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 investigate the mechanisms by which Mahuang Lianqiao Chixiaodoutang （MLC） improves obesity-type polycystic ovary syndrome （PCOS） through the phosphatidylinositol 3-kinase （PI3K）/protein kinase B （Akt） signaling pathway. MethodsThirty-six female Sprague-Dawley （SD） rats were randomly divided into a blank control group （Con） and an obesity-type PCOS model preparation group. The model was induced by gavage with letrozole （1 mg·kg^-1） combined with a high-fat diet （HFD）. After model establishment， the obesity-type PCOS model preparation group was further divided into the model group （Mod， normal saline）， metformin group （Met， 0.3 g·kg^-1）， low-dose MLC group （MLC-L， 4.3 g·kg^-1）， medium-dose MLC group （MLC-M， 8.6 g·kg^-1）， and high-dose MLC group （MLC-H， 17.2 g·kg^-1）. Active components of MLC and targets of obesity-type PCOS were screened from databases， a protein-protein interaction （PPI） network was constructed， and gene ontology（GO）and Kyoto Encyclopedia of Genes and Genomes （KEGG） pathway enrichment analysis was performed. The gut microbiota structure was analyzed based on 16S rRNA sequencing and correlated with network pharmacology pathways. Body weight and estrous cycle were dynamically monitored. Ovarian morphology was observed by hematoxylin-eosin （HE） staining. Cell apoptosis was detected by terminal deoxynucleotidyl transferase-mediated dUTP nick-end labeling （TUNEL）. Enzyme-linked immunosorbent assay （ELISA） was used to detect levels of follicle-stimulating hormone （FSH）， luteinizing hormone （LH）， anti-Müllerian hormone （AMH）， testosterone （T）， and estradiol （E₂）. Western blot was used to detect the protein expression levels of phosphorylated PI3K/PI3K （p-PI3K/PI3K）， phosphorylated Akt/Akt （p-Akt/Akt）， B-cell lymphoma-2 （Bcl-2）， and Bcl-2-associated X protein （Bax）. ResultsNetwork pharmacology screening identified 124 active components of MLC and 408 overlapping targets between the herbal formula and the disease. Core targets such as Akt1 and Bcl-2 were revealed. As indicated by 16S rRNA sequencing， the abundances of Lachnospiraceae， Lachnoclostridium， and Dorea were increased in the MLC groups （P<0.05）， while the abundance of Veillonella was decreased （P<0.05）. KEGG correlation analysis integrating network pharmacology and gut microbiota data showed significant enrichment of the PI3K/Akt signaling pathway. Animal experiments showed that， compared with the Mod group， body weight decreased to normal levels in the Met， MLC-M， and MLC-H groups. The estrous cycle became regular. The number of corpora lutea increased and cystic follicles decreased. Serum levels of T， FSH， and LH/FSH were reduced （P<0.05， P<0.01）， while the E₂ level was increased （P<0.01）. Ovarian cell apoptosis was reduced （P<0.01）， and the protein expression levels of p-PI3K/PI3K， p-Akt/Akt， and Bcl-2 in ovarian tissue were significantly increased， whereas Bax protein expression was significantly decreased （P<0.05， P<0.01）. ConclusionMLC can regulate gut microbiota structure， effectively improve ovarian pathology in rats with obesity-type PCOS， and inhibit ovarian granulosa cell apoptosis. The mechanism may be associated with upregulation of the PI3K/Akt signaling pathway.

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 investigate the mechanisms by which Mahuang Lianqiao Chixiaodoutang （MLC） improves obesity-type polycystic ovary syndrome （PCOS） through the phosphatidylinositol 3-kinase （PI3K）/protein kinase B （Akt） signaling pathway. MethodsThirty-six female Sprague-Dawley （SD） rats were randomly divided into a blank control group （Con） and an obesity-type PCOS model preparation group. The model was induced by gavage with letrozole （1 mg·kg^-1） combined with a high-fat diet （HFD）. After model establishment， the obesity-type PCOS model preparation group was further divided into the model group （Mod， normal saline）， metformin group （Met， 0.3 g·kg^-1）， low-dose MLC group （MLC-L， 4.3 g·kg^-1）， medium-dose MLC group （MLC-M， 8.6 g·kg^-1）， and high-dose MLC group （MLC-H， 17.2 g·kg^-1）. Active components of MLC and targets of obesity-type PCOS were screened from databases， a protein-protein interaction （PPI） network was constructed， and gene ontology（GO）and Kyoto Encyclopedia of Genes and Genomes （KEGG） pathway enrichment analysis was performed. The gut microbiota structure was analyzed based on 16S rRNA sequencing and correlated with network pharmacology pathways. Body weight and estrous cycle were dynamically monitored. Ovarian morphology was observed by hematoxylin-eosin （HE） staining. Cell apoptosis was detected by terminal deoxynucleotidyl transferase-mediated dUTP nick-end labeling （TUNEL）. Enzyme-linked immunosorbent assay （ELISA） was used to detect levels of follicle-stimulating hormone （FSH）， luteinizing hormone （LH）， anti-Müllerian hormone （AMH）， testosterone （T）， and estradiol （E₂）. Western blot was used to detect the protein expression levels of phosphorylated PI3K/PI3K （p-PI3K/PI3K）， phosphorylated Akt/Akt （p-Akt/Akt）， B-cell lymphoma-2 （Bcl-2）， and Bcl-2-associated X protein （Bax）. ResultsNetwork pharmacology screening identified 124 active components of MLC and 408 overlapping targets between the herbal formula and the disease. Core targets such as Akt1 and Bcl-2 were revealed. As indicated by 16S rRNA sequencing， the abundances of Lachnospiraceae， Lachnoclostridium， and Dorea were increased in the MLC groups （P<0.05）， while the abundance of Veillonella was decreased （P<0.05）. KEGG correlation analysis integrating network pharmacology and gut microbiota data showed significant enrichment of the PI3K/Akt signaling pathway. Animal experiments showed that， compared with the Mod group， body weight decreased to normal levels in the Met， MLC-M， and MLC-H groups. The estrous cycle became regular. The number of corpora lutea increased and cystic follicles decreased. Serum levels of T， FSH， and LH/FSH were reduced （P<0.05， P<0.01）， while the E₂ level was increased （P<0.01）. Ovarian cell apoptosis was reduced （P<0.01）， and the protein expression levels of p-PI3K/PI3K， p-Akt/Akt， and Bcl-2 in ovarian tissue were significantly increased， whereas Bax protein expression was significantly decreased （P<0.05， P<0.01）. ConclusionMLC can regulate gut microbiota structure， effectively improve ovarian pathology in rats with obesity-type PCOS， and inhibit ovarian granulosa cell apoptosis. The mechanism may be associated with upregulation of the PI3K/Akt signaling pathway.

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.

Chronic pancreatitis （CP） is a common disease in clinical practice characterized by progressive inflammatory fibrosis of the pancreas. Gut microbiota， known as the “second genome” of humans， bidirectionally modulates the progression of fibrosis in CP via the gut-pancreas axis. This article systematically elaborates on the characteristics of gut microbiota during the progression of CP and its molecular mechanism in mediating pancreatic fibrosis through bacterial translocation， metabolites， immune regulatory networks， and microbe-pancreatic stellate cell interactions， with a focus on the pivotal role of short-chain fatty acids and inflammatory cytokine networks in pancreatic stellate cell activation and extracellular matrix deposition. In addition， this article explores the potential value of gut microbiota-targeted interventions in the prevention and treatment of CP fibrosis， such as probiotics， prebiotics， and fecal microbiota transplantation， and discusses the translational potential of using multi-omics technologies to identify diagnostic biomarkers and novel therapeutic targets for CP， in order to provide new ideas for the precise diagnosis and treatment of CP.

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 explore the efficacy and mechanisms of Sini San in the treatment of depression and liver injury based on gut microbiota. MethodsThirty-two male Sprague-Dawley （SD） rats were randomly divided into a normal group， model group （M）， Sini San group （MS， 2.5 g·kg^-1）， and fluoxetine group （MF， 2 mg·kg^-1）. Except for the normal group， rats in the other three groups were subjected to chronic unpredictable mild stress （CUMS）. After 8 weeks， the open-field test and sucrose preference test were conducted. Enzyme-linked immunosorbent assay （ELISA） was used to detect serum corticosterone （CORT）， adrenocorticotropic hormone （ACTH）， corticotropin-releasing factor （CRF）， lipopolysaccharide （LPS）， Zonulin， interleukin-6 （IL-6）， tumor necrosis factor-α （TNF-α）， interleukin-1β （IL-1β）， γ-aminobutyric acid （GABA） levels in the hippocampus and prefrontal cortex， and brain-derived neurotrophic factor （BDNF） levels in the hippocampus. Real-time quantitative polymerase chain reaction （Real-time PCR） was used to detect hippocampal BDNF mRNA expression. Serum alanine aminotransferase （ALT） and aspartate aminotransferase （AST） levels were measured using the ultraviolet lactate dehydrogenase method. The ultrastructure of the intestinal epithelium was observed by electron microscopy， and gut microbiota in rat feces were analyzed using 16S rDNA high-throughput sequencing. ResultsCompared with the normal group， the sucrose preference of rats in the model group was significantly reduced （P0.01）， whereas it was significantly increased in the Sini San group compared with the model group （P0.05）. Compared with the normal group， hippocampal GABA protein levels and BDNF mRNA expression in the model group were significantly decreased （P0.05）， and compared with the model group， both were significantly increased in the Sini San group （P0.05， P0.01）. Compared with the normal group， serum LPS and Zonulin levels in the model group were significantly increased （P0.05， P0.01）， and compared with the model group， Zonulin levels in the Sini San group were significantly decreased （P0.05）. No obvious changes were observed in the ultrastructure of the jejunal mucosa among groups. Compared with the normal group， widened and blurred tight junctions， sparse and shortened microvilli， and mitochondrial swelling with cristae disruption in epithelial cells were observed in the ileal and colonic mucosa of the model group， which were markedly improved in the Sini San and fluoxetine groups. The results of 16S rDNA high-throughput sequencing showed that Sini San improved CUMS-induced dysbiosis of Bacteroidetes and Proteobacteria. Correlation analysis indicated that Bacteroidetes and Proteobacteria were significantly correlated with depression-related indicators， liver function， and intestinal mucosal permeability. ConclusionSini San exerts antidepressant and hepatoprotective effects by improving Bacteroidetes and Proteobacteria and inhibiting the increase in intestinal mucosal permeability in CUMS rats.

ObjectiveTo explore the efficacy and mechanisms of Sini San in the treatment of depression and liver injury based on gut microbiota. MethodsThirty-two male Sprague-Dawley （SD） rats were randomly divided into a normal group， model group （M）， Sini San group （MS， 2.5 g·kg^-1）， and fluoxetine group （MF， 2 mg·kg^-1）. Except for the normal group， rats in the other three groups were subjected to chronic unpredictable mild stress （CUMS）. After 8 weeks， the open-field test and sucrose preference test were conducted. Enzyme-linked immunosorbent assay （ELISA） was used to detect serum corticosterone （CORT）， adrenocorticotropic hormone （ACTH）， corticotropin-releasing factor （CRF）， lipopolysaccharide （LPS）， Zonulin， interleukin-6 （IL-6）， tumor necrosis factor-α （TNF-α）， interleukin-1β （IL-1β）， γ-aminobutyric acid （GABA） levels in the hippocampus and prefrontal cortex， and brain-derived neurotrophic factor （BDNF） levels in the hippocampus. Real-time quantitative polymerase chain reaction （Real-time PCR） was used to detect hippocampal BDNF mRNA expression. Serum alanine aminotransferase （ALT） and aspartate aminotransferase （AST） levels were measured using the ultraviolet lactate dehydrogenase method. The ultrastructure of the intestinal epithelium was observed by electron microscopy， and gut microbiota in rat feces were analyzed using 16S rDNA high-throughput sequencing. ResultsCompared with the normal group， the sucrose preference of rats in the model group was significantly reduced （P<0.01）， whereas it was significantly increased in the Sini San group compared with the model group （P<0.05）. Compared with the normal group， hippocampal GABA protein levels and BDNF mRNA expression in the model group were significantly decreased （P<0.05）， and compared with the model group， both were significantly increased in the Sini San group （P<0.05， P<0.01）. Compared with the normal group， serum LPS and Zonulin levels in the model group were significantly increased （P<0.05， P<0.01）， and compared with the model group， Zonulin levels in the Sini San group were significantly decreased （P<0.05）. No obvious changes were observed in the ultrastructure of the jejunal mucosa among groups. Compared with the normal group， widened and blurred tight junctions， sparse and shortened microvilli， and mitochondrial swelling with cristae disruption in epithelial cells were observed in the ileal and colonic mucosa of the model group， which were markedly improved in the Sini San and fluoxetine groups. The results of 16S rDNA high-throughput sequencing showed that Sini San improved CUMS-induced dysbiosis of Bacteroidetes and Proteobacteria. Correlation analysis indicated that Bacteroidetes and Proteobacteria were significantly correlated with depression-related indicators， liver function， and intestinal mucosal permeability. ConclusionSini San exerts antidepressant and hepatoprotective effects by improving Bacteroidetes and Proteobacteria and inhibiting the increase in intestinal mucosal permeability in CUMS rats.