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.

Owing to its inherent advantages—such as being non-destructive, rapid, highly molecule-specific, and minimally interfered with by moisture—Raman spectroscopy has been widely adopted in the fields of skin barrier function assessment, monitoring the transdermal penetration of active cosmetic ingredients, and the identification and quality control of cosmetic products. Despite these strengths, the practical application of this technique faces a significant bottleneck: the strong fluorescence background generated by endogenous skin components and exogenous cosmetic additives. Endogenous skin substances, such as structural proteins (e.g., collagen and elastin), metabolic coenzymes (e.g., nicotinamide adenine dinucleotide), and pigments (e.g., melanin), together with exogenous cosmetic constituents like organic colorants, chemical sunscreens, and fragrances, often possess strong absorption and emission characteristics. When excited by lasers, these components produce a fluorescence background that can be 10⁶ to 10⁸ times stronger than the Raman scattering signals, effectively masking the inherently weak vibrational fingerprint information. In recent years, driven by the rapid development of optoelectronic hardware and artificial intelligence algorithms, fluorescence suppression strategies have evolved from isolated, single-method approaches into comprehensive, multi-level synergistic systems. These systems are categorized into three distinct tiers: sample preparation, signal acquisition, and data processing. At the sample preparation level, techniques such as photobleaching and surface-enhanced Raman spectroscopy (SERS) are employed to eliminate or bypass the generation of fluorescence at the source. At the signal acquisition level, instrumental improvements—including the use of long-wavelength near-infrared excitation (typically 785 nm or 1 064 nm), confocal spatial filtering, and shifted excitation Raman difference spectroscopy (SERDS)— are utilized to physically isolate Raman signals from the fluorescence background. Furthermore, at the data processing level, numerical baseline correction methods such as polynomial fitting, penalized least squares (e.g., airPLS, arPLS), wavelet transform, and derivative algorithms are increasingly integrated into the analytical pipeline to extract Raman spectral features from mixed signals without increasing hardware costs or acquisition time. This review provides a systematic categorization and critical evaluation of these fluorescence suppression methods, detailing their underlying principles, technical advantages, and inherent limitations in diverse experimental setups. By focusing on critical application scenarios—including skin barrier assessment, percutaneous absorption monitoring, the routine quality control of cosmetics, and the emerging field of portable on-site detection—this paper explores the current state of technique selection and optimization. Finally, the article discusses future development trends, emphasizing the necessity of constructing adaptive, tiered suppression strategies, developing intelligent and automated data processing algorithms, and promoting the integration of portable, multi-modal diagnostic devices. The objective of this review is to provide a comprehensive technical reference to facilitate the transition of Raman spectroscopy from a specialized laboratory tool into a routine, robust analytical platform for advancements in skin science and cosmetic research.

Metabolic dysfunction-associated fatty liver disease （MAFLD） progresses to metabolic dysfunction-associated steatohepatitis （MASH） due to mitochondrial homeostasis imbalance and dysfunction in hepatocytes caused by various factors such as lipotoxicity and inflammatory infiltration. Recent studies have confirmed that mitochondrial injury is closely associated with chronic inflammation， with extracellular vesicle （EV） acting as a key mediator linking the two processes. This article systematically reviews the molecular mechanisms of hepatocyte mitochondrial dysfunction in MAFLD/MASH， highlights the regulatory role of hepatocyte-derived EV in intrahepatic inflammation， and discusses the potential application prospects of mitochondria-targeted therapies and intercellular communication interventions in MAFLD/MASH， in order to provide a theoretical basis for developing novel therapeutic strategies for these diseases.

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

The inclusion complex of taxifolin(TAX)with hydroxypropyl-β-cyclodextrin(HP-β-CD)was prepared by saturated aqueous solution method,and the preparation conditions such as molar ratio,volume ratio of solution,inclusion temperature and inclusion time were selected by single-factor experiment.The orthogonal design of three-level four-factor L9(34)was used to screen the preparation process of the inclusion complex,and the inclusion complex was prepared with optimal preparation process.The prepared inclusion complex was characterized by scanning electron microscopy(SEM),nuclear magnetic resonance(1H NMR,2D NMR),Fourier transform infrared spectroscopy(FT-IR),ultraviolet-visible(UV-Vis)absorption spectroscopy and X-ray powder diffraction(XRD).The inclusion ratio,biostability,solubility and in vitro release of the inclusion complex were investigated.The results of orthogonal experiments showed that the optimum conditions for preparation of the inclusion complex were as follows:the molar ratio of TAX to HP-β-CD was 1:1,the volume ratio of methanol to ultra-pure water was 1:8,the inclusion time was 8 h,and the inclusion temperature was 30℃.Under the optimal conditions,the inclusion ratio between TAX and HP-β-CD was calculated to be 1:1 by Job's curve method.According to the change of UV-vis absorption spectra,the host-guest complexation constant of 4.9488×104 L/mol was obtained by Benesi-Hildebrand curve method.The solubility of TAX increased from 1.2665 mg/mL to 19.3469 mg/mL after inclusion,demonstrating that HP-β-CD could serve as an effective host molecule for TAX,which could significantly enhance the bio-stability and solubility of the formed inclusion complex.

Objective To investigate the effect of pseudogene GTF3AP2 in erythroid differentiation.Methods The published high-throughput RNA sequencing(RNA-seq)data were analyzed to identify the functional pseudogene GTF3AP2,which may play a role in erythropoiesis.The endogenous expression of GTF3AP2 was inhibited by shR-NA in CD34+hematopoietic stem/progenitor cells to assess the colony-forming ability through colony-forming assay.Flow cytometry analysis was applied to detect changes in the ratio of erythroid/megakaryocytic progenitor cells.Ad-ditionally,the role of GTF3AP2 in erythroid differentiation was determined through transcriptome sequencing,which revealed alterations at the cellular and molecular levels following the knockdown of GTF3AP2.Results Com-pared with the sh-EV group,knockdown of GTF3AP2 resulted in a significant increase in cell expansion,character-ized by a significant rise in the number of colony-forming unit erythroid cells(P＜0.001),an increase in the proportion of CD71+CD235a+erythroid precursors(P＜0.01),and a decrease in the proportion of CD71-CD235a+mature erythrocytes(P＜0.05).Furthermore,there was a significant reduction in the expression of key erythroid dif-ferentiation genes,including KLF1,HBB,GYPA,EPOR and TFRC.Conclusions Knocking down of GTF3AP2 promotes the expansion of erythroid precursor cells and inhibits erythroid maturation,suggesting that GTF3AP2 plays a regulatory role in erythroid differentiation.

Erectile dysfunction (ED) is prevalent among men, but its relationship with dietary habits is uncertain. The aim of our study was to assess whether dietary patterns enhance erectile function by reviewing the literature published before August 1, 2022, via PubMed, Web of Science, and EMBASE databases. The data compiled included author details; publication dates, countries, treatments, patient numbers, ages, follow-ups, and clinical trial outcomes, such as ED cases, odds ratios (ORs), confidence intervals (CIs), and International Index of Erectile Function-5 (IIEF-5) scores with means and standard deviations. An analysis of 14 studies with 27 389 participants revealed that plant-based diets (OR = 0.71, 95% CI: 0.66-0.75; P < 0.00001), low-fat diets (OR = 0.27, 95% CI: 0.13-0.53; P = 0.0002), and alternative diets such as intermittent fasting and organic diets (OR = 0.54, 95% CI: 0.36-0.80; P = 0.002) significantly reduced ED risk. High-protein low-fat diets (hazard ratio [HR] = 1.38, 95% CI: 1.12-1.64; P < 0.00001) and high-carb low-fat diets (HR = 0.79, 95% CI: 0.55-1.04; P < 0.00001) improved IIEF-5 scores. Combined diet and exercise interventions decreased the likelihood of ED (OR = 0.49, 95% CI: 0.28-0.85; P = 0.01) and increased the IIEF-5 score (OR = 3.40, 95% CI: 1.69-5.11; P < 0.0001). Diets abundant in fruits and vegetables (OR = 0.97, 95% CI: 0.96-0.98; P < 0.00001) and nuts (OR = 0.54, 95% CI: 0.37-0.80; P = 0.002) were also correlated with lower ED risk. Our meta-analysis underscores a strong dietary-ED association, suggesting that low-fat/Mediterranean diets rich in produce and nuts could benefit ED management.
Humans ; Male ; Erectile Dysfunction/epidemiology* ; Diet ; Diet, Fat-Restricted ; Feeding Behavior ; Penile Erection/physiology* ; Diet, Vegetarian