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.

To explore the variation laws of volatile oil during the extraction process of Artemisiae Argyi Folium and its impact on the quality of the medicinal solution, as well as to achieve precise control of the extraction process, this study employed headspace solid phase microextraction gas chromatography-mass spectrometry(HS-SPME-GC-MS) in combination with multiple light scattering techniques to conduct a comprehensive analysis, identification, and characterization of the changes in volatile components and the physical properties of the medicinal solution during the extraction process. A total of 82 volatile compounds were identified using the HS-SPME-GC-MS technique, including 21 alcohols, 15 alkenes, 14 ketones, 9 acids, 6 aldehydes, 5 phenols, 3 esters, and 9 other types of compounds. At different extraction time points(15, 30, 45, and 60 min), 71, 72, 64, and 44 compounds were identified in the medicinal solution, respectively. It was observed that the content of volatile components gradually decreased with the extension of extraction time. Through multivariate statistical analysis, four compounds with significant differences during different extraction time intervals were identified, namely 1,8-cineole, terpinen-4-ol, 3-octanone, and camphor. RESULTS:: from multiple light scattering techniques indicated that at 15 minutes of extraction, the transmittance of the medicinal solution was the lowest(25%), the particle size was the largest(0.325-0.350 nm), and the stability index(turbiscan stability index, TSI) was the highest(0-2.5). With the extension of extraction time, the light transmittance of the medicinal solution improved, stability was enhanced, and the particle size decreased. These laws of physicochemical property changes provide important basis for the control of Artemisiae Argyi Folium extraction process. In addition, the changes in the bioactivity of Artemisiae Argyi Folium extracts during the extraction process were investigated through mouse writhing tests and antimicrobial assays. The results indicated that the analgesic and antimicrobial effects of the medicinal solution were strongest at the 15-minute extracting point. In summary, the findings of this study demonstrate that the content of volatile oil in Artemisiae Argyi Folium extracts gradually decreases with the extension of extraction time, and the variation in volatile oil content directly influences the physicochemical properties and pharmacological efficacy of the medicinal solution. This discovery provides important scientific reference for the optimization of Artemisiae Argyi Folium extraction processes and the development and application of process analytical technologies.
Oils, Volatile/pharmacology* ; Artemisia/chemistry* ; Gas Chromatography-Mass Spectrometry ; Drugs, Chinese Herbal/pharmacology* ; Chlorogenic Acid/pharmacology* ; Solid Phase Microextraction ; Quality Control

Atopic dermatitis (AD) is a prevalent inflammatory skin disorder in which patients experience recurrent eczematous lesions and intense itching. The colonization of Staphylococcus aureus (S. aureus) is correlated with the severity of the disease, but its role in AD development remains elusive. Using single-cell RNA sequencing, we uncovered that keratinocytes activate a distinct immune response characterized by induction of Il24 when exposed to methicillin-resistant S. aureus (MRSA). Further experiments using animal models showed that the administration of recombinant IL-24 protein worsened AD-like pathology. Genetic ablation of Il24 or the receptor Il20rb in keratinocytes alleviated allergic inflammation and atopic march. Mechanistically, IL-24 acted through its heterodimeric receptors on keratinocytes and augmented the production of IL-33, which in turn aggravated type 2 immunity and AD-like skin conditions. Overall, these findings establish IL-24 as a critical factor for onset and progression of AD and a compelling therapeutic target.
Dermatitis, Atopic/genetics* ; Interleukins/metabolism* ; Animals ; Methicillin-Resistant Staphylococcus aureus/immunology* ; Mice ; Keratinocytes/microbiology* ; Humans ; Interleukin-33/immunology* ; Inflammation/microbiology* ; Staphylococcal Infections/microbiology* ; Disease Models, Animal ; Hypersensitivity/microbiology* ; Mice, Inbred C57BL

Background Due to the unique working environment and numerous occupational disease hazards, workers in mining industry are particularly susceptible to psychological problems such as occupational stress. Objective To understand the current status of occupational stress, depressive symptoms, anxiety symptoms and sleep quality of workers in ferrous and non-ferrous metal mining industry in Gansu Province, and to explore the effects of occupational stress on depressive symptoms, anxiety symptoms, and sleep. Methods From April to December 2022, the workers of 25 large, medium, and small and micro enterprises were selected by stratified cluster random sampling and surveyed in ferrous and non-ferrous metal mining industry in Gansu Province. The Occupational Health Literacy Questionnaire of National Key Population, Core Occupational Stress Scale, Patient Health Questionnaire-q, Generalized Anxiety Disorder, and Self-administer Sleep Questionnaire were used to collect basic information, occupational stress, depressive symptoms, anxiety symptoms, and sleep quality of the workers. Chi-square test was used to compare occupational stress, depressive symptoms, anxiety symptoms and sleep disorders among different categories. Logistic regression model was used to study the effects of occupational stress on depressive symptoms, anxiety symptoms, and sleep quality. Results In this study, 2192 workers in mining industry were surveyed, of which 2087 returned valid questionnaires, and the recovery rate of valid questionnaires was 95.2%. Among them, 728 (38.4%) reported occupational stress. There were statistically significant differences in the positive rate of occupational stress among workers by gender, age, marital status, education level, average monthly income, length of service, enterprise size, and night shifts (P<0.001). The positive rates of depressive symptoms, anxiety symptoms, and sleep disorders in the mining industry workers were 85.6%, 49.8%, and 47.3%, respectively. The positive rates of depressive symptoms, anxiety symptoms, and sleep disorders among workers with higher occupational stress were higher than those among workers without occupational stress (P<0.001). The logistic regression analysis showed that occupational stress was a common risk factor for depressive symptoms (OR=3.29, 95%CI: 2.26, 4.79), anxiety symptoms (OR=2.87, 95%CI: 2.33, 3.53), and sleep disorder (OR=1.78, 95%CI: 1.46, 2.16). In addition, length of service and enterprise-scale were also risk factors for depressive symptoms, anxiety symptoms, and sleep disorders. In the 5−<10 and 10−<20 years of service groups, the risks of reporting depressive symptoms were 1.80 (95%CI: 1.18, 2.74) and 1.73 (95%CI: 1.10, 2.71) times higher than that of workers with less than 1 year of service, respectively; the risks of reporting anxiety symptoms were 1.98 (95%CI: 1.42, 2.76) and 2.11 (95%CI: 1.48, 3.01) times higher than that with less than 1 year of service, respectively; the risks of reporting sleep disorders were 1.58 (95%CI: 1.15, 2.16) and 1.78 (95%CI: 1.29, 2.45) times higher than that with less than 1 year of service, respectively. Workers in large enterprises were inclined to report more depressive symptoms, anxiety symptoms, and sleep disturbances than those in micro and small enterprises (OR=3.53, 95%CI: 2.41, 5.16; OR=2.49, 95%CI: 1.98, 3.13; OR=2.10, 95%CI: 1.67, 2.62). Conclusion The occupational stress level of mining industry workers in Gansu Province is high, and reporting occupational stress, 5−<10 and 10−<20 working age groups, and large enterprises are important risk factors affecting workers' mental health and sleep. It is necessary to increase the attention and develop intervention programs for mental health of miners in the working age group of 5−20 years old and in large enterprises.

Objective: To investigate the expression and functional role of FK506 binding protein 10 (FKBP10) in oral squamous cell carcinoma (OSCC), and to provide a research basis for the estimated prognosis and targeted therapy of OSCC. Methods: A total of 284 OSCC samples and 19 normal samples were selected from the Cancer Genome Atlas (TCGA) database, and diagnostic analysis was performed to determine mRNA expression. Survival analysis for FKBP10 and OSCC was conducted on a gene expression profile interaction analysis website. Real-time fluorescence quantitative PCR and Western Blot were used to detect the mRNA and protein expression of FKBP10 in four OSCC cell lines and SAS and SCC9 cells transfected with siRNA. The cell proliferation ability of FKBP10-silenced cells was detected using the CCK8 method, and the cell cycle distribution and apoptosis were detected by flow cytometry. Cell migration and invasion ability were detected through wound healing and invasion experiments. The expression changes of total protein and phosphatidylinositol 3-kinase (PI3K)-serine/threonine kinase (AKT) after FKBP10 silencing were analyzed by proteomics and Western Blot. Results: According to the analysis of gene expression levels, the mRNA expression level of FKBP10 in OSCC was significantly higher than that in normal tissues (P < 0.001). In terms of diagnosis, the expression level of FKBP10 has unique diagnostic value for OSCC (P < 0.05). The survival analysis of FKBP10 and OSCC showed that a high expression of FKBP10 led to a decrease in patient survival and poor prognosis (P < 0.05). The expression of FKBP10 mRNA and protein in OSCC cell lines was higher than that in normal oral keratinocytes (P < 0.001). Silencing FKBP10 can reduce the proliferation, invasion, and migration ability of SAS and SCC9 (P < 0.001), and also block their cell cycle in the G0/G1 phase (P < 0.001), with a significant increase in apoptosis (P < 0.05). Protein mass spectrometry and Western blot analysis revealed that FKBP10 silencing significantly downregulated the expression of multiple proteins in the RAP1 signaling pathway, mainly RAP guanine nucleotide exchange factor 1 (RAPGEF1) (P < 0.05) and the phosphorylation of PI3K-AKT proteins (P < 0.05). Conclusion FKBP10 is highly expressed in OSCC, leading to poor prognosis for patients. Downregulated FKBP10 expression can inhibit the proliferation, migration, and invasion ability of OSCC cells, hinder cell cycle progression, and promote apoptosis via the RAP1-PI3K-AKT axis. FKBP10 is a potential therapeutic target and prognostic biomarker for OSCC.

Traditional Chinese Medicine (TCM), as a treasure of the Chinese nation, plays a significant role in maintaining public health. In 2019, the Central Committee of the Communist Party of China and the State Council proposed for the first time the establishment of a TCM registration and evaluation evidence system that integrates TCM theory, "personal experience" and clinical trials (referred to as the "Three-in-One" System) to promote the inheritance and innovation of TCM. Subsequently, the National Medical Products Administration issued several guiding principles to advance the improvement and implementation of this system. Owing to the complexity of its implementation, there are still differing understandings within the TCM industry regarding the positioning of the "Three-in-One" Registration and Evaluation Evidence System, as well as the connotation and value orientation of the "personal experience." To address this, Academician WANG Qi, President of the TCM Association, China International Exchange and Promotion Association for Medical and Healthcare and TCM master, led a group of academicians, TCM masters, TCM pharmacology experts and clinical TCM experts to convene a "Seminar on Promoting the Implementation of the ′Three-in-One′ Registration and Evaluation Evidence System for Chinese Medicinals." Through extensive discussions, an expert consensus was formed, clarifying the different roles of the TCM theory, "personal experience" and clinical trials within the system. It was further emphasized that the "personal experience" is the core of this system, and its data should be derived from clinical practice scenarios. In the future, the improvement of this system will require collaborative efforts across multiple fields to promote the high-quality development of the Chinese medicinal industry.

Kounis syndrome is an acute coronary syndrome triggered by an allergic reaction, which is clinically rare and frequently subject to misdiagnosis or missed diagnosis. This article presents a case report of a 70-year-old male patient who developed a rash, pruritus, and chest pain following colon polyp resection. Coronary angiography revealed occlusion of the left anterior descending artery, and blood flow was restored after stent implantation. However, the patient experienced recurrent symptoms accompanied by loss of consciousness. Drug skin tests confirmed positive reactions to chlorhexidine and fondaparinux sodium, leading to a diagnosis of type Ⅱ Kounis syndrome. By avoiding allergenic drugs and combining antihistamines with symptomatic treatment to correct myocardial ischemia, the patient′s clinical symptoms significantly improved, and he eventually recovered and was discharged from the hospital. This case underscores the importance of maintaining vigilance for this syndrome in patients with allergies accompanied by chest pain and promptly identifying and avoiding allergens.

Objective: To establish an ultra-high performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) method based on solid-phase extraction column purification for simultaneous determination of cyromazine and melamine in poultry eggs and meat. Methods: Eggs, quail eggs, and chicken were collected from markets. After homogenization, the sample was extracted with 0.5% formic acid in acetonitrile, subjected to solid-phase extraction using an MCX cartridge, and eluted with 5% ammonia in methanol. The eluate was collected, evaporated to near dryness under nitrogen, and reconstituted in a 10% aqueous methanol solution. Separated using TSK gel Amide-80 column (2.0 mm×150 mm, 5 μm), cyromazine and melamine were simultaneously detected in positive ion multiple reaction monitoring mode via tandem mass spectrometry, with quantification achieved by isotope dilution internal standard methods. Efficiency was enhanced and matrix interference minimized by optimizing conditions such as sample extraction, solid-phase extraction cartridge selection, and instrumental parameters. Calibration curves were constructed, and detection limits, quantification limits, spiked recoveries, and relative standard deviations for (RSD) of cyromazine and melamine were calculated. Results: After method optimization, matrix effects for cyromazine and melamine ranged from 0.97 to 1.04, indicating no significant matrix suppression or enhancement. Both cyromazine and melamine exhibited excellent linearity within the concentration range of 1.0-200.0 ng/mL, with correlation coefficients ≥0.999 5. The limits of detection were 0.3 μg/kg for cyromazine and 0.5 μg/kg for melamine, the quantification limits were 1.0 and 1.5 μg/kg, respectively. At spiked levels of 1.0, 20.0, and 150.0 μg/kg, the average recoveries ranged from 78.6% to 103.1%, with RSD between 3.5% and 6.3%. Among 95 samples tested, cyromazine was detected in 6 samples and melamine in 5 samples; neither cyromazine nor melamine was detected in chicken samples. Conclusion The UPLC-MS/MS method established in this study enables simultaneous detection and accurate quantification of cyromazine and melamine in poultry eggs and meat.