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.

Background Work-related musculoskeletal disorders (WMSDs) are a major occupational health concern, particularly among workers exposed to adverse ergonomic conditions. Manganese production involves heavy physical demands, yet research on WMSDs among manganese workers remains limited. Objective To investigate the prevalence and influencing factors of WMSDs among manganese workers in a manganese enterprise in Guangxi. Methods A cross-sectional survey was conducted from May to June 2024 on workers at a manganese factory in Guangxi. The Chinese Musculoskeletal Disorders Questionnaire was used to collect information on demographic characteristics, distribution of musculoskeletal symptoms, and work-related exposures. χ² test was applied to compare differences in positive WMSDs rates across groups, and logistic regression analysis was performed to identify associated factors. Results A total of 1476 workers were enrolled in the study after pre-determined inclusion and exclusion criteria. The overall prevalence of WMSDs was 34.15%. The most commonly affected body regions were the lower back (17.28%), neck (16.67%), and shoulders (13.82%). The results of logistic regression analysis indicated that female, older age, and education level of college or above were associated with a higher risk of WMSDs (P<0.05). Awkward working postures were significantly associated with WMSDs in corresponding body regions; in particular, awkward postures of the neck, upper limbs, trunk, and lower limbs were related to an increased risk of WMSDs in multiple body sites (P<0.05). In addition, poor lighting conditions, high workplace temperature, frequent or sustained arm support during work, and high job demands were associated with an increased risk of overall or site-specific WMSDs (P<0.05). Conclusion The high prevalence of WMSDs among manganese workers is closely associated with demographic characteristics, working postures, and work environment and organizational factors. Targeted ergonomic interventions focusing on high-risk body regions and key ergonomic exposures are warranted to reduce the risk of WMSDs among manganese workers.

Intraoperative cell salvage (IOCS) has been widely applied as an important blood conservation measure in surgical operations. However, there is currently a lack of clinical practice guidelines for the implementation of IOCS in patients with malignant tumors. This report aims to provide clinicians with recommendations on the use of IOCS in patients with malignant tumors based on the review and assessment of the existed evidence. Data were derived from databases such as PubMed, Embase, the Cochrane Library and Wanfang. The guideline development team formulated recommendations based on the quality of evidence, balance of benefits and harms, patient preferences, and health economic assessments. This study constructed seven major clinical questions. The main conclusions of this guideline are as follows: 1) Compared with no perioperative allogeneic blood transfusion (NPABT), perioperative allogeneic blood transfusion (PABT) leads to a more unfavorable prognosis in cancer patients (Recommended); 2) Compared with the transfusion of allogeneic blood or no transfusion, IOCS does not lead to a more unfavorable prognosis in cancer patients (Recommended); 3) The implementation of IOCS in cancer patients is economically feasible (Recommended); 4) Leukocyte depletion filters (LDF) should be used when implementing IOCS in cancer patients (Strongly Recommended); 5) Irradiation treatment of autologous blood to be reinfused can be used when implementing IOCS in cancer patients (Recommended); 6) A careful assessment of the condition of cancer patients (meeting indications and excluding contraindications) should be conducted before implementing IOCS (Strongly Recommended); 7) Informed consent from cancer patients should be obtained when implementing IOCS, with a thorough pre-assessment of the patient's condition and the likelihood of blood loss, adherence to standardized internally audited management procedures, meeting corresponding conditions, and obtaining corresponding qualifications (Recommended). In brief, current evidence indicates that IOCS can be implemented for some malignant tumor patients who need allogeneic blood transfusion after physician full evaluation, and LDF or irradiation should be used during the implementation process.

Salvia miltiorrhiza (Danshen) is a traditional Chinese herb that is commonly known for its cardiovascular and hepatoprotective benefits. Recent studies have confirmed that Danshen and its bioactive components can influence gut microbial homeostasis, thereby affecting Helicobacter pylori (HP) colonization in the human stomach. HP is a bacterial pathogen associated with various gastrointestinal diseases. Current HP treatments mainly involve antibiotics and proton pump inhibitors. However, their efficacy is strongly compromised by the rapid emergence of antibiotic resistance in HP and genetic heterogeneity among patients. The interaction between Danshen and gut microbial status provides a novel perspective for HP treatment. Understanding the medical properties of Danshen in altering gut microbiota and eliminating HP, as well as the underlying mechanisms, is important for improving human gastrointestinal healthcare. This review investigates the interaction between Danshen and gut microbiota and its impact on HP infection using databases including Web of Science, PubMed, and Google Scholar. We explored the unconventional intersection between Danshen, gut microbiota, and HP infection, shedding light on their intricate interplay and potential therapeutic implications. A comprehensive understanding of this interaction provides valuable insights into developing novel therapeutic strategies that target the gut microbiota to mitigate HP-associated gastrointestinal disorders. Please cite this article as: Li SJ, Miao JX, Wang F, Wang HY, Ma YW, Jiang Y, Xue X. Salvia miltiorrhiza components and gut microbiota interactions in Helicobacter pylori infection. J Integr Med. 2025; 23(5):462-470.
Salvia miltiorrhiza/chemistry* ; Gastrointestinal Microbiome/drug effects* ; Humans ; Helicobacter Infections/microbiology* ; Helicobacter pylori/drug effects* ; Drugs, Chinese Herbal/therapeutic use*

OBJECTIVE: We aimed to investigate the patterns of fasting blood glucose (FBG) trajectories and analyze the relationship between various occupational hazard factors and FBG trajectories in male steelworkers. METHODS: The study cohort included 3,728 workers who met the selection criteria for the Tanggang Occupational Cohort (TGOC) between 2017 and 2022. A group-based trajectory model was used to identify the FBG trajectories. Environmental risk scores (ERS) were constructed using regression coefficients from the occupational hazard model as weights. Univariate and multivariate logistic regression analyses were performed to explore the effects of occupational hazard factors using the ERS on FBG trajectories. RESULTS: FBG trajectories were categorized into three groups. An association was observed between high temperature, noise exposure, and FBG trajectory ( P < 0.05). Using the first quartile group of ERS1 as a reference, the fourth quartile group of ERS1 had an increased risk of medium and high FBG by 1.90 and 2.21 times, respectively (odds ratio [ OR] = 1.90, 95% confidence interval [ CI]: 1.17-3.10; OR = 2.21, 95% CI: 1.09-4.45). CONCLUSION An association was observed between occupational hazards based on ERS and FBG trajectories. The risk of FBG trajectory levels increase with an increase in ERS.
Humans ; Male ; Adult ; Blood Glucose/analysis* ; China ; Prospective Studies ; Occupational Exposure/adverse effects* ; Risk Factors ; Middle Aged ; Steel ; Fasting/blood* ; Metal Workers ; East Asian People

Senecavirus A (SVA) is a major viral pathogen causing disease in pigs, and effective monitoring of SVA infection is critical for disease control. In this study, we aimed to develop a reliable ELISA method for rapidly detecting neutralizing antibodies against SVA. We used HEK293F cells to express an SVA-specific porcine Fab antibody and verified the biological activity of the Fab antibody by indirect ELISA, immunofluorescence assay, virus neutralization test, and Western blotting. The Fab antibody was biotinylated and used as a competitive antibody to establish a competitive ELISA (C-ELISA) for detecting neutralizing antibodies against SVA. We then evaluated the C-ELISA in terms of sensitivity, specificity, repeatability, and result agreement rate with the VNT. The results showed that we successfully prepared an SVA-specific porcine Fab antibody, which showed high affinity for SVA. We named this antibody 1M33Fab and designated it as Bio-1M33Fab after biotin labeling. The assay conditions were optimized as follows: the coating concentration of SVA particles being 1 μg/mL, the working concentration of Bio-1M33Fab being 0.5 μg/mL, the optimal serum dilution of 1:10, and the optimal dilution of enzyme-labeled avidin being 1:30 000. At a percent inhibition (PI) of 47%, the assay demonstrated the highest sensitivity (96.88%) and specificity (100%), with no cross-reactivity observed with the positive sera of major porcine viral diseases. The intra-assay coefficient of variation ranged from 1.12% to 7.34%, while the inter-assay coefficient of variation ranged from 1.10% to 8.97%, indicating good repeatability. In the detection of 224 clinical pig serum samples, C-ELISA and VNT showed a result agreement rate of 93.75%. In conclusion, we successfully develop a C-ELISA method for detecting neutralizing antibodies against SVA by using a porcine-derived Fab antibody, which lays a foundation for the development of detection kits.
Animals ; Swine ; Antibodies, Neutralizing/immunology* ; Enzyme-Linked Immunosorbent Assay/methods* ; Immunoglobulin Fab Fragments/immunology* ; Antibodies, Viral/immunology* ; Picornaviridae/immunology* ; Humans ; HEK293 Cells ; Swine Diseases/diagnosis* ; Picornaviridae Infections/diagnosis*

Objective: To investigate the molecular mechanisms and pathways of action of total flavonoids of Dracocephalum moldavica L.(TFDM) in treating vascular cognitive impairment(VCI) based on network pharmacology and in vivo animal experiments. Methods : The swiss target prediction database, literature, and PubChem were used to screen the active components and action targets of TFDM. The online mendelian inheritance in man(OMIM) and GeneCards databases were utilized to screen for possible VCI targets. Venny software was used to obtain the intersection target of TFDM and VCI. The search tool for recurring instances of neighbouring genes(String) database and Cytoscape software was used to construct the PPI network. The database for annotation, visualization and integrated discovery(DAVID) database was utilized to screen for the kyoto encyclopedia of genes and genomes(KEGG) pathway and gene ontology(GO) enrichment analyses to explore the molecular mechanism and signaling pathway of TFDM for VCI. 24 rats were divided into Sham, Model, Donepezil, and TFDM groups. Except for the Sham group, the VCI model was created using modified bilateral common carotid artery ligation. After continuous gavage for 21 days, the Morris water maze test was used to evaluate the spatial learning and memory ability of rats. Hematoxy-lineosin(HE) staining was used to observe the pathological changes in the hippocampal CA1 and cortex region of the animals and immunohistochemistry detection of zonula occludens-1(ZO-1) content in the brains of the rats. Western blot was used to detect nuclear factor kappa-B p65(NF-κB p65) and tumor necrosis factor-α(TNF-α) in rat brains. Results : A total of 39 active ingredients of TFDM were screened, 209 corresponding targets, 10 417 gene targets of VCI, and 193 intersecting targets. According to the results of the GO enrichment of function analysis, TFDM could improve the response of reactive oxygen species and metabolic processes of reactive oxygen species, etc. KEGG pathway enrichment analysis suggested that TFDM might regulate TNF, IL-17 signing pathway, etc. The results of animal experiments showed that TFDM improved learning and memory while reduced pathological damage in the brains of VCI rats. In addition, TFDM upregulated the positive expression of ZO-1 and downregulated the protein levels of TNF-α and NF-κB p65(P<0.05). Conclusion TFDM can improve the cognitive function of VCI through multi-components and multi-targets, and its key mechanism may be related to inhibiting TNF-α/NF-κB p65 signaling pathway,reducing neuroinflammation,and improvement of blood-brain barrier permeability.