Irritable bowel syndrome （IBS） is a functional bowel disorder characterized primarily by abdominal pain and altered defecation habits. In recent years， traditional Chinese medicine （TCM） has made progress in multiple aspects of IBS research and treatment， including syndrome distribution， development of TCM formulas， clinical efficacy evaluation， external therapies， and psychosocial regulation. However， it still faces challenges such as over-reliance on symptomatic manifestations rather than biomarkers for diagnostic criteria， and the lack of high-quality evidence-based data supporting the efficacy of TCM formulas in treating IBS. This paper proposed that TCM diagnosis and treatment of IBS should adhere to the strategy of integrating the holistic concept with syndrome differentiation and treatment， combining TCM external therapies such as acupuncture， moxibustion and acupoint application）， and emphasizing individualized diagnosis and treatment for psychosomatic abnormalities. Future research should integrate multi-omics technologies， artificial intelligence and other methods to deepen the understanding of the pathogenesis of IBS and the mechanisms of TCM formulas， so as to promote the standardization and internationalization of TCM in the diagnosis and treatment of IBS.

Objective To understand the status of body image disturbance and its influencing factors in patients with ankylosing spondylitis (AS), so as to provide a scientific basis for the clinical management of AS. Methods A total of 353 AS patients admitted from January 2022 to December 2024 were selected as research subjects. Chinese version of Body Image Disturbance Questionnaire (BIDQ) was used to investigate the body image disturbance in AS patients. Single factor analysis was performed by t test and analysis of variance, and multiple factors were analyzed by multivariate linear regression. Results The total score of BIDQ in 342 AS patients was (25.01±4.22). Multivariate linear regression analysis results showed that self-paid medical expense, nighttime VAS score and negative emotion PANAS score could positively predict body image disturbance in AS patients (standardized regression coefficient=0.413, 0.413, 0.460, P<0.05), and PSSS score, positive emotion PANAS score and exercise management CDSSM score could negatively predict body image disturbance (standardized regression coefficient=-0.245, -0.134, -0.247, P<0.05). Conclusion The body image disturbance in AS patients is worthy of clinical attention. Nighttime pain, negative emotion and self-paid medical treatment can increase the risk of body image disturbance. Positive emotion, social support and high self-management level of exercise behavior can reduce the formation of body image disturbance, which can provide new ideas for clinical management of AS patients.

OBJECTIVE To compare the efficacy and safety of evolocumab and probucol in patients with ultra-high-risk atherosclerotic cardiovascular disease （ASCVD） following percutaneous coronary intervention （PCI）. METHODS A retrospective analysis was conducted on 156 ultra-high-risk ASCVD patients who underwent PCI in our institution between January 1， 2023 and December 31， 2024. According to the lipid-lowering regimen， the patients were categorized into evolocumab group （ n ＝86） and probucol group （ n ＝70）. Changes in lipid parameters [total cholesterol （TC）， low-density lipoprot ein cholesterol （LDL-C）， high-density lipoprotein cholesterol （HDL-C）， triglycerides， lipoprotein （a）， and lipid goal achievement rate ] ， inflammatory markers [interleukin-6 （IL-6） and C-reactive protein （CRP） ] ， and cardiac function indices （left ventricular ejection fraction， left ventricular end-systolic diameter， left ventricular end-diastolic diameter， and N-terminal pro-B-type natriuretic peptide） were compared between two groups at baseline and after 6 months of treatment. The incidence of adverse clinical events during treatment， including acute myocardial infarction， in-stent restenosis， acute heart failure， cerebral hemorrhage， and stroke， was also evaluated. RESULTS No statistically significant differences were observed between the two groups at baseline （ P ＞0.05）. After 6 months of treatment， both groups demonstrated significant improvements in lipid profiles （except HDL-C） and inflammatory markers compared to those at baseline （ P ＜0.05）. The evolocumab group exhibited greater reductions in TC， LDL-C， IL-6， and CRP， along with a higher lipid target achievement rate， compared with the probucol group （ P ＜0.05）. There were no statistically significant differences in the cardiac function-related indicators before and after treatment between the two groups， nor in the incidence of adverse events during the treatment （ P ＞0.05）. CONCLUSIONS For ultra-high-risk ASCVD patients after PCI， both of the above treatment options are associated with improvements in blood lipid and inflammatory response， with good safety during short-term follow-up. Evolocumab shows superior efficacy in TC， LDL-C and inflammatory markers reduction and lipid target achievement， compared to probucol.

ObjectiveThis paper aims to find the identified and validated clinical biomarker data building upon a clinical study of early-phase phase Ⅱ and investigate the correlation analysis of Huanglian Jiedu Wan on syndrome improvement and clinical biomarkers in the treatment of "excess heat-toxicity" based on a machine learning model. Additionally， the effective prediction of clinical biomarker values for the main symptoms of the "excess heat-toxicity" syndrome was assessed. MethodsA total of 229 patients meeting the inclusion criteria for "excess heat-toxicity" syndrome were randomly divided into the Huanglian Jiedu Wan group and the placebo group. Syndrome score transition matrices were constructed for the Huanglian Jiedu Wan group and the placebo group based on three main symptoms of "excess heat-toxicity" syndrome， such as oral ulcers， sore throat， and gum swelling and pain. Data from the patients with these three syndromes were also integrated for an overall analysis. The corresponding syndrome score transition matrices were further constructed to visualize symptom change trends of the patients in the two groups via heatmaps. Based on the identified and validated clinical biomarkers related to inflammation， oxidative stress， and energy metabolism in the early phase， Spearman correlation analysis was employed to analyze and evaluate the associations between clinical biomarkers and syndrome improvement. Key clinical biomarkers reflecting the effect of Huanglian Jiedu Wan were screened through the comparison of differences between groups. An extreme gradient boosting （XGBoost） algorithm was used to develop a prediction model for main symptom classification， with classification performance evaluated through 10-fold cross-validation. Feature importance analysis was applied to identify variables with the greatest contribution to the prediction result. ResultsThe syndrome transition matrix results indicated that the Huanglian Jiedu Wan group showed a superior effect to the placebo group in improving oral ulcers， sore throat， and overall symptoms， with significant effects observed especially in sore throat and overall symptom analyses （P<0.01）. Spearman correlation analysis revealed that several clinical biomarkers positively correlated with "excess heat-toxicity" syndrome and its main symptom improvement， were also called "heat-related biomarkers"， including succinic acid， α-ketoglutaric acid， glycine， lactic acid， adenosine monophosphate （AMP）， tumor necrosis factor-α （TNF-α）， interferon-γ （IFN-γ）， interleukin-1β （IL-1β）， interleukin-4 （IL-4）， interleukin-6 （IL-6）， interleukin-8 （IL-8）， interleukin-10 （IL-10）， and so on. Conversely， clinical biomarkers negatively correlated with symptom severity， were also called "heat-clearing related biomarkers" after administration of Huanglian Jiedu Wan， including malic acid， fumaric acid， cis-aconitic acid， adrenocorticotropic hormone （ACTH）， IL-1β， IL-4， IL-8， succinic acid， and citric acid. The XGBoost classification model using all 52 biomarkers as variables achieved an average test accuracy of 0.754 and an average F1 score of 0.777. Feature importance analysis identified the scores of glutamic acid in saliva and IL-6 were the highest in all the variables， with importance scores of 0.081 and 0.080， respectively. After screening out 14 key variables and optimizing the parameters， model performance improved to an average accuracy of 0.758 and an F1 score of 0.798. Feature importance analysis further determined that the glutamic acid in saliva and IL-6 showed obvious changes after screening the variables， confirming the good syndrome prediction ability of the model constructed by these key clinical biomarkers. ConclusionThis study systematically elucidates the correlation between syndrome improvement and clinical biomarkers of Huanglian Jiedu Wan in the treatment of "excess heat-toxicity" syndrome. An XGBoost classification model based on key clinical biomarkers is successfully established， achieving effective prediction of the symptoms related to the "excess heat-toxicity" syndrome such as oral ulcers and sore throat and providing a new insight for objective identification of traditional Chinese medicine syndromes.

ObjectiveThis paper aims to find the identified and validated clinical biomarker data building upon a clinical study of early-phase phase Ⅱ and investigate the correlation analysis of Huanglian Jiedu Wan on syndrome improvement and clinical biomarkers in the treatment of "excess heat-toxicity" based on a machine learning model. Additionally， the effective prediction of clinical biomarker values for the main symptoms of the "excess heat-toxicity" syndrome was assessed. MethodsA total of 229 patients meeting the inclusion criteria for "excess heat-toxicity" syndrome were randomly divided into the Huanglian Jiedu Wan group and the placebo group. Syndrome score transition matrices were constructed for the Huanglian Jiedu Wan group and the placebo group based on three main symptoms of "excess heat-toxicity" syndrome， such as oral ulcers， sore throat， and gum swelling and pain. Data from the patients with these three syndromes were also integrated for an overall analysis. The corresponding syndrome score transition matrices were further constructed to visualize symptom change trends of the patients in the two groups via heatmaps. Based on the identified and validated clinical biomarkers related to inflammation， oxidative stress， and energy metabolism in the early phase， Spearman correlation analysis was employed to analyze and evaluate the associations between clinical biomarkers and syndrome improvement. Key clinical biomarkers reflecting the effect of Huanglian Jiedu Wan were screened through the comparison of differences between groups. An extreme gradient boosting （XGBoost） algorithm was used to develop a prediction model for main symptom classification， with classification performance evaluated through 10-fold cross-validation. Feature importance analysis was applied to identify variables with the greatest contribution to the prediction result. ResultsThe syndrome transition matrix results indicated that the Huanglian Jiedu Wan group showed a superior effect to the placebo group in improving oral ulcers， sore throat， and overall symptoms， with significant effects observed especially in sore throat and overall symptom analyses （P<0.01）. Spearman correlation analysis revealed that several clinical biomarkers positively correlated with "excess heat-toxicity" syndrome and its main symptom improvement， were also called "heat-related biomarkers"， including succinic acid， α-ketoglutaric acid， glycine， lactic acid， adenosine monophosphate （AMP）， tumor necrosis factor-α （TNF-α）， interferon-γ （IFN-γ）， interleukin-1β （IL-1β）， interleukin-4 （IL-4）， interleukin-6 （IL-6）， interleukin-8 （IL-8）， interleukin-10 （IL-10）， and so on. Conversely， clinical biomarkers negatively correlated with symptom severity， were also called "heat-clearing related biomarkers" after administration of Huanglian Jiedu Wan， including malic acid， fumaric acid， cis-aconitic acid， adrenocorticotropic hormone （ACTH）， IL-1β， IL-4， IL-8， succinic acid， and citric acid. The XGBoost classification model using all 52 biomarkers as variables achieved an average test accuracy of 0.754 and an average F1 score of 0.777. Feature importance analysis identified the scores of glutamic acid in saliva and IL-6 were the highest in all the variables， with importance scores of 0.081 and 0.080， respectively. After screening out 14 key variables and optimizing the parameters， model performance improved to an average accuracy of 0.758 and an F1 score of 0.798. Feature importance analysis further determined that the glutamic acid in saliva and IL-6 showed obvious changes after screening the variables， confirming the good syndrome prediction ability of the model constructed by these key clinical biomarkers. ConclusionThis study systematically elucidates the correlation between syndrome improvement and clinical biomarkers of Huanglian Jiedu Wan in the treatment of "excess heat-toxicity" syndrome. An XGBoost classification model based on key clinical biomarkers is successfully established， achieving effective prediction of the symptoms related to the "excess heat-toxicity" syndrome such as oral ulcers and sore throat and providing a new insight for objective identification of traditional Chinese medicine syndromes.

Work-related musculoskeletal disorders (WMSDs) represent a significant occupational health challenge among healthcare professionals globally, posing substantial threats to physical and mental well-being as well as work sustainability. Adopting preventive behaviors—including ergonomic postural adjustments, optimized work-rest scheduling, proper use of protective and assistive equipment, and regular physical activity—is essential for mitigating the risk of WMSDs. Guided by the social ecological model, the review synthesized current evidence on the determinants of WMSDs preventive behaviors across four levels: intrapersonal characteristics, work environment conditions, interpersonal support, and policy/institutional factors. The findings suggest that higher educational attainment, favorable health-related behavioral patterns, optimized ergonomic work environments, adoption of supportive collaborative systems, strong organizational support, as well as policy safeguards facilitate preventive behavior adoption. Conversely, limited prevention-related knowledge, low risk perception, insufficient physical activity, excessive workload, lack of appropriate protective equipment, inadequate ergonomic training, a prevailing culture of presenteeism, and inadequate policy implementation constitute significant barriers. Multi-dimensional intervention strategies targeting these determinants are warranted to enhance preventive behaviors, reduce the risk of WMSDs, and strengthen occupational health protection for healthcare professionals.

Based on the thinking of programmatization and proceduralization， this study integrated traditional Chinese medicine （TCM） classic theories with modern knowledge expression technologies to construct a "formula-symptom" syndrome differentiation thinking model centered on "symptom clustering-main syndrome screening-formula adaptation"， and explored the standardization and intelligentization path of TCM syndrome differentiation and treatment. By establishing the mapping relationship model between formulas and syndromes including quantitative weight analysis of chief， deputy， assistant and envoy medicines， designing the logical hierarchical structure of formula-syndrome decision tree （application of three-level decision tree and fuzzy logic）， and formulating the procedural design of four diagnostic methods （structured collection， correlation model， and dynamic correction mechanism）， the standardization and visualization of the syndrome differentiation process are realized. This model can be transformed into the core data set for artificial intelligence training. Through ternary knowledge graph and machine learning algorithms， it can improve the repeatability of syndrome differentiation and the efficiency of diagnosis and treatment， and implement the strategy of "group model + individual modification" to balance the conflict between quantification and individualization. The core value of this model lies in promoting the objectification and precision development of TCM syndrome differentiation and treatment through the integration of traditional syndrome differentiation thinking and modern system science.

ObjectiveTo measure the distance from the surface of Fengfu （GV 16） to the deep important bony structures in children aged 4 to 8 years based on CT three-dimensional reconstruction technology， thereby providing imaging reference data for clinical acupuncture safe operations in terms of different age groups and needle insertion angles. MethodsCervical CT image data were collected from healthy children aged 4 to 8 years with five age groups （4-， 5-， 6-， 7-， 8-year-old groups）， 20 cases in each group. The images were imported into Mimics 21.0 software for three-dimensional reconstruction. The straight-line distances from the skin model surface of the Fengfu （GV 16） to the first underlying bony barrier （such as the lower edge of the occipital bone， the posterior arch of the atlas vertebra） were measured at intervals of 5° on both the transverse section （0° ± 35°） and the sagittal section （40° upward to 40° downward on the diagonal）. The correlation between the measured distance， age， and angle was analyzed. ResultsIn the transverse and sagittal sections， the measured distance from the skin surface to the underlying bone of Fengfu （GV 16） at each angle increased with age. In the transverse section， the increase was relatively small within the 0° to 20° angle range， whereas a more pronounced increase was observed when the angle exceeded 20°； at measurement angles of 30° to 35°， the distance of the skin surface to the bone at Fengfu （GV 16） in the 7- and 8-year-old groups was significantly greater than that in the 4-year-old group （P＜0.05）. In the sagittal section， the measured distance from the skin surface to the bone at Fengfu （GV 16） was shortest and changed greatly at oblique upward angles of 15° to 40° within each age group， and increased markedly at near-vertical angles of 0° to 10°； it was longest at oblique downward angles of -40° to -5° and showed relatively gradual changes. ConclusionThis study obtained the imaging distance data from Fengfu （GV 16） to the surrounding bony structures in children aged 4 to 8 years through three-dimensional modeling， finding that this distance has clear age and angle dependence， which can provide quantitative evidence for developing individualized and precise safe acupuncture schemes at Fengfu （GV 16） in pediatric clinical practice.

ObjectiveTo measure the distance from the surface of Fengfu （GV 16） to the deep important bony structures in children aged 4 to 8 years based on CT three-dimensional reconstruction technology， thereby providing imaging reference data for clinical acupuncture safe operations in terms of different age groups and needle insertion angles. MethodsCervical CT image data were collected from healthy children aged 4 to 8 years with five age groups （4-， 5-， 6-， 7-， 8-year-old groups）， 20 cases in each group. The images were imported into Mimics 21.0 software for three-dimensional reconstruction. The straight-line distances from the skin model surface of the Fengfu （GV 16） to the first underlying bony barrier （such as the lower edge of the occipital bone， the posterior arch of the atlas vertebra） were measured at intervals of 5° on both the transverse section （0° ± 35°） and the sagittal section （40° upward to 40° downward on the diagonal）. The correlation between the measured distance， age， and angle was analyzed. ResultsIn the transverse and sagittal sections， the measured distance from the skin surface to the underlying bone of Fengfu （GV 16） at each angle increased with age. In the transverse section， the increase was relatively small within the 0° to 20° angle range， whereas a more pronounced increase was observed when the angle exceeded 20°； at measurement angles of 30° to 35°， the distance of the skin surface to the bone at Fengfu （GV 16） in the 7- and 8-year-old groups was significantly greater than that in the 4-year-old group （P＜0.05）. In the sagittal section， the measured distance from the skin surface to the bone at Fengfu （GV 16） was shortest and changed greatly at oblique upward angles of 15° to 40° within each age group， and increased markedly at near-vertical angles of 0° to 10°； it was longest at oblique downward angles of -40° to -5° and showed relatively gradual changes. ConclusionThis study obtained the imaging distance data from Fengfu （GV 16） to the surrounding bony structures in children aged 4 to 8 years through three-dimensional modeling， finding that this distance has clear age and angle dependence， which can provide quantitative evidence for developing individualized and precise safe acupuncture schemes at Fengfu （GV 16） in pediatric clinical practice.

ObjectiveTo construct a new quality classification method for Ophiopogonis Radix by systematically quantifying and integrating its appearance traits and bioactive components as objective indicators according to the theory of excellent shape， high quality， and superior effect of authentic medicinal materials. MethodsWith Ophiopogonis Radix from Zhejiang （a traditionally recognized authentic variety） as the research model， extensive samples were collected. Through textual research on classical herbal literature and modern references， root tuber length and hardness were selected as representative indicators of traditional appearance traits. These indicators were accurately measured by a digital vernier caliper and a universal testing machine for objective quantification. According to prescription data and literature review results， total saponins， total polysaccharides， and total flavonoids were chosen as key component indicators， and their content was determined. Descriptive statistics， cluster analysis， and other methods were comprehensively employed to identify the core objective indicators and their threshold ranges defining the excellent shape and high quality. The constructed evaluation system was subsequently applied to Ophiopogonis Radix from Zhejiang and Sichuan to verify its applicability. ResultsThe core quantitative indicators for the excellent shape and high quality of Ophiopogonis Radix were determined as follows： Length≥2.09 cm， hardness≤7.0 N， and content of total saponins， total polysaccharides， and total flavonoids not lower than 0.12%， 1.69%， and 0.13%， respectively. Verification results showed that this evaluation system could effectively identify Ophiopogonis Radix samples from Zhejiang， with the results consistent with traditional high-quality recognition. Its successful application to the samples from Sichuan further confirmed its cross-region universality. ConclusionThis study established an objective indicator-based evaluation system for the excellent shape and high quality of Ophiopogonis Radix， which breaks through the reliance on production regions. This system provides theoretical and methodological bases for precise quality control， scientific grading， and quality-based pricing of Ophiopogonis Radix， offering an innovative paradigm for the objective evaluation of authentic medicinal materials.