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.

The objective assessment of hearing loss is one of the critical components in forensic clini-cal research.Auditory brainstem response(ABR)is an important method for objectively assessing hearing levels.It is divided into various types based on different stimulus signals,each with its own characteris-tics and applications.Among them,narrow-band Chirp ABR,due to its frequency specificity,fulfills the basic requirements for objective assessment of forensic audiology,promising to be an important method of objective hearing assessment in forensic medicine.This article reviews the development history,charac-teristics and clinical applications of Chirp ABR,and envisions its application prospects in forensic audi-tory identification.

OBJECTIVE: The occurrence and development of atrial fibrillation (AF) are influenced by the autonomic nervous system and inflammation. Acupuncture is an effective treatment for AF. This study explored the protective effects of acupuncture in a rat model of paroxysmal AF and investigated its mechanisms. METHODS: Male Sprague-Dawley rats (n = 130) were randomly divided into blank control (Con), sham operation (Sham), AF, and acupuncture treatment (Acu) groups. A paroxysmal AF model was established by rapid atrial pacing through the jugular vein. Rats in the Acu group were immobilized to receive acupuncture treatment at Neiguan acupoint (PC6) for 20 min daily for seven days. The other groups were immobilized for the same duration over the treatment period but did not receive acupuncture. The AF induction rate, AF duration, cardiac electrophysiological parameters, and heart rate variability were evaluated by monitoring surface electrocardiogram and vagus nerve discharge signals. After the intervention, the rats were euthanized, and atrial morphology was assessed using haematoxylin and eosin staining. The expression of macrophage F4/80 antigen (F4/80) and cluster of differentiation (CD) 86 in atrial myocardial tissue was detected using immunohistochemistry, immunofluorescence and flow cytometry. The expression levels or contents of interleukin (IL)-1β, IL-6, tumor necrosis factor-α (TNF-α), α7 nicotinic acetylcholine receptor (α7nAChR), phosphorylated Janus kinase 2 (p-JAK2), and phosphorylated signal transducer and activator of transcription 3 (p-STAT3) in atrial myocardial tissue were detected using Western blotting, reverse transcription-quantitative polymerase chain reaction, or enzyme-linked immunosorbent assay. The role of α7nAChR in acupuncture treatment was verified by intraperitoneal injection of the α7nAChR antagonist methyllycaconitine (MLA). RESULTS: Compared with the AF group, acupuncture significantly reduced AF duration and induction rate, improved cardiac electrophysiology by enhancing vagus nerve activity and regulating autonomic balance. It also decreased the pro-inflammatory M1 macrophage proportion, alleviating myocardial injury and infiltration. MLA weakened acupuncture's electrophysiological improvement and anti-inflammatory effect. Results suggest that acupuncture triggers the α7nAChR-JAK2/STAT3 pathway and exerts cardioprotection via neuroimmune regulation. CONCLUSION Acupuncture significantly reduced the AF induction rate, shortened AF duration, improved cardiac electrophysiological parameters, enhanced vagus nerve activity, and decreased the expression of pro-inflammatory M1 macrophages and inflammatory factors in rats with paroxysmal AF. Its positive effects are related to the activation of the α7nAChR-mediated JAK2/STAT3 signalling pathway, indicating that the interaction between cardiac vagus nerve and macrophages may be a potential target for acupuncture in the prevention and treatment of AF. Please cite this article as: Li ZH, Yang WM, Huang Q, Shi GX, Liu CZ, Zhang YQ. Acupuncture activates vagus nerve-macrophage axis and improves cardiac electrophysiology and inflammatory response in rats with atrial fibrillation via α7nAChR-JAK2/STAT3 pathway. J Integr Med. 2025; 23(4): 398-414.
Animals ; Male ; Rats, Sprague-Dawley ; STAT3 Transcription Factor/metabolism* ; alpha7 Nicotinic Acetylcholine Receptor/metabolism* ; Janus Kinase 2/metabolism* ; Atrial Fibrillation/metabolism* ; Vagus Nerve/physiopathology* ; Rats ; Acupuncture Therapy ; Signal Transduction ; Macrophages/metabolism* ; Inflammation/therapy*

Objective:To investigate the risk factors,clinical characteristics,and bacterial resistance of bloodstream infections caused by Streptococcus mitis in children with hematological disease,so as to provide a reference for infection control.Methods:The clinical information and laboratory findings of pediatric patients complicated with blood cultures positive for Streptococcus mitis from January 2018 to December 2020 in the Institute of Hematology & Blood Diseases Hospital were searched and collected.The clinical characteristics,susceptibility factors,and antibiotic resistance of the children were retrospectively analyzed.Results:Data analysis from 2018 to 2020 showed that the proportion of Streptococcus mitis isolated from bloodstream infections in children(≤14 years old)with hematological diseases was the highest(19.91％)and significantly higher than other bacteria,accounting for 38.64％of Gram-positive cocci,and presented as an increasing trend year by year.A total of 427 children tested positive blood cultures,including 85 children with bloodstream infections caused by Streptococcus mitis who tested after fever.Most children experienced a recurrent high fever in the early and middle stages(≤6 d)of neutropenia and persistent fever for more than 3 days.After adjusting the antibiotics according to the preliminary drug susceptibility results,the body temperature of most children(63.5％)returned to normal within 4 days.The 85 children were mainly diagnosed with acute myeloid leukemia(AML),accounting for 84.7％.The proportion of children in the neutropenia stage was 97.7％.The incidence of oral mucosal damage,lung infection,and gastrointestinal injury symptoms was 40％,31.8％,and 27.1％,respectively.The ratio of elevated C-reactive protein(CRP)and procalcitonin was 65.9％and 9.4％,respectively.All isolated strains of Streptococcus mitis were not resistant to vancomycin and linezolid,and the resistance rate to penicillin,cefotaxime,levofloxacin,and quinupristin-dalfopristin was 10.6％,8.2％,9.4％,and 14.1％,respectively.None of children died due to bloodstream infection caused by Streptococcus mitis.Conclusion:The infection rate of Streptococcus mitis is increasing year by year in children with hematological diseases,especially in children with AML.Among them,neutropenia and oral mucosal damage after chemotherapy are high-risk infection factors.The common clinical symptoms include persistent high fever,oral mucosal damage,and elevated CRP.Penicillin and cephalosporins have good sensitivity.Linezolid,as a highly sensitive antibiotic,can effectively control infection and shorten the course of disease.

Objective:To establish an in vitro cell model simulating acute graft-versus-host disease(aGVHD)bone marrow microenvironment injury with the advantage of mouse serum of aGVHD model and explore the effect of serum of aGVHD mouse on the adipogenic differentiation ability of mesenchymal stem cells(MSCs).Methods:The 6-8-week-old C57BL/6N female mice and BALB/c female mice were used as the donor and recipient mice of the aGVHD model,respectively.Bone marrow transplantation(BMT)mouse model(n=20)was established by being injected with bone marrow cells(1 × 10'per mouse)from donor mice within 4-6 hours after receiving a lethal dose(8.0 Gy,72.76 cGy/min)of y ray general irradiation.A mouse model of aGVHD(n=20)was established by infusing a total of 0.4 ml of a mixture of donor mouse-derived bone marrow cells(1 × 107 per mouse)and spleen lymphocytes(2 × 106 per mouse).The blood was removed from the eyeballs and the mouse serum was aspirated on the 7th day after modeling.Bone marrow-derived MSCs were isolated from 1-week-old C57BL/6N male mice and incubated with 2％,5％and 10％BMT mouse serum and aGVHD mouse serum in the medium,respectively.The effect of serum in the two groups on the in vitro adipogenic differentiation ability of mouse MSCs was detected by Oil Red O staining.The expression levels of related proteins PPARy and CEBPα were detected by Western blot.The expression differences of key adipogenic transcription factors including PPARy,CEBPα,FABP4 and LPL were determined by real-time quantitative PCR(RT-qPCR).Results:An in vitro cell model simulating the damage of bone marrow microenvironment in mice with aGVHD was successfully established.Oil Red O staining showed that the number of orange-red fatty droplets was significantly reduced and the adipogenic differentiation ability of MSC was impaired at aGVHD serum concentration of 10％compared with BMT serum.Western blot experiments showed that adipogenesis-related proteins PPARy and CEBPα expressed in MSCs were down-regulated.Further RT-qPCR assay showed that the production of PPARy,CEBPα,FABP4 and LPL,the key transcription factors for adipogenic differentiation of MSC,were significantly reduced.Conclusion:The adipogenic differentiation capacity of MSCs is inhibited by aGVHD mouse serum.

Objective To identify key proteins associated with sudden cardiac death(SCD)caused by lethal arrhythmia and to explore their potential molecular mechanisms through integrated proteomic analysis,data mining,and bioinformatics.Methods A lethal arrhythmia model was established in 8-week-old male Sprague-Dawley rats,which were divided into an arrhythmia group and a control group.Proteomic techniques were applied to identify and quantify proteins in left ventricular myocardial tissue,and differentially expressed proteins related to arrhythmia were screened.Key proteins were further identified through comparison with target proteins in databases combined with joint analyses.Bioinformatics methods were then used to investigate potential molecular mechanisms.Results A total of 356 differentially expressed proteins were identified,including 189 upregulated and 167 downregulated.Association analysis with target gene proteins identified 71 key proteins,and a protein-protein interaction network was constructed.GO enrichment and KEGG pathway analyses indicated that these key proteins were primarily involved in ion channel dysfunction,enhanced oxidative stress,and autonomic nervous system imbalance.Conclusion This study,through the integration of proteomics,data mining,and bioinformatics,revealed critical molecular mechanisms underlying SCD associated with lethal arrhythmia.These findings provide new perspectives and potential biomarkers for forensic identification and research on the mechanisms of death.

Objective:To investigate the predictive value of endothelial activation and stress index(EASIX)for the prognosis of patients with mantle cell lymphoma(MCL).Methods:A retrospective analysis was conducted to assess prognosis and compare the clinical features of patients diagnosed with MCL who were admitted to the Affiliated Hospital of Xuzhou Medical University from January 2010 to June 2023,had therapeutic indications and received standard treatment.Results:A total of 66 patients were included and divided into high EASIX group and low EASIX group,according to a cutoff value of 0.97 determined by the receiver operating characteristic(ROC)curve.Multivariate Cox regression analysis showed that prealbumin＜0.2 g/L,high EASIX,and ECOG PS score ≥2 were independent risk factors influencing overall survival(OS)in MCL patients.The median OS of patients in the high and low EASIX group was 13.0 and 37.5 months,and the median progression-free survival was 8.8 and 26.0 months,respectively.The proportions of patients with ECOG PS score ≥2 and prealbumin＜0.2 g/L at onset significantly increased in the high EASIX group compared to those in the low EASIX group.Conclusion:At the time of initial diagnosis,EASIX can serve as an independent prognostic indicator impacting OS in patients with MCL.Furthermore,patients in the high EASIX group experience a poorer prognosis and shorter survival duration compared with those in the low EASIX group.