The importance of consensus research in medical decision-making has become increasinglyprominent. However, this field has long lacked unified terminology definitions and reporting standards, leading to significant heterogeneity in study design, implementation, and result presentation that affects the credibility and reproducibility of outcomes. The ACCurate COnsensus Reporting Document (ACCORD) in the field of biomedical research provides a structured writing framework for various consensus methods such as the Delphi method and nominal group technique, aiming to enhance the completeness and transparency of study reports. Combined with specific cases, this article interprets the core items of ACCORD, offering references for the design, implementation, and reporting of high-quality consensus research in China.

ObjectiveTo observe the effects of Jiangtang No. 3 prescription on inflammatory pathways and insulin resistance-related indicators in rats with type 2 diabetes mellitus （T2DM）， and to elucidate its molecular mechanism in combating diabetes. MethodsA T2DM rat model was established using a high-fat diet combined with intraperitoneal injection of streptozotocin （STZ）. Successfully modeled rats were randomly assigned to the model group， metformin group， and low-， medium-， and high-dose Jiangtang No. 3 prescription groups， and a normal group was also set. Daily gavage was administered for 8 weeks as follows： metformin at 0.1 g·kg^-1·d^-1， Jiangtang No. 3 prescription granules at 1.62， 3.24， 6.48 g·kg^-1·d^-1 for the respective dose groups， and sterile water for the normal and model groups. Rat body weight， fasting blood glucose （FBG）， oral glucose tolerance test （OGTT）， and insulin tolerance test （ITT） were measured. After drug intervention， enzyme-linked immunosorbent assay （ELISA） was used to determine serum levels of total cholesterol （TC）， triglycerides （TG）， low-density lipoprotein cholesterol （LDL）， high-density lipoprotein cholesterol （HDL）， non-esterified fatty acids （NEFA）， interleukin （IL）-1β， IL-18， and insulin （INS）. Hematoxylin-eosin （HE） staining was used to observe morphological changes in adipose tissue. Real-time quantitative PCR was used to detect the mRNA expression of Toll-like receptor 4 （TLR4）， nuclear factor-κB （NF-κB）， NOD-like receptor protein 3 （NLRP3）， Caspase-1， IL-1β， IL-18， and gasdermin D （GSDMD） in adipose tissue. Western blot was used to measure the corresponding protein expression levels. ResultsCompared with the model group， Jiangtang No. 3 prescription groups exhibited significantly increased body weight （P<0.05， P<0.01）， significantly reduced FBG （P<0.05， P<0.01）， significant reductions in TC， TG， NEFA， and LDL （P<0.05， P<0.01）， and a significant increase in HDL （P<0.01）. Serum levels of inflammatory mediators IL-1β and IL-18 were significantly decreased （P<0.01）， the homeostatic model assessment of insulin resistance （HOMA-IR） index was significantly reduced （P<0.05， P<0.01）， and adipose tissue pathology was improved. The protein expression levels of TLR4， NF-κB， NLRP3， Caspase-1， IL-1β， IL-18， and GSDMD were markedly decreased （P<0.05， P<0.01）， and the mRNA expression levels of these indicators were also significantly downregulated （P<0.05， P<0.01）. Some effects were superior to those of the positive control drug metformin， and certain indicators exhibited dose-dependent improvements. ConclusionT2DM rats display significant inflammatory responses， disordered glucose and lipid metabolism， and insulin resistance. Jiangtang No. 3 prescription effectively suppresses inflammatory mediators， improves glucose and lipid metabolism and insulin resistance， and ameliorates pathological changes in adipose tissue. Its mechanism may be related to the regulation of the TLR4/NF-κB/NLRP3 signaling pathway in visceral adipose tissue， thereby influencing downstream inflammatory mediators.

To systematically analyzed the reporting status of core elements in publicly available clinical practice guideline(hereafter referred to as "guideline") protocols published domestically and internationally over the past decade, identified existing problems, and provided evidence to inform the standardized writing and publication of future guideline protocols.

Objective To analyze the clinical and therapeutic characteristics of Epstein-Barr virus (EBV)-negative posttransplant lymphoproliferative disease (PTLD) with diffuse large B-cell lymphoma (DLBCL) in the context of specific cases and literature. Methods A case of EBV-negative DLBCL (GCB type) after kidney transplantation is reported. The patient was a 45-year-old male who underwent living-related kidney transplantation in 2016 and has been receiving triple immunosuppressive therapy with tacrolimus, mycophenolate mofetil and methylprednisolone since then. In 2024, the patient presented with intermittent fever, night sweats and gastrointestinal symptoms. The diagnosis was confirmed by endoscopic pathology, immunohistochemical staining and positron emission tomography/computed tomography. The R-CDOP regimen (rituximab + cyclophosphamide + liposomal doxorubicin + vincristine + dexamethasone) was used for treatment. Results The patient was diagnosed with EBV-negative DLBCL (GCB type, Ann Arbor stage Ⅳ B). After 4 cycles of R-CDOP chemotherapy, the efficacy assessment was partial remission, and the transplant kidney function remained stable. Conclusions For EBV-negative PTLD after kidney transplantation, it is necessary to break through the "virus-dependent" diagnostic thinking. In clinical practice, the focus should be on protecting the transplant kidney, and individualized treatment plans should be developed for patients.

ObjectiveTo explore the potential mechanism of Xiaoqinglongtang（XQL） in the prevention and treatment of high altitude pulmonary edema（HAPE） by network pharmacology， molecular docking， and molecular dynamics simulation， and to verify it by in vivo animal model. MethodsIn this study， the active ingredients， drug targets， and HAPE-related targets of XQL were collected from BATMAN-TCM， GeneCards， and Online Mendelian Inheritance in Man（OMIM） databases. The protein-protein interaction（PPI） network was constructed by using intersection targets， and the core targets were screened and visualized by Cytoscape software. Functional annotation and pathway analysis of the intersection targets were performed by gene ontology （GO） and Kyoto encyclopedia of genes and genomes （KEGG） functional enrichment. AutoDock and GROMACS were used to evaluate the binding ability of active ingredients to key targets. In the experimental verification part， a mouse model of HAPE induced by hypobaric hypoxia（simulated 6 000 m altitude for 48 h） was established. The control effect was evaluated by hematoxylin-eosin（HE） staining， lung tissue water content， lung tissue wet/dry weight ratio， real-time quantitative polymerase chain reaction（Real-time PCR） detection of gene expression levels， and immunohistochemistry and Western blot detection of key protein expression. ResultsA total of 355 active ingredients of XQL， 2 142 targets， 716 HAPE-related targets， and 236 intersection targets were obtained by network pharmacology analysis. Key core targets such as interleukin （IL）-6， tumor necrosis factor （TNF）， protein kinase B1 （Akt1）， and hypoxia-inducible factor-1α （HIF-1α） were screened. The results of GO analysis of common targets involved 738 biological processes（BP）， 72 cellular components（CC）， and 135 molecular functions（MF）. KEGG analysis effectively enriched two important signaling pathways： Phosphoinositol 3-kinase （PI3K）/Akt and HIF-1α. The results of molecular docking and molecular dynamics simulation showed that the screened active ingredients had good binding ability with key targets. In the HAPE model induced by hypobaric hypoxia（6 000 m， 48 h）， the lung tissue water content， lung tissue wet/dry weight ratio， and pathological injury score of the model group were significantly increased（P<0.01）， accompanied by exudation of a large number of red blood cells in the alveoli and alveolar interstitium， a significant increase in inflammatory cells， a significant widening of the alveolar septum， and mutual fusion between the alveoli. The XQL administration group significantly improved the above pathological changes（P<0.01）. The results of inflammatory factor expression showed that compared with the control group， the model group showed significantly up-regulated expression of TNF-α， IL-6， and IL-1β in the lung tissue（P<0.01）. Compared with the model group， the XQL administration group had significantly decreased expression of inflammatory factors（P<0.05， P<0.01）. The mRNA expression of key pathway related genes PI3K， Akt1， mammalian target of rapamycin（mTOR）， and HIF-1α was significantly increased in the model group（P<0.01）， and decreased in a concentration-dependent manner after XQL administration（P<0.05， P<0.01）. The expression levels of key proteins PI3K， phosphorylation（p）-PI3K， Akt1， p-Akt1， mTOR， p-mTOR， and HIF-1α in lung tissue were analyzed by immunohistochemistry and Western blot. Compared with the blank group， the model group showed increased expression of key proteins（P<0.05， P<0.01）. Compared with the model group， the XQL administration group exhibited decreased expression of key proteins（P<0.05， P<0.01）. ConclusionXQL can reduce lung inflammation and improve HAPE. The mechanism may be related to the regulation of PI3K/Akt/mTOR and HIF-1α pathways. This study provides a new idea and a theoretical basis for the treatment of HAPE with XQL.

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.

ObjectiveTo explore the potential mechanism of Xiaoqinglongtang（XQL） in the prevention and treatment of high altitude pulmonary edema（HAPE） by network pharmacology， molecular docking， and molecular dynamics simulation， and to verify it by in vivo animal model. MethodsIn this study， the active ingredients， drug targets， and HAPE-related targets of XQL were collected from BATMAN-TCM， GeneCards， and Online Mendelian Inheritance in Man（OMIM） databases. The protein-protein interaction（PPI） network was constructed by using intersection targets， and the core targets were screened and visualized by Cytoscape software. Functional annotation and pathway analysis of the intersection targets were performed by gene ontology （GO） and Kyoto encyclopedia of genes and genomes （KEGG） functional enrichment. AutoDock and GROMACS were used to evaluate the binding ability of active ingredients to key targets. In the experimental verification part， a mouse model of HAPE induced by hypobaric hypoxia（simulated 6 000 m altitude for 48 h） was established. The control effect was evaluated by hematoxylin-eosin（HE） staining， lung tissue water content， lung tissue wet/dry weight ratio， real-time quantitative polymerase chain reaction（Real-time PCR） detection of gene expression levels， and immunohistochemistry and Western blot detection of key protein expression. ResultsA total of 355 active ingredients of XQL， 2 142 targets， 716 HAPE-related targets， and 236 intersection targets were obtained by network pharmacology analysis. Key core targets such as interleukin （IL）-6， tumor necrosis factor （TNF）， protein kinase B1 （Akt1）， and hypoxia-inducible factor-1α （HIF-1α） were screened. The results of GO analysis of common targets involved 738 biological processes（BP）， 72 cellular components（CC）， and 135 molecular functions（MF）. KEGG analysis effectively enriched two important signaling pathways： Phosphoinositol 3-kinase （PI3K）/Akt and HIF-1α. The results of molecular docking and molecular dynamics simulation showed that the screened active ingredients had good binding ability with key targets. In the HAPE model induced by hypobaric hypoxia（6 000 m， 48 h）， the lung tissue water content， lung tissue wet/dry weight ratio， and pathological injury score of the model group were significantly increased（P<0.01）， accompanied by exudation of a large number of red blood cells in the alveoli and alveolar interstitium， a significant increase in inflammatory cells， a significant widening of the alveolar septum， and mutual fusion between the alveoli. The XQL administration group significantly improved the above pathological changes（P<0.01）. The results of inflammatory factor expression showed that compared with the control group， the model group showed significantly up-regulated expression of TNF-α， IL-6， and IL-1β in the lung tissue（P<0.01）. Compared with the model group， the XQL administration group had significantly decreased expression of inflammatory factors（P<0.05， P<0.01）. The mRNA expression of key pathway related genes PI3K， Akt1， mammalian target of rapamycin（mTOR）， and HIF-1α was significantly increased in the model group（P<0.01）， and decreased in a concentration-dependent manner after XQL administration（P<0.05， P<0.01）. The expression levels of key proteins PI3K， phosphorylation（p）-PI3K， Akt1， p-Akt1， mTOR， p-mTOR， and HIF-1α in lung tissue were analyzed by immunohistochemistry and Western blot. Compared with the blank group， the model group showed increased expression of key proteins（P<0.05， P<0.01）. Compared with the model group， the XQL administration group exhibited decreased expression of key proteins（P<0.05， P<0.01）. ConclusionXQL can reduce lung inflammation and improve HAPE. The mechanism may be related to the regulation of PI3K/Akt/mTOR and HIF-1α pathways. This study provides a new idea and a theoretical basis for the treatment of HAPE with XQL.

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.

The development of intestinal-type gastric cancer follows a progression from non-atrophic gastritis — atrophic gastritis — intestinal metaplasia — epithelial dysplasia — gastric cancer，known as the " inflammation-cancer transformation. " Leveraging the advantages of integrated traditional Chinese and Western medicine，while collaborating to inhibit this transformation，remains a research focus and challenge. The incidence of gastric cancer in China has declined with the continuous elucidation of the mechanisms behind inflammation-cancer transformation，innovations in early screening and diagnosis techniques in Western medicine，the establishment of risk stratification and treatment systems，and effective interventions through traditional Chinese medicine. Leveraging the theoretical and practical advantages of the " preventing disease before it occurs" philosophy of traditional Chinese medicine，particularly the concept of " preventing transformation in existing diseases，" is essential. This approach emphasizes shifting the focus of prevention and treatment to earlier stages of disease progression. Developing more effective and reliable strategies and innovative drugs that block the dynamic progression of the " inflammation-cancer transformation" in gastric cancer remains a key goal. This article reviews the latest progress in both basic and clinical research in this field，the issues related to high-level clinical research in traditional Chinese medicine，the construction of integrated diagnosis and treatment pathways combining Chinese and Western medicine，the establishment of efficacy evaluation standards，and the elucidation of the integration mechanisms of the complex system of traditional Chinese medicine. It also explores research directions and solutions within the context of multidisciplinary collaboration to provide insights and references to block inflammation-cancer transformation and to construct a gastric cancer prevention and control system with Chinese characteristics，thereby further enhancing the level of gastric cancer prevention and control.

Objective To investigate the effect of ubiquitin specific peptidase 22 (USP22) on the occurrence and development of esophageal squamous cell carcinoma (ESCC) under hypoxic conditions, and its regulatory relationship with hypoxia-inducible factor-1α (HIF-1α). Methods Western blotting and quantitative polymerase chain reaction were used to detect the differences in USP22 protein and mRNA expression between normal esophageal epithelial cells HEEC and ESCC cell lines KYSE30, KYSE150, EC9706, and TE-1 under normoxic (5% CO2, 20% O2, 75% N2) and hypoxic (5% CO2, 1% O2, 94% N2) conditions. By transfecting USP22 plasmid or siUSP22, ESCC cells were divided into a normoxia control group, a normoxia+USP22 group, a normoxia+siUSP22 group, a hypoxia control group, a hypoxia+USP22 group, and a hypoxia+siUSP22 group. The proliferation and migration abilities of cells in each group were detected. The expression of USP22 and HIF-1α under hypoxic conditions after up-regulating or down-regulating USP22 was detected, and their regulatory relationship was verified. The interaction between USP22 and HIF-1α was verified by co-immunoprecipitation (Co-IP) technique. Results Compared with HEEC cells, the expression of USP22 in ESCC cells was significantly increased (P<0.05). Up-regulation of USP22 expression promoted the proliferation and migration of ESCC cells, while silencing USP22 inhibited the proliferation and migration of ESCC cells (P<0.05). Under hypoxic conditions, the expression of USP22 and HIF-1α increased, and with the up-regulation of USP22 expression, the expression of HIF-1α also significantly increased (P<0.05). Co-IP experiment confirmed the binding between USP22 and HIF-1α. Conclusion Up-regulation of USP22 expression promotes the proliferation and migration of ESCC cells. Hypoxia microenvironment can induce the increase of USP22 expression in ESCC. USP22 may participate in the regulation of the occurrence and development of ESCC by directly binding to HIF-1α.