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.

OBJECTIVE To form an expert consensus addressing clinical issues regarding the use of parenteral direct thrombin inhibitors （DTIs） in special populations. METHODS Led by the Sichuan Academy of Medical Sciences & Sichuan Provincial People’s Hospital（the Affiliated Hospital of UESTC）， a multidisciplinary working group was formed comprising experts from multiple fields， including clinical pharmacy， cardiac surgery， obstetrics， pediatrics and evidence-based medicine. Through literature review and the Delphi method， clinical questions regarding the efficacy and safety of parenteral DTIs used in special populations were identified. A structured design was adopted using the “Population-Intervention-Comparison-Outcome” （PICO） framework；systematic searches were conducted in CJFD， PubMed， Embase and other databases. Relevant evidence from randomized controlled trials，cohort studies and systematic reviews were included and synthesized. Evidence quality was assessed using the Grading of Recommendations Assessment，Development and Evaluation （GRADE） approach， and recommendations were formulated through three rounds of Delphi surveys and expert consensus meetings. RESULTS &CONCLUSIONS Seven clinical questions were ultimately selected （with a consensus rate exceeding 90%）， resulting in the formulation of seven recommendations on the use of parenteral DTIs in special populations， including children， pregnant women， patients with hepatic or renal impairment， patients with mesenteric venous thrombosis， and individuals with thrombophilia. These recommendations clarify the preferred agents， dosing ranges， monitoring parameters， and safety management strategies for parenteral DTIs in these special populations. This expert consensus， which is formulated based on the best available evidence， provides evidence-based guidance for standardized and individualized use of parenteral DTIs in special populations.

Immune-stimulating antibody drug conjugate (ISAC) can not only effectively solve the defects of stimulator of interferon genes (STING) agonists by coupling antibodies with STING agonists through the targeting of antibodies, but also play a synergistic role with antibodies to further improve the efficacy of STING agonists. This review first provides a concise overview of the current research landscape of ISACs and STING agonists, systematically elaborates on evolving trends in STING agonist development, and subsequently summarizes the mechanistic advances in STING ISAC research. Special emphasis is placed on representative STING ISAC candidates in preclinical/clinical development. Finally, the future directions of STING ISACs are critically discussed with perspectives and recommendations, aiming to provide theoretical insights and practical guidance for future investigations.

ObjectiveTo investigate the role and mechanism of Lck/Yes-related novel protein tyrosine kinase （Lyn） on lipopolysaccharide （LPS）-induced M1-type polarization of macrophage. MethodsThe LentiCRISPR-V2 plasmid was digested with the restriction endonuclease BSMBI-V2， and the digested DNA fragments were recovered. The digested plasmid was ligated with Lyn-sgRNA using T4 ligase to generate the Lenti-Lyn-gRNA lentivirus. THP-1 cells were infected with the Lenti-Lyn-gRNA lentivirus to obtain a stable cell line with Lyn knockout， and a monoclonal THP-1 cell line with complete Lyn knockout （Lyn^⁻/⁻） was established subsequently. Wild-type Lyn （Lyn^WT） and Lyn^⁻/⁻ THP-1 cells were induced with 100 ng/mL phorbol myristate acetate （PMA） for 48 h to differentiate into M0 macrophages， which were further polarized into M1 macrophages by stimulation with 100 ng/mL LPS for 24 h. Quantitative real-time polymerase chain reaction （qPCR） was performed to detect the expression of M0 macrophage markers， including integrin αM （CD11b）， macrophage antigen （CD68）， and monocyte differentiation antigen （CD14）. The expression of Lyn in M1 macrophages differentiated from wild-type THP-1 cells （Lyn^WT-M1） was measured by qPCR， and the ratio of phosphorylated Lyn to total Lyn （P-Lyn/Lyn） in Lyn^WT-M1 cells was determined by Western blot. In M1 macrophages differentiated from Lyn-knockout THP-1 cells （Lyn^⁻/⁻-M1）， qPCR was used to detect the mRNA expression of inducible nitric oxide synthase （iNOS）， interleukin-6 （IL-6）， and chemokine （C-X-C motif） ligand 10 （CXCL-10）. Western blot was conducted to assess the protein expression of iNOS， as well as the protein levels of molecules related to the Janus kinase 1 （JAK1）-signal transducer and activator of transcription 1 （STAT1）signaling pathway， including JAK1， phosphorylated JAK1 （P-JAK1）， STAT1， and phosphorylated STAT1 （P-STAT1）. Additionally， the expression of the M1 macrophage marker cluster of differentiation 80 （CD80） was analyzed by flow cytometry. ResultsThe Lyn^-/- monoclonal cell line was successfully constructed. The expression of CD11b was significantly elevated in Lyn^-/- M0 macrophages， and the differentiation of M1 macrophages was successful. Knockdown of Lyn inhibited mRNA expression of iNOS， IL⁃6， CXCL⁃10， protein expression of iNOS and CD80 expression in M1 macrophages （P<0.05）. Western blot assay showed that Lyn knockdown inhibited protein expression of JAK1 and P-STAT1 （P<0.01）. ConclusionAfter CRISPR/Cas9-mediated Lyn knockout， the expression levels of JAK1 and P-STAT1， the key molecules in the JAK/STAT signaling pathway of M1 macrophages， are significantly downregulated； concomitantly， the expression of M1 macrophage-specific secretory factors （iNOS， IL⁃6， CXCL⁃10 mRNA） and CD80 is also downregulated， which may be achieved via targeted regulation of the JAK1/P-STAT1-mediated JAK/STAT signaling pathway.

BACKGROUND:At present,the pathogenesis of osteoarthritis is still unclear,and there is a lack of effective means to control the disease.Research on osteoarthritis is mostly concentrated in the field of immunity,and there are few studies in the field of oxidative stress. OBJECTIVE:To explore the roles of oxidative stress and immune infiltration in osteoarthritis and to predict related miRNAs and therapeutic agents. METHODS:The GSE55235 dataset(10 samples of osteoarthritis and 10 healthy control samples)and the GSE55457 dataset(10 samples of osteoarthritis and 10 healthy control samples)were obtained from the GEO database for merging to obtain their differentially expressed genes that were combined with oxidative stress genes to get the differentially expressed genes of oxidative stress.The differentially expressed genes of oxidative stress were analyzed for KEGG and GO enrichment,and the osteoarthritis pathways and biological processes were evaluated using GSEA enrichment analysis.The protein-protein interaction network was constructed using the STRING online website and Cytoscape software,and the Degree algorithm was run to get the key genes.The GSE1919 dataset was obtained from the GEO database as a validation dataset,and the key genes were analyzed by variance analysis and receiver operating characteristic curve analysis to get the core genes.In addition,immune infiltration was evaluated by CIBERSORT and the correlation between core genes and immune cells was explored.miRNA prediction of core genes was performed using TargetScan and target drugs were predicted using the DSigDB database. RESULTS AND CONCLUSION:Sixty-five differentially expressed genes and five core genes(IL1B,CXCL8,MYC,NFKBIA,JUN)associated with oxidative stress were identified.Enrichment analysis showed that differentially expressed genes associated with oxidative stress were concentrated in the pathways of oxidative stress,interleukin-17,osteoclast differentiation,fluid shear stress and atherosclerosis.The area under the receiver operating characteristic curve for the five core genes exceeded 0.85,indicating their excellent specificity and sensitivity in diagnosing bone and joint conditions,as well as their close association with immune cells.The predicted miRNA was has-miR-3937,and the therapeutic small-molecule drugs were metformin,ionomycin and celecoxib.To conclude,oxidative stress and immune infiltration exist in osteoarthritis,and immune infiltration is involved in activating oxidative stress.The core genes and predicted miRNAs can be used as novel markers for the diagnosis of osteoarthritis,and small molecule drugs are predicted to treat osteoarthritis.

Background/Aims: Endoscopic radiofrequency ablation (ERFA) is a treatment option for superficial esophageal squamous cell neoplasia (ESCN), with a relatively low risk of stenosis; however, the long-term outcomes remain unclear. We aimed to compare the long-term outcomes of patients with widespread superficial ESCN who underwent endoscopic submucosal dissection (ESD) or ERFA. Methods: We retrospectively analyzed the clinical data of patients with superficial ESCN who underwent ESD or ERFA between January 2015 and December 2021. The primary outcome measure was recurrence-free survival. Results: Ninety-two and 33 patients with superficial ESCN underwent ESD and ERFA, respectively. The en bloc, R0, and curative resection rates for ESD were 100.0%, 90.2%, and 76.1%, respectively. At 12 months, the complete response rate was comparable between the two groups (94.6% vs 90.9%, p=0.748). During a median follow-up of 66 months, recurrence-free survival was significantly longer in the ESD group than in the ERFA group (p=0.004), while no significant differences in overall survival (p=0.845) and disease-specific survival (p=0.494) were observed.Preoperative diagnosis of intramucosal cancer (adjusted hazard ratio, 5.55; vs high-grade intraepithelial neoplasia) was an independent predictor of recurrence. Significantly fewer patients in the ERFA group experienced stenosis compare to ESD group (15.2% vs 38.0%, p=0.016). Conclusions The risk of recurrence was higher for ERFA than ESD for ESCN but overall survival was not affected. The risk of esophageal stenosis was significantly lower for patients who underwent ERFA.

This study aims to comprehensively analyze the material basis of toad visceral oil(hereafter referred to as toad oil), and explore the pharmacological effect of toad oil on atopic dermatitis(AD). Ultra-high performance liquid chromatography-linear ion trap/orbitrap high-resolution mass spectrometry(UHPLC-LTQ-Orbitrap-MS) and gas chromatography-mass spectrometry(GC-MS) were employed to comprehensively identify the chemical components in toad oil. The animal model of AD was prepared by the hapten stimulation method. The modeled animals were respectively administrated with positive drug(0.1% hydrocortisone butyrate cream) and low-and high-doses(1%, 10%) of toad oil by gavage. The effect of toad oil on AD was evaluated with the AD score, ear swelling rate, spleen index, and pathological section results as indicators. A total of 99 components were identified by UHPLC-LTQ-Orbitrap-MS, including 14 bufadienolides, 7 fatty acids, 6 alkaloids, 10 ketones, 18 amides, and other compounds. After methylation of toad oil samples, a total of 20 compounds were identified by GC-MS. Compared with the model group, the low-and high-dose toad oil groups showed declined AD score, ear swelling rate, and spleen index, alleviated skin lesions, and reduced infiltrating mast cells. This study comprehensively analyzes the chemical composition and clarifies the material basis of toad oil. Meanwhile, this study proves that toad oil has a good therapeutic effect on AD and is a reserve resource of traditional Chinese medicine for external use in the treatment of AD.
Animals ; Dermatitis, Atopic/immunology* ; Disease Models, Animal ; Mice ; Male ; Gas Chromatography-Mass Spectrometry ; Humans ; Bufonidae ; Oils/administration & dosage* ; Chromatography, High Pressure Liquid ; Female ; Mice, Inbred BALB C

This study aims to explore the mechanism of Jiaotai Pills in treating depression based on metabolomics and network pharmacology. The chemical constituents of Jiaotai Pills were identified by UHPLC-Orbitrap Exploris 480, and the targets of Jiaotai Pills and depression were retrieved from online databases. STRING and Cytoscape 3.7.2 were used to construct the protein-protein interaction network of core targets of Jiaotai Pills in treating depression and the "compound-target-pathway" network. DAVID was used for Gene Ontology(GO) function and Kyoto Encyclopedia of Genes and Genomes(KEGG) pathway enrichment analyses of the core targets. The mouse model of depression was established with chronic unpredictable mild stress(CUMS) and treated with different doses of Jiaotai Pills. The behavioral changes and pathological changes in the hippocampus were observed. UHPLC-Orbitrap Exploris 120 was used for metabolic profiling of the serum, from which the differential metabolites and related metabolic pathways were screened. A "metabolite-reaction-enzyme-gene" network was constructed for the integrated analysis of metabolomics and network pharmacology. A total of 34 chemical components of Jiaotai Pills were identified, and 143 core targets of Jiaotai Pills in treating depression were predicted, which were mainly involved in the arginine and proline, sphingolipid, and neurotrophin metabolism signaling pathways. The results of animal experiments showed that Jiaotai Pills alleviated the depression behaviors and pathological changes in the hippocampus of the mouse model of CUMS-induced depression. In addition, Jiaotai Pills reversed the levels of 32 metabolites involved in various pathways such as arginine and proline metabolism, sphingolipid metabolism, and porphyrin metabolism in the serum of model mice. The integrated analysis showed that arginine and proline metabolism, cysteine and methionine metabolism, and porphyrin metabolism might be the key pathways in the treatment of depression with Jiaotai Pills. In conclusion, metabolomics combined with network pharmacology clarifies the antidepressant mechanism of Jiaotai Pills, which may provide a basis for the clinical application of Jiaotai Pills in treating depression.
Animals ; Drugs, Chinese Herbal/chemistry* ; Depression/genetics* ; Mice ; Network Pharmacology ; Metabolomics ; Male ; Disease Models, Animal ; Humans ; Protein Interaction Maps/drug effects* ; Antidepressive Agents

Background/Aims: Endoscopic radiofrequency ablation (ERFA) is a treatment option for superficial esophageal squamous cell neoplasia (ESCN), with a relatively low risk of stenosis; however, the long-term outcomes remain unclear. We aimed to compare the long-term outcomes of patients with widespread superficial ESCN who underwent endoscopic submucosal dissection (ESD) or ERFA. Methods: We retrospectively analyzed the clinical data of patients with superficial ESCN who underwent ESD or ERFA between January 2015 and December 2021. The primary outcome measure was recurrence-free survival. Results: Ninety-two and 33 patients with superficial ESCN underwent ESD and ERFA, respectively. The en bloc, R0, and curative resection rates for ESD were 100.0%, 90.2%, and 76.1%, respectively. At 12 months, the complete response rate was comparable between the two groups (94.6% vs 90.9%, p=0.748). During a median follow-up of 66 months, recurrence-free survival was significantly longer in the ESD group than in the ERFA group (p=0.004), while no significant differences in overall survival (p=0.845) and disease-specific survival (p=0.494) were observed.Preoperative diagnosis of intramucosal cancer (adjusted hazard ratio, 5.55; vs high-grade intraepithelial neoplasia) was an independent predictor of recurrence. Significantly fewer patients in the ERFA group experienced stenosis compare to ESD group (15.2% vs 38.0%, p=0.016). Conclusions The risk of recurrence was higher for ERFA than ESD for ESCN but overall survival was not affected. The risk of esophageal stenosis was significantly lower for patients who underwent ERFA.