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.

This paper systematically reviews the current status of integrated traditional Chinese and western medicine in the treatment of Helicobacter pylori （Hp） infection， as well as recent progress in clinical and basic research both in China and internationally. It summarizes the advantages of traditional Chinese medicine （TCM） in Hp infection management， including improving Hp eradication rates， enhancing antibiotic sensitivity， reducing antimicrobial resistance， decreasing drug-related adverse effects， and ameliorating gastric mucosal lesions. These advantages are particularly evident in patients who are intolerant to bismuth-containing regimens， those with refractory Hp infection， and individuals with precancerous gastric lesions. An integrated， whole-process management approach and individualized， staged comprehensive treatment strategies combining TCM and western medicine are proposed for Hp infection. Future prevention and control of Hp infection should adopt an integrative Chinese-western medical strategy， emphasizing prevention， strengthening primary care， implementing proactive long-term monitoring， optimizing screening strategies， and advancing the development of novel technologies and mechanistic studies of Chinese herbal interventions. These efforts aim to provide a theoretical basis and practical pathways for the establishment and improvement of Hp infection prevention and control systems.

Childhood obesity has become a global public health issue. Current research indicates that early life obesogen exposure has emerged as a significant risk factor for childhood obesity. While obesogens have been confirmed to influence the development and progression of childhood obesity through mechanisms such as endocrine disruption and epigenetic programming, controversies remain regarding the establishment of causal relationships, assessment of combined exposures, and validation of transgenerational effects in humans. In recent years, novel approaches including multi-omics technologies, exposome-based analysis, and multigenerational cohort studies have integrated dynamic biomarker monitoring with analyses of social-environmental interactions, offering new perspectives and methodologies for constructing a systematic "exposure-mechanism-outcome" research framework. This article reviews literature from PubMed and Web of Science up to August 2025 on the association between early life obesogen exposure and childhood obesity, summarizing evidence on the health effects of early life obesogen exposure, major exposure pathways and internal exposure assessment, interactions and amplifying effects of social and environmental factors, as well as the biological mechanisms underlying obesogen action. It further examines current research frontiers and challenges, aiming to provide a theoretical foundation for early prevention and precision intervention of childhood obesity.

Objective: To investigate the late identification and its influencing factors of newly reported HIV/AIDS cases in Linhai City, Zhejiang Province from 2015 to 2024, so as to provide a basis for formulating targeted AIDS prevention and control strategies. Methods: Data on newly reported HIV/AIDS cases in Linhai City from 2015 to 2024, including demographic characteristics and detection modes, were collected through the HIV/AIDS Comprehensive Control System of the Chinese Disease Prevention and Control Information System. The new identification rate and late identification proportion of HIV/AIDS cases were analyzed. The average annual percent change (AAPC) was used to assess trends in both the new identification rate and late identification proportion from 2015 to 2024. Multivariable logistic regression model was used to analyze the influencing factors for late identification among HIV/AIDS cases. Results: A total of 589 newly reported HIV/AIDS cases were documented in Linhai City from 2015 to 2024. The new identification rate declined from 5.08/105 in 2015 to 3.53/105 in 2024 (AAPC=-6.161%, P<0.05). Among them, 225 cases were late identified. After excluding 4 cases with inferred late identification, the late identification proportion increased from 24.53% in 2015 to 58.97% in 2024 (AAPC=7.595%, P<0.05). Multivariable logistic regression analysis indicated that age ≥25 years (25~<50 years, OR=3.569, 95%CI: 1.567-8.130; ≥50 years, OR=8.683, 95%CI: 3.440-21.917) and passive detection (OR=1.730, 95%CI: 1.022-2.928) were associated with a higher risk of late identification. In contrast, being married or having a spouse (OR=0.565, 95%CI: 0.332-0.960) was associated with a lower risk of late identification. Conclusions The new identification rate of HIV/AIDS cases in Linhai City from 2015 to 2024 showed a downward trend, while the proportion of late identification exhibited an upward trend. Age, marital status, and detection mode were identified as influencing factors for late identification among HIV/AIDS cases.

ObjectiveTo investigate the mechanisms by which Renshentang treats atherosclerosis （AS） in mice， focusing on the regulation of endothelial inflammatory responses mediated by transient receptor potential vanilloid subtype 1 （TRPV1）. MethodsAn AS model was established in apolipoprotein E knockout （ApoE^-/-） mice fed a high-fat diet. The mice were randomly divided into a simvastatin group （0.02 g·kg^-1·d^-1） and low-， medium-， and high-dose Renshentang groups （1.77， 3.54， 7.08 g·kg^-1·d^-1）， with 12 mice in each group. ApoE^-/- mice were fed a high-fat diet and treated simultaneously. C57BL/6J mice fed a normal diet served as the normal group （n=9）. After continuous administration for 12 weeks， mice were anesthetized and the aortas were collected. Oil Red O staining was used to observe lipid plaque formation in the aorta. Hematoxylin-eosin （HE） staining was performed to examine pathological changes in the aortic root. Immunohistochemistry was used to analyze the levels of pro-inflammatory factors tumor necrosis factor-α （TNF-α） and interleukin-1β （IL-1β）， as well as the expression of TRPV1， phosphorylated phosphoinositide 3-kinase （p-PI3K）， and phosphorylated protein kinase B （p-Akt） in the aortic root. Real-time quantitative polymerase chain reaction （Real-time PCR） was used to detect endothelial nitric oxide synthase （eNOS） mRNA expression in the aorta， and Western blot was used to detect TRPV1 protein expression. ResultsCompared with the normal group， the model group showed a significant increase in aortic plaque formation （P<0.01） and significantly elevated levels of TNF-α and IL-1β in the aortic root （P<0.01）. The expression levels of TRPV1， p-PI3K， and p-Akt were decreased （P<0.05， P<0.01）， and eNOS mRNA expression was reduced （P<0.05， P<0.01）. Compared with the model group， all Renshentang groups significantly reduced aortic plaque formation （P<0.01）， significantly decreased TNF-α and IL-1β levels （P<0.01）， and markedly increased the expression levels of TRPV1， p-PI3K， p-Akt， and eNOS mRNA （P<0.05， P<0.01）. ConclusionRenshentang may inhibit endothelial inflammation and suppress the formation of AS by increasing TRPV1 protein expression and up-regulating the PI3K/Akt/eNOS signaling pathway， which may be one of the molecular mechanisms underlying its therapeutic effect against AS.

Objective To evaluate the radiation dose levels induced by secondary neutrons at different locations inside proton therapy treatment rooms, and analyze the distribution characteristics of neutron energy spectra by combining experimental measurements with simulations, and to provide a theoretical basis and technical support for radiation protection design and management in proton therapy. Methods Multiple representative measurement points were established in the treatment rooms of two hospital-based proton therapy centers. The DIAMON neutron spectrometer was employed to perform in-situ measurements of secondary neutron doses and energy spectra. Three-dimensional simulation models of treatment rooms were constructed using the FLUKA code to simulate the generation and transport of secondary neutrons. Results Measurements showed that the neutron dose was highest near the target region, reaching up to 4293.750 µSv/h. The doses at the maze entrance were the next highest, ranging from 422.091 to 489.268 µSv/h, while the doses in the middle section of the maze ranged from 2.860 to 6.727 µSv/h. The neutron energy spectra exhibited a triple-peak pattern. Conclusion Significant accumulation of secondary neutrons was observed near the target and in the maze regions during proton therapy, with intermediate-energy neutrons being the dominant dose contributor. The consistency between measurements and simulations validated the reliability of the model, which can provide a basis for optimizing treatment room shielding and controlling occupational exposure for staff.

ObjectiveBased on the clinical characteristics of chronic gouty arthritis （CGA） in both traditional Chinese and western medicine， this study aims to systematically evaluate the clinical concordance of existing CGA animal models， providing recommendations for establishing animal models that align with the pathological characteristics of CGA and the manifestations of traditional Chinese medicine syndromes. MethodsBy comprehensively retrieving Chinese and international databases such as China National Knowledge Infrastructure， Wanfang， VIP Chinese Science and Technology Periodical Database （VIP）， and PubMed， all relevant literature on CGA animal models was collected. Based on the guidelines， the diagnostic criteria of both traditional Chinese and western medicine were summarized and organized. The evaluation indicators for the CGA model were constructed with reference to existing evaluation modes， and the CGA animal models were analyzed to systematically evaluate the clinical concordance of existing models. ResultsThe current methods used to construct CGA animal models mainly include monosodium urate crystal induction， high-protein diet induction （poultry lack urate oxidase）， and high-fat diet combined with urate oxidase inhibitors and joint injection. Based on 11 pieces of included literature， the traditional Chinese and western medicine scoring data of each model were extracted， and the average scoring values of all models were ultimately calculated. The results show that the average clinical concordances of existing CGA animal models in both traditional Chinese and western medicine are 43.33% and 64.44%， respectively. Among them， the model with the highest clinical concordance rate is the one with a high-fat diet combined with potassium oxonate to induce hyperuricemia plus joint injection， achieving 83.33% clinical concordance in western medicine and 60% in traditional Chinese medicine. This model aligns well with the pathogenic characteristics and pathological changes of clinical CGA. ConclusionAlthough current CGA animal models can simulate some pathological characteristics of CGA， they struggle to comprehensively reflect the complex pathological processes of CGA and the characteristics of traditional Chinese medicine syndromes. Therefore， in the future， it is necessary to establish the CGA animal models that incorporate the clinical disease and syndrome characteristics of traditional Chinese and western medicine and formulate the uniform model evaluation criteria， providing more precise tools for CGA mechanism research and the development of traditional Chinese medicine.

ObjectiveGastrodia elata has evolved ecological types with shortened rhizome internodes and diversified flower and fruit coloration in response to different altitudes. Studying the genetic mechanisms of different ecotype germplasm is significant for guiding variety breeding in different cultivation areas. MethodsThe bHLH gene family was identified based on the whole-genome datasets of G. elata f. elata and G. elata f. glauca. Subsequently， the gene family members were subject to analysis， including gene structure， chromosomal localization， cis-acting elements， gene synteny， and phylogeny. Combined with transcriptome data and quantitative Real-time PCR， the expression patterns of bHLH genes in the stems of the different G. elata ecotype germplasm were analyzed. Finally， correlation analysis was conducted between gene expression patterns and color to obtain the key bHLH genes regulating the color formation of stem. ResultsA total of 63 bHLH genes were identified in both G elata f. elata and G. elata f. glauca， unevenly distributed across 17 chromosomes and clustered into 16 subfamilies， with significant expansion in some family members. Obvious inversions of bHLH genes on the same chromosome and interchromosomal translocations were detected in the two ecotype germplasm. Among these genes， 12 bHLH genes （such as bHLH62-3 and bHLH74） were associated with the bright yellow color of G elata f. elata stem， while 9 bHLH genes （such as PIL13， UNE12， and bHLH130） were correlated with the red color of G. elata f. glauca stem. Compared to G. elata f. glauca， the bHLH48 expression level was significantly higher in flowers and scale leaves of G elata f. elata， and the bHLH62-3 expression level was significantly higher in all organs of G elata f. elata. ConclusionsFunctional pathway divergence of the bHLH family members has occurred across different chromosomes in G elata f. elata and G. elata f. glauca. Through synergism or antagonism with other genes， 21 bHLH genes participate in the coloration metabolic pathway regulation of stems， flowers， and fruits. Specifically， bHLH62-3 is involved in regulating stem color differentiation in the anthocyanin biosynthesis pathway of G. elata， thus relevant to the color formation of stem. Additionally， GebHLH48 positively regulates flowering-related pathways to promote the early-flowering phenotype of G. elata f. elata. These findings have laid the foundation for analyzing the genetic regulatory mechanisms underlying the color formation of the G. elata stem.

ObjectiveGastrodia elata has evolved ecological types with shortened rhizome internodes and diversified flower and fruit coloration in response to different altitudes. Studying the genetic mechanisms of different ecotype germplasm is significant for guiding variety breeding in different cultivation areas. MethodsThe bHLH gene family was identified based on the whole-genome datasets of G. elata f. elata and G. elata f. glauca. Subsequently， the gene family members were subject to analysis， including gene structure， chromosomal localization， cis-acting elements， gene synteny， and phylogeny. Combined with transcriptome data and quantitative Real-time PCR， the expression patterns of bHLH genes in the stems of the different G. elata ecotype germplasm were analyzed. Finally， correlation analysis was conducted between gene expression patterns and color to obtain the key bHLH genes regulating the color formation of stem. ResultsA total of 63 bHLH genes were identified in both G elata f. elata and G. elata f. glauca， unevenly distributed across 17 chromosomes and clustered into 16 subfamilies， with significant expansion in some family members. Obvious inversions of bHLH genes on the same chromosome and interchromosomal translocations were detected in the two ecotype germplasm. Among these genes， 12 bHLH genes （such as bHLH62-3 and bHLH74） were associated with the bright yellow color of G elata f. elata stem， while 9 bHLH genes （such as PIL13， UNE12， and bHLH130） were correlated with the red color of G. elata f. glauca stem. Compared to G. elata f. glauca， the bHLH48 expression level was significantly higher in flowers and scale leaves of G elata f. elata， and the bHLH62-3 expression level was significantly higher in all organs of G elata f. elata. ConclusionsFunctional pathway divergence of the bHLH family members has occurred across different chromosomes in G elata f. elata and G. elata f. glauca. Through synergism or antagonism with other genes， 21 bHLH genes participate in the coloration metabolic pathway regulation of stems， flowers， and fruits. Specifically， bHLH62-3 is involved in regulating stem color differentiation in the anthocyanin biosynthesis pathway of G. elata， thus relevant to the color formation of stem. Additionally， GebHLH48 positively regulates flowering-related pathways to promote the early-flowering phenotype of G. elata f. elata. These findings have laid the foundation for analyzing the genetic regulatory mechanisms underlying the color formation of the G. elata stem.

Objective Orosomucoid1 （ORM1） is a novel target in the quest for anti-fatigue pharmacotherapy. Preliminary investigations have illuminated oleuropein （OLE） as a promising candidate molecule, poised to enhance ORM1 expression. To elucidate the influence of OLE on ORM1 protein expression and assess its ramifications on muscle endurance. Methods The impact of OLE on ORM1 protein expressions within hepatocytes and liver tissue was meticulously quantified through Western blotting; the effects of OLE on muscle endurance were evaluated via the rotarod and forced swimming tests; glycogen content within liver and muscle tissues was determined utilizing a specialized kit; and PAS staining was employed to visualize glycogen deposition in the gastrocnemius muscle. Results OLE demonstrated a capacity to elevate ORM1 protein expression in hepatocytes in a time- and dose-dependent manner, concurrently prolonging the duration of swimming and rotarod performance in mice, also in a time- and dose-dependent manner. Furthermore, OLE augmented ORM1 expression in liver tissue, elevated serum ORM1 levels, and enhanced glycogen reserves within the liver and muscle. Conclusion OLE may serve to amplify muscle endurance by elevating ORM1 levels in vivo and augmenting glycogen stores within skeletal muscle.