ObjectiveThis paper aims to find the identified and validated clinical biomarker data building upon a clinical study of early-phase phase Ⅱ and investigate the correlation analysis of Huanglian Jiedu Wan on syndrome improvement and clinical biomarkers in the treatment of "excess heat-toxicity" based on a machine learning model. Additionally， the effective prediction of clinical biomarker values for the main symptoms of the "excess heat-toxicity" syndrome was assessed. MethodsA total of 229 patients meeting the inclusion criteria for "excess heat-toxicity" syndrome were randomly divided into the Huanglian Jiedu Wan group and the placebo group. Syndrome score transition matrices were constructed for the Huanglian Jiedu Wan group and the placebo group based on three main symptoms of "excess heat-toxicity" syndrome， such as oral ulcers， sore throat， and gum swelling and pain. Data from the patients with these three syndromes were also integrated for an overall analysis. The corresponding syndrome score transition matrices were further constructed to visualize symptom change trends of the patients in the two groups via heatmaps. Based on the identified and validated clinical biomarkers related to inflammation， oxidative stress， and energy metabolism in the early phase， Spearman correlation analysis was employed to analyze and evaluate the associations between clinical biomarkers and syndrome improvement. Key clinical biomarkers reflecting the effect of Huanglian Jiedu Wan were screened through the comparison of differences between groups. An extreme gradient boosting （XGBoost） algorithm was used to develop a prediction model for main symptom classification， with classification performance evaluated through 10-fold cross-validation. Feature importance analysis was applied to identify variables with the greatest contribution to the prediction result. ResultsThe syndrome transition matrix results indicated that the Huanglian Jiedu Wan group showed a superior effect to the placebo group in improving oral ulcers， sore throat， and overall symptoms， with significant effects observed especially in sore throat and overall symptom analyses （P<0.01）. Spearman correlation analysis revealed that several clinical biomarkers positively correlated with "excess heat-toxicity" syndrome and its main symptom improvement， were also called "heat-related biomarkers"， including succinic acid， α-ketoglutaric acid， glycine， lactic acid， adenosine monophosphate （AMP）， tumor necrosis factor-α （TNF-α）， interferon-γ （IFN-γ）， interleukin-1β （IL-1β）， interleukin-4 （IL-4）， interleukin-6 （IL-6）， interleukin-8 （IL-8）， interleukin-10 （IL-10）， and so on. Conversely， clinical biomarkers negatively correlated with symptom severity， were also called "heat-clearing related biomarkers" after administration of Huanglian Jiedu Wan， including malic acid， fumaric acid， cis-aconitic acid， adrenocorticotropic hormone （ACTH）， IL-1β， IL-4， IL-8， succinic acid， and citric acid. The XGBoost classification model using all 52 biomarkers as variables achieved an average test accuracy of 0.754 and an average F1 score of 0.777. Feature importance analysis identified the scores of glutamic acid in saliva and IL-6 were the highest in all the variables， with importance scores of 0.081 and 0.080， respectively. After screening out 14 key variables and optimizing the parameters， model performance improved to an average accuracy of 0.758 and an F1 score of 0.798. Feature importance analysis further determined that the glutamic acid in saliva and IL-6 showed obvious changes after screening the variables， confirming the good syndrome prediction ability of the model constructed by these key clinical biomarkers. ConclusionThis study systematically elucidates the correlation between syndrome improvement and clinical biomarkers of Huanglian Jiedu Wan in the treatment of "excess heat-toxicity" syndrome. An XGBoost classification model based on key clinical biomarkers is successfully established， achieving effective prediction of the symptoms related to the "excess heat-toxicity" syndrome such as oral ulcers and sore throat and providing a new insight for objective identification of traditional Chinese medicine syndromes.

ObjectiveThis paper aims to find the identified and validated clinical biomarker data building upon a clinical study of early-phase phase Ⅱ and investigate the correlation analysis of Huanglian Jiedu Wan on syndrome improvement and clinical biomarkers in the treatment of "excess heat-toxicity" based on a machine learning model. Additionally， the effective prediction of clinical biomarker values for the main symptoms of the "excess heat-toxicity" syndrome was assessed. MethodsA total of 229 patients meeting the inclusion criteria for "excess heat-toxicity" syndrome were randomly divided into the Huanglian Jiedu Wan group and the placebo group. Syndrome score transition matrices were constructed for the Huanglian Jiedu Wan group and the placebo group based on three main symptoms of "excess heat-toxicity" syndrome， such as oral ulcers， sore throat， and gum swelling and pain. Data from the patients with these three syndromes were also integrated for an overall analysis. The corresponding syndrome score transition matrices were further constructed to visualize symptom change trends of the patients in the two groups via heatmaps. Based on the identified and validated clinical biomarkers related to inflammation， oxidative stress， and energy metabolism in the early phase， Spearman correlation analysis was employed to analyze and evaluate the associations between clinical biomarkers and syndrome improvement. Key clinical biomarkers reflecting the effect of Huanglian Jiedu Wan were screened through the comparison of differences between groups. An extreme gradient boosting （XGBoost） algorithm was used to develop a prediction model for main symptom classification， with classification performance evaluated through 10-fold cross-validation. Feature importance analysis was applied to identify variables with the greatest contribution to the prediction result. ResultsThe syndrome transition matrix results indicated that the Huanglian Jiedu Wan group showed a superior effect to the placebo group in improving oral ulcers， sore throat， and overall symptoms， with significant effects observed especially in sore throat and overall symptom analyses （P<0.01）. Spearman correlation analysis revealed that several clinical biomarkers positively correlated with "excess heat-toxicity" syndrome and its main symptom improvement， were also called "heat-related biomarkers"， including succinic acid， α-ketoglutaric acid， glycine， lactic acid， adenosine monophosphate （AMP）， tumor necrosis factor-α （TNF-α）， interferon-γ （IFN-γ）， interleukin-1β （IL-1β）， interleukin-4 （IL-4）， interleukin-6 （IL-6）， interleukin-8 （IL-8）， interleukin-10 （IL-10）， and so on. Conversely， clinical biomarkers negatively correlated with symptom severity， were also called "heat-clearing related biomarkers" after administration of Huanglian Jiedu Wan， including malic acid， fumaric acid， cis-aconitic acid， adrenocorticotropic hormone （ACTH）， IL-1β， IL-4， IL-8， succinic acid， and citric acid. The XGBoost classification model using all 52 biomarkers as variables achieved an average test accuracy of 0.754 and an average F1 score of 0.777. Feature importance analysis identified the scores of glutamic acid in saliva and IL-6 were the highest in all the variables， with importance scores of 0.081 and 0.080， respectively. After screening out 14 key variables and optimizing the parameters， model performance improved to an average accuracy of 0.758 and an F1 score of 0.798. Feature importance analysis further determined that the glutamic acid in saliva and IL-6 showed obvious changes after screening the variables， confirming the good syndrome prediction ability of the model constructed by these key clinical biomarkers. ConclusionThis study systematically elucidates the correlation between syndrome improvement and clinical biomarkers of Huanglian Jiedu Wan in the treatment of "excess heat-toxicity" syndrome. An XGBoost classification model based on key clinical biomarkers is successfully established， achieving effective prediction of the symptoms related to the "excess heat-toxicity" syndrome such as oral ulcers and sore throat and providing a new insight for objective identification of traditional Chinese medicine syndromes.

Background: s/Aims: Sarcomatoid hepatocellular carcinoma (HCC) is a rare histological subtype of HCC characterized by extremely poor prognosis; however, its molecular characterization has not been elucidated. Methods: In this study, we conducted an integrated multiomics study of whole-exome sequencing, RNA-seq, spatial transcriptome, and immunohistochemical analyses of 28 paired sarcomatoid tumor components and conventional HCC components from 10 patients with sarcomatoid HCC, in order to identify frequently altered genes, infer the tumor subclonal architectures, track the genomic evolution, and delineate the transcriptional characteristics of sarcomatoid HCCs. Results: Our results showed that the sarcomatoid HCCs had poor prognosis. The sarcomatoid tumor components and the conventional HCC components were derived from common ancestors, mostly accessing similar mutational processes. Clonal phylogenies demonstrated branched tumor evolution during sarcomatoid HCC development and progression. TP53 mutation commonly occurred at tumor initiation, whereas ARID2 mutation often occurred later. Transcriptome analyses revealed the epithelial–mesenchymal transition (EMT) and hypoxic phenotype in sarcomatoid tumor components, which were confirmed by immunohistochemical staining. Moreover, we identified ARID2 mutations in 70% (7/10) of patients with sarcomatoid HCC but only 1–5% of patients with non-sarcomatoid HCC. Biofunctional investigations revealed that inactivating mutation of ARID2 contributes to HCC growth and metastasis and induces EMT in a hypoxic microenvironment. Conclusions We offer a comprehensive description of the molecular basis for sarcomatoid HCC, and identify genomic alteration (ARID2 mutation) together with the tumor microenvironment (hypoxic microenvironment), that may contribute to the formation of the sarcomatoid tumor component through EMT, leading to sarcomatoid HCC development and progression.

Background: s/Aims: Sarcomatoid hepatocellular carcinoma (HCC) is a rare histological subtype of HCC characterized by extremely poor prognosis; however, its molecular characterization has not been elucidated. Methods: In this study, we conducted an integrated multiomics study of whole-exome sequencing, RNA-seq, spatial transcriptome, and immunohistochemical analyses of 28 paired sarcomatoid tumor components and conventional HCC components from 10 patients with sarcomatoid HCC, in order to identify frequently altered genes, infer the tumor subclonal architectures, track the genomic evolution, and delineate the transcriptional characteristics of sarcomatoid HCCs. Results: Our results showed that the sarcomatoid HCCs had poor prognosis. The sarcomatoid tumor components and the conventional HCC components were derived from common ancestors, mostly accessing similar mutational processes. Clonal phylogenies demonstrated branched tumor evolution during sarcomatoid HCC development and progression. TP53 mutation commonly occurred at tumor initiation, whereas ARID2 mutation often occurred later. Transcriptome analyses revealed the epithelial–mesenchymal transition (EMT) and hypoxic phenotype in sarcomatoid tumor components, which were confirmed by immunohistochemical staining. Moreover, we identified ARID2 mutations in 70% (7/10) of patients with sarcomatoid HCC but only 1–5% of patients with non-sarcomatoid HCC. Biofunctional investigations revealed that inactivating mutation of ARID2 contributes to HCC growth and metastasis and induces EMT in a hypoxic microenvironment. Conclusions We offer a comprehensive description of the molecular basis for sarcomatoid HCC, and identify genomic alteration (ARID2 mutation) together with the tumor microenvironment (hypoxic microenvironment), that may contribute to the formation of the sarcomatoid tumor component through EMT, leading to sarcomatoid HCC development and progression.

Background: s/Aims: Sarcomatoid hepatocellular carcinoma (HCC) is a rare histological subtype of HCC characterized by extremely poor prognosis; however, its molecular characterization has not been elucidated. Methods: In this study, we conducted an integrated multiomics study of whole-exome sequencing, RNA-seq, spatial transcriptome, and immunohistochemical analyses of 28 paired sarcomatoid tumor components and conventional HCC components from 10 patients with sarcomatoid HCC, in order to identify frequently altered genes, infer the tumor subclonal architectures, track the genomic evolution, and delineate the transcriptional characteristics of sarcomatoid HCCs. Results: Our results showed that the sarcomatoid HCCs had poor prognosis. The sarcomatoid tumor components and the conventional HCC components were derived from common ancestors, mostly accessing similar mutational processes. Clonal phylogenies demonstrated branched tumor evolution during sarcomatoid HCC development and progression. TP53 mutation commonly occurred at tumor initiation, whereas ARID2 mutation often occurred later. Transcriptome analyses revealed the epithelial–mesenchymal transition (EMT) and hypoxic phenotype in sarcomatoid tumor components, which were confirmed by immunohistochemical staining. Moreover, we identified ARID2 mutations in 70% (7/10) of patients with sarcomatoid HCC but only 1–5% of patients with non-sarcomatoid HCC. Biofunctional investigations revealed that inactivating mutation of ARID2 contributes to HCC growth and metastasis and induces EMT in a hypoxic microenvironment. Conclusions We offer a comprehensive description of the molecular basis for sarcomatoid HCC, and identify genomic alteration (ARID2 mutation) together with the tumor microenvironment (hypoxic microenvironment), that may contribute to the formation of the sarcomatoid tumor component through EMT, leading to sarcomatoid HCC development and progression.

Medical institutions, with their clinical practice foundation and abundant human use experience data, have become important carriers for the inheritance and innovation of traditional Chinese medicine(TCM) and the "cradles" of the preparation of new TCM. To effectively promote the transformation of new TCM originating from the TCM clinical practice in medical institutions and establish an effective evaluation index system for the transformation of new TCM conforming to the characteristics of TCM, consensus experts adopted the literature research, questionnaire survey, Delphi method, etc. By focusing on the policy and technical evaluation of new TCM originating from the TCM clinical practice in medical institutions, a comprehensive evaluation from the dimensions of drug safety, efficacy, feasibility, and characteristic advantages was conducted, thus forming a comprehensive evaluation system with four primary indicators and 37 secondary indicators. The expert consensus reached aims to encourage medical institutions at all levels to continuously improve the high-quality research and development and transformation of new TCM originating from the TCM clinical practice in medical institutions and targeted at clinical needs, so as to provide a decision-making basis for the preparation, selection, cultivation, and transformation of new TCM for medical institutions, improve the development efficiency of new TCM, and precisely respond to the public medication needs.
Medicine, Chinese Traditional/standards* ; Humans ; Consensus ; Drugs, Chinese Herbal/therapeutic use* ; Surveys and Questionnaires

Infant, Newborn ; Humans ; Quality Improvement ; Intensive Care Units, Neonatal

Aim To explore the molecular mechanism of Selaginella moelledorffii Hieron. in the treatment of laryngeal cancer. Methods According to the relevant literature reports, the chemical constituents of S. moellendorffii were obtained, and the active ingredients were screened out through the SwissADME database, and the targets were screened through the PharmMapper database. The laryngeal cancer-related targets were collected by searching OMIM and other databases, and the Venny 2.1.0 online platform was used to obtain the intersection of the two. Protein interaction analysis of the potential targets was performed using the STRNG platform. GO functional analysis and KEGG pathway analysis was carried out using DAVID database. Visual networks were built with Cytoscape 3.8.0 software. Molecular docking was validated by SYBYL-X 2. 0 software. MTT method, Hoechst 33258 staining method and Western blotting were also used for validation. Results At the molecular level, a total of 110 active ingredients of S. moellendorffii and 82 drug targets were screened out, 1,608 targets related to laryngeal cancer, and intersection of 34 targets. GO analysis yielded 135 entries, and KEGG analysis yielded a total of 61 pathways. Molecular docking results showed that the 11 key active ingredients such as 2", 3"-dihydrooch-naflavone wood flavonoids and 4 core target proteins such as MAPK1 had 95. 5% of good docking activity. At the cellular level, SM-BFRE was screened for its strongest inhibitory effect on laryngeal cancer cell proliferation through MTT assay. Furthermore, Hoechst 33258 staining showed that the decrease in Hep-2 cell viability produced by SM-BFRE was related to cell apoptosis. Finally, Western blot verified that SM-BFRE inhibited PI3K/Akt/NF through inhibition- K B/COX-2 pathway to induce apoptosis in laryngeal cancer cells. Conclusions To sum up, it fully reflects the multicomponent, multi-target, and multi-channel synergistic effect of S. moellendorffii in the treatment of laryngeal cancer, and provides a theoretical reference for further elucidation of the mechanism of action of S. moellendorffii in the treatment of laryngeal cancer.

Objective To investigate the effects of Simo decoction on duodenal microinflammation and NOD-like receptor thermal protein domain associated protein 3(NLRP3)/cysteinyl aspartate-specific proteinase-1(Caspase-1)/gasdermin D(GSDMD)signaling pathway in rats with functional dyspepsia(FD).Methods The FD model was established by multifactorial method.SD rats were randomly divided into normal group,model group(FD model),positive control group(gavage administration of 0.305 mg·kg-1 mosapride injection)and experimental-H,-M,-L groups(gavage administration of 5.62,2.81,1.40 g·kg-1 Simo decoction).Small intestinal advancement rate and gastric emptying rate was determined;the levels of interleukin(IL)-1 β and IL-18 in serum were determined by enzyme linked immunosorbent assay(ELISA);the protein expression of NLRP3 and GSDMD in duodenal tissue was detected by Western blotting.Results The gastric emptying rates of normal,model,positive control and experimental-H,-M,-Lgroupswere(58.34±5.72)％,(29.16±8.37)％,(48.77±6.10)％,(48.35±6.04)％,(48.20±3.49)％and(39.24±4.20)％;the small intestinal propulsion rates were(82.01±7.55)％,(41.95±9.53)％,(64.61±10.18)％,(75.04±9.76)％,(60.58±7.13)％and(45.89±7.40)％;serum IL-1 β expression were(12.86±0.88),(43.73±4.60),(18.84±0.86),(24.61±1.57),(19.14±0.77)and(29.04±0.72)pg·mL-1;IL-18 expressions were(95.00±3.74),(170.60±8.78),(108.50±3.05),(118.90±3.45),(99.90±8.70)and(141.00±3.71)pg·mL-1;the relative expression levels of NLRP3 proteins were 0.32±0.02,0.84±0.05,0.42±0.03,0.48±0.02,0.61±0.04 and 0.62±0.05;the relative expression levels of GSDMD proteins were 0.34±0.05,0.93±0.06,0.35±0.03,0.52±0.02,0.53±0.06 and 0.55±0.05,respectively.Compared with the normal group,the above indexes in the model group have statistical significance;compared with the model group,the above indexes in the experimental-H group and the positive control group also have statistical significance(P＜0.01 or P＜0.05).Conclusion Simo decoction can effectively improve the general condition and duodenal microinflammation in FD rats,and the mechanism may be related to the inhibition of duodenal NLRP3/Caspase-1/GSDMD signaling pathway.

Coronary artery bypass grafting (CABG) is one of the most effective revascularization treatments for coronary heart disease. Secondary prevention strategies, which rely on antiplatelet and lipid-lowering drugs, are crucial after CABG to ensure the durability of revascularization treatment effects and prevent adverse cardiovascular and cerebrovascular events in the medium to long term. Previous research conducted by Professor Zhao Qiang's team from Ruijin Hospital of Shanghai Jiao Tong University, known as the DACAB study, indicated that dual antiplatelet therapy (DAPT, specifically ticagrelor+aspirin) after CABG can enhance venous graft patency. However, it remains uncertain whether DAPT can further improve the medium to long-term clinical outcomes of CABG patients. Recently, the team reported the medium to long-term follow-up results of the DACAB study, termed the DACAB-FE study, finding that DAPT administered after CABG can reduce the incidence of major cardiovascular events over five years and improve patients' medium to long-term clinical outcomes. This article will interpret the methodological highlights and significant clinical implications of the DACAB-FE study.