases. It is recommended to enhance the translation of research findings into practice, thereby providing a scientific basis for the occupational health protection system and promoting the well-being and sustainable development of the working population.

Objective To investigate the temporal changes in pathological damage and macrophage polarization in liver and spleen tissues of mice infected with Angiostrongylus cantonensis, and to preliminarily unravel the peripheral immune responses during the early stage of A. cantonensis infection. Methods Forty female BALB/c mice at ages of 6 to 8 weeks were randomly divided into four groups, including the control group and 7-, 14-, and 21-day infection groups, with 10 mice in each group. Each mouse in the infection groups was inoculated with 30 third-stage (L3) larvae of A. cantonensis by oral gavage, and five mice were randomly selected from each infection group on days 7, 14, and 21 post-infection, while mice in the control group were given the same volume of physiological saline and five mice were randomly selected from the control group on the day of oral gavage. Mouse liver and spleen tissues were sampled. The histopathological changes of mouse liver and spleen tissues were observed using hematoxylin and eosin (HE) staining, and the percentage of positive staining area and the co-localization positive rates of the macrophage surface antigens F4/80, CD86, and CD206 were quantified in mouse liver and spleen tissues using immunohistochemical and immunofluorescence staining. In addition, five mice were collected from each infection group on days 7, 14, and 21 post-infection, and five mice were collected from the control group on the day of oral gavage. Mouse liver and spleen tissues were sampled for detection of macrophage markers CD86 and CD206 and macrophage phenotyping using flow cytometry, and the expression of M1 macrophage markers, including inducible nitric oxide synthase (Nos2), tumor necrosis factor-α (TNF-α), interleukin-1β (IL-1β) and M2 markers, including arginase 1 (Arg1), mannose receptor C-type 1 (Mrc1) and chitinase-like protein 3 (Chil3) was quantified in mouse liver and spleen tissues using real-time quantitative PCR (RT-qPCR) assay. Results Proliferative lesions of the hepatocyte were observed in mouse liver tissues and the follicular structures of the mouse spleen white pulp were disrupted 21 days post-infection with A. cantonensis. Immunohistochemical staining showed that there were significant differences in the percentages of F4/80, CD86 and CD206 positive staining areas in the liver and spleen tissues among the four groups of mice (F = 242.40, 197.14, 183.19, 157.65, 242.35 and 146.24; all P values < 0.001), and the percentages of positive staining in the liver and spleen tissues of mice in the 14-day infection group [(4.45 ± 0.51)%, (3.74 ± 0.67)%, (8.32 ± 0.72)%, (16.56 ± 1.14)%, (11.62 ± 0.52)%, and (8.29 ± 0.72)%, respectively] and the 21-day infection group [(3.70 ± 0.11)%, (3.22 ± 0.43)%, (11.53 ± 1.03)%, (12.59 ± 1.05)%, (9.02 ± 0.83)%, and (11.67 ± 1.10)%, respectively] were higher than in the control group [(0.35 ± 0.16)%, (0.40 ± 0.02)%, (0.93 ± 0.05)%, (2.78 ± 0.26)%, (2.33 ± 0.20)%, and (1.85 ± 0.20)%, respectively] (all P values < 0.05). Immunofluorescence staining showed significant differences in the positive rates of F4/80 co-localization with CD86 and CD206 in mouse liver and spleen tissues among the four groups (F = 24.42, 25.28, 54.51 and 130.55; all P values < 0.001). Flow cytometry detected significant differences in the proportions of CD86⁺ and CD206⁺ macrophages in mouse liver and spleen tissues among the four groups (F = 67.98, 18.41, 29.77, 172.80; all P values < 0.001), and the proportions of CD206⁺ macrophages in the liver and spleen of the 21-day infection group were significantly higher than those in the control group [(9.25 ± 2.55)% vs (3.83 ± 0.72)%, and (4.22 ± 0.56)% vs (0.47 ± 0.18)%, respectively] (both P values < 0.05). In addition, RT-qPCR assay quantified significant differences in the relative mRNA expression of M1 macrophage markers (IL-1β, TNF-α and Nos2) and M2 macrophage markers (Arg1, Chil3 and Mrc1) in mouse liver and spleen tissues among the four groups (F = 41.30, 31.82, 199.33, 19.96, 62.01, 119.76, 23.67, 95.90, 72.27, 82.59, 123.41 and 29.75; all P values < 0.05). Conclusions A. cantonensis infection may cause progressive pathological damage in mouse liver and spleen tissues, accompanied by dynamic temporal changes in macrophage polarization. M1 macrophage polarization predominates at the early stage of A. cantonensis infection and shifts towards M2 polarization at the later stages, suggesting that M2 polarization may participate in immune regulation at late stages of A. cantonensis infection by suppressing excessive inflammatory responses and promoting tissue repair.

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.