BACKGROUND:The Guilu Erxian Glue consists of Testudinis Plastrum,Cornu Cervi,Lycii Fructus,and Ginseng Radix.In earlier clinical observations,it is discovered that using Guilu Erxian Glue to treat patients with liver-kidney deficiency type knee osteoarthritis effectively alleviated knee pain,increased the range of motion,and improved walking ability.However,the exact mechanism by which oral administration of Guilu Erxian Glue can produce local therapeutic effects on the knee joint is still unclear.OBJECTIVE:To investigate the effects of Guilu Erxian Glue on gut microbiota in rats with knee osteoarthritis and to evaluate its mechanism using 16S rDNA sequencing and machine learning analysis.METHODS:Totally 18 female SD rats were randomly divided into three groups:blank group,model group,and Guilu Erxian Glue group,with 6 rats in each group.A knee osteoarthritis model was prepared using the destabilization of the medial meniscus surgical method.After successful modeling,the Guilu Erxian Glue group was given a decoction of Guilu Erxian Glue by gavage,while the blank and model groups were given an equal amount of distilled water.After 28 days of continuous intervention,high performance liquid chromatography was used to detect the active ingredients of Guilu Erxian Glue.MRI imaging was used to observe the condition of rat knee articular cartilage.Fecal samples were collected;DNA was extracted using a kit,amplified and purified by PCR,and an Illumina sequencing library was constructed.The Illumina MiSeq platform was used for high-throughput sequencing to generate raw sequence data.After obtaining the raw data,QIIME2 software was used to process the data.Linear Discriminant Analysis Effect Size analysis and random forest algorithm were used to screen for differential species in microbial data.KEGG and MetaCyc functional pathway analyses were used to explore the association between key microbial communities and experimental groups.Linear discriminant analysis effect values and random forest algorithm were used to screen for differential species.Association networks were used to analyze the interactions between microbial communities,and machine learning methods were used to analyze the composition and changes of gut microbiota.RESULTS AND CONCLUSION:(1)LC-MS component identification was conducted on the traditional Chinese medicine formula of Guilu Erxian Glue,and a total of 7 effective ingredients were identified.(2)MRI imaging showed that synovitis scope of high-density shadows in rats of the Guilu Erxian Glue group was reduced,and the degeneration of medial femoral condyle cartilage was less than that in the model group.(3)16S rDNA sequencing showed that the model group rats exhibited significant microbial imbalance,with a significant decrease in the abundance of Firmicutes and Bacteroidetes at the phylum level,while the proportion of Proteobacteria increased significantly(P＜0.05).The gut microbiota structure of rats in the Guilu Erxian Glue group was significantly improved,and the proportion of Firmicutes and Bacteroidetes increased,restoring a more diverse microbiota composition,approaching that of the blank group(P＜0.05).(4)KEGG and MetaCyc functional pathway analysis showed that the Guilu Erxian Glue group significantly activated multiple metabolic pathways,including amino acid metabolism,lipid metabolism,and biotin synthesis pathways(P＜0.05).(5)The results indicate that Guilu Erxian Glue contains seven active ingredients,and the changes in gut microbiota of knee osteoarthritis rats were analyzed using 16S rDNA sequencing.Guilu Erxian Glue can significantly improve the imbalance of gut microbiota,restore the abundance of beneficial bacteria,and have a significant impact on the composition of gut microbiota,providing scientific basis for the efficacy and mechanism of Guilu Erxian Glue.

BACKGROUND:The Guilu Erxian Glue consists of Testudinis Plastrum,Cornu Cervi,Lycii Fructus,and Ginseng Radix.In earlier clinical observations,it is discovered that using Guilu Erxian Glue to treat patients with liver-kidney deficiency type knee osteoarthritis effectively alleviated knee pain,increased the range of motion,and improved walking ability.However,the exact mechanism by which oral administration of Guilu Erxian Glue can produce local therapeutic effects on the knee joint is still unclear.OBJECTIVE:To investigate the effects of Guilu Erxian Glue on gut microbiota in rats with knee osteoarthritis and to evaluate its mechanism using 16S rDNA sequencing and machine learning analysis.METHODS:Totally 18 female SD rats were randomly divided into three groups:blank group,model group,and Guilu Erxian Glue group,with 6 rats in each group.A knee osteoarthritis model was prepared using the destabilization of the medial meniscus surgical method.After successful modeling,the Guilu Erxian Glue group was given a decoction of Guilu Erxian Glue by gavage,while the blank and model groups were given an equal amount of distilled water.After 28 days of continuous intervention,high performance liquid chromatography was used to detect the active ingredients of Guilu Erxian Glue.MRI imaging was used to observe the condition of rat knee articular cartilage.Fecal samples were collected;DNA was extracted using a kit,amplified and purified by PCR,and an Illumina sequencing library was constructed.The Illumina MiSeq platform was used for high-throughput sequencing to generate raw sequence data.After obtaining the raw data,QIIME2 software was used to process the data.Linear Discriminant Analysis Effect Size analysis and random forest algorithm were used to screen for differential species in microbial data.KEGG and MetaCyc functional pathway analyses were used to explore the association between key microbial communities and experimental groups.Linear discriminant analysis effect values and random forest algorithm were used to screen for differential species.Association networks were used to analyze the interactions between microbial communities,and machine learning methods were used to analyze the composition and changes of gut microbiota.RESULTS AND CONCLUSION:(1)LC-MS component identification was conducted on the traditional Chinese medicine formula of Guilu Erxian Glue,and a total of 7 effective ingredients were identified.(2)MRI imaging showed that synovitis scope of high-density shadows in rats of the Guilu Erxian Glue group was reduced,and the degeneration of medial femoral condyle cartilage was less than that in the model group.(3)16S rDNA sequencing showed that the model group rats exhibited significant microbial imbalance,with a significant decrease in the abundance of Firmicutes and Bacteroidetes at the phylum level,while the proportion of Proteobacteria increased significantly(P＜0.05).The gut microbiota structure of rats in the Guilu Erxian Glue group was significantly improved,and the proportion of Firmicutes and Bacteroidetes increased,restoring a more diverse microbiota composition,approaching that of the blank group(P＜0.05).(4)KEGG and MetaCyc functional pathway analysis showed that the Guilu Erxian Glue group significantly activated multiple metabolic pathways,including amino acid metabolism,lipid metabolism,and biotin synthesis pathways(P＜0.05).(5)The results indicate that Guilu Erxian Glue contains seven active ingredients,and the changes in gut microbiota of knee osteoarthritis rats were analyzed using 16S rDNA sequencing.Guilu Erxian Glue can significantly improve the imbalance of gut microbiota,restore the abundance of beneficial bacteria,and have a significant impact on the composition of gut microbiota,providing scientific basis for the efficacy and mechanism of Guilu Erxian Glue.

The initiation of adaptive immune responses relies on the precise recognition and interpretation of antigenic information. In this process, the specific binding of T cell receptors (TCRs) to peptide-major histocompatibility complex (pMHC) molecules represents one of the key molecular events in the initiation of adaptive immune responses. Accordingly, the structural features of TCR-pMHC complexes provide a fundamental basis for dissecting antigen recognition mechanisms and support rational vaccine design, therapeutic target discovery in TCR-based immunotherapy, and TCR identification and optimization. However, experimental determination of TCR-pMHC structures remains costly, time-consuming, and limited in coverage, making computational approaches essential for rapidly obtaining reliable structural information. Computational methods for predicting the structures of TCR-pMHC complexes have advanced rapidly in recent years, driven by progress in deep learning-based modeling frameworks and the increasing availability of structural and sequence resources. Despite these developments, most existing tools do not adequately distinguish the key structural and biophysical differences between MHC class I (MHC-I) and MHC class II (MHC-II) complexes during model construction. As a consequence, their predictive performance differs substantially between class I and class II complexes. In general, structural predictions for class I complexes outperform those for class II complexes. This discrepancy may be related to several fundamental differences between the two systems, including the architecture of the peptide-binding groove, the distribution of peptide lengths, and the properties of peptide flanking residues (PFRs). Compared with MHC-I molecules, MHC-II molecules usually bind longer antigenic peptides, which typically range from 13 to 25 amino acids in length. PFRs at both termini of these peptides participate in regulating the overall conformation of TCR-pMHC class II complexes and exert a pronounced effect on the geometric and physicochemical characteristics of the TCR-pMHC binding interface. Furthermore, within the TCR recognition interface, the complementarity-determining regions (CDRs) consist of segments that differ markedly in conformational behavior. They commonly include regions that are relatively rigid and structurally stable, together with highly flexible segments exhibiting substantial conformational plasticity. These rigidity-flexibility features constitute an essential structural basis enabling TCRs to recognize diverse peptide-MHC ligands and to accommodate conformational heterogeneity at the interface. However, many current modeling tools, in an effort to enforce global conformational stability or reduce structural noise, tend to over-constrain intrinsically flexible regions. Such oversimplification may lead to inappropriate rigidification of flexible CDR loops, resulting in local structural distortions, compromised interface geometry, or even complete modeling failure for specific complexes. Against this background, the review approaches the field from the perspective of computational differences between MHC-I and MHC-II complexes. We first systematically organize and summarize available resources related to TCRs and pMHCs, including structural datasets, sequence databases, prediction tools, and benchmarking studies. We then focus on five representative tools capable of predicting both class I and class II complexes—AlphaFold2, AlphaFold3, TCRmodel2, tFold-TCR, and TCR-pHLA_ModellerS. After excluding structures present in the training sets of these tools, we constructed a benchmark dataset comprising 25 class I and 10 class II TCR-pMHC complexes in the bound state and conducted a systematic evaluation using this dataset. We first employ widely used general evaluation metrics, including All-Atom Root Mean Square Deviation (All-Atom RMSD), Backbone RMSD, Template Modeling score (TM-score), and DockQ, to assess the global conformational accuracy and interface modeling quality of class I and class II complexes. For class II complexes, we propose for the first time a peptide flanking residue deviation index, including the PFRs-Deviation Index (PFRs-DI), N-PFR-Deviation Index (N-PFR-DI), and C-PFR-Deviation Index (C-PFR-DI), to quantitatively characterize conformational deviations in PFRs. In addition, we propose the CDR conformational consistency index (CCC) designed to qualitatively evaluate the ability of prediction tools to capture TCR CDR conformational flexibility. These metrics collectively assess a tool’s ability to model both overall conformation and critical functional regions, thereby addressing the limitations of existing evaluation criteria that overemphasize global structure while inadequately capturing modeling quality in key functional areas. This establishes a unified analytical framework for MHC-I and MHC-II complexes to guide data resource selection, modeling strategy formulation, and evaluation system development. The framework further advances computational modeling and provides crucial support for multi-scale analysis of TCR-pMHC recognition mechanisms and their biological functions.

The initiation of adaptive immune responses relies on the precise recognition and interpretation of antigenic information. In this process, the specific binding of T cell receptors (TCRs) to peptide-major histocompatibility complex (pMHC) molecules represents one of the key molecular events in the initiation of adaptive immune responses. Accordingly, the structural features of TCR-pMHC complexes provide a fundamental basis for dissecting antigen recognition mechanisms and support rational vaccine design, therapeutic target discovery in TCR-based immunotherapy, and TCR identification and optimization. However, experimental determination of TCR-pMHC structures remains costly, time-consuming, and limited in coverage, making computational approaches essential for rapidly obtaining reliable structural information. Computational methods for predicting the structures of TCR-pMHC complexes have advanced rapidly in recent years, driven by progress in deep learning-based modeling frameworks and the increasing availability of structural and sequence resources. Despite these developments, most existing tools do not adequately distinguish the key structural and biophysical differences between MHC class I (MHC-I) and MHC class II (MHC-II) complexes during model construction. As a consequence, their predictive performance differs substantially between class I and class II complexes. In general, structural predictions for class I complexes outperform those for class II complexes. This discrepancy may be related to several fundamental differences between the two systems, including the architecture of the peptide-binding groove, the distribution of peptide lengths, and the properties of peptide flanking residues (PFRs). Compared with MHC-I molecules, MHC-II molecules usually bind longer antigenic peptides, which typically range from 13 to 25 amino acids in length. PFRs at both termini of these peptides participate in regulating the overall conformation of TCR-pMHC class II complexes and exert a pronounced effect on the geometric and physicochemical characteristics of the TCR-pMHC binding interface. Furthermore, within the TCR recognition interface, the complementarity-determining regions (CDRs) consist of segments that differ markedly in conformational behavior. They commonly include regions that are relatively rigid and structurally stable, together with highly flexible segments exhibiting substantial conformational plasticity. These rigidity-flexibility features constitute an essential structural basis enabling TCRs to recognize diverse peptide-MHC ligands and to accommodate conformational heterogeneity at the interface. However, many current modeling tools, in an effort to enforce global conformational stability or reduce structural noise, tend to over-constrain intrinsically flexible regions. Such oversimplification may lead to inappropriate rigidification of flexible CDR loops, resulting in local structural distortions, compromised interface geometry, or even complete modeling failure for specific complexes. Against this background, the review approaches the field from the perspective of computational differences between MHC-I and MHC-II complexes. We first systematically organize and summarize available resources related to TCRs and pMHCs, including structural datasets, sequence databases, prediction tools, and benchmarking studies. We then focus on five representative tools capable of predicting both class I and class II complexes—AlphaFold2, AlphaFold3, TCRmodel2, tFold-TCR, and TCR-pHLA_ModellerS. After excluding structures present in the training sets of these tools, we constructed a benchmark dataset comprising 25 class I and 10 class II TCR-pMHC complexes in the bound state and conducted a systematic evaluation using this dataset. We first employ widely used general evaluation metrics, including All-Atom Root Mean Square Deviation (All-Atom RMSD), Backbone RMSD, Template Modeling score (TM-score), and DockQ, to assess the global conformational accuracy and interface modeling quality of class I and class II complexes. For class II complexes, we propose for the first time a peptide flanking residue deviation index, including the PFRs-Deviation Index (PFRs-DI), N-PFR-Deviation Index (N-PFR-DI), and C-PFR-Deviation Index (C-PFR-DI), to quantitatively characterize conformational deviations in PFRs. In addition, we propose the CDR conformational consistency index (CCC) designed to qualitatively evaluate the ability of prediction tools to capture TCR CDR conformational flexibility. These metrics collectively assess a tool’s ability to model both overall conformation and critical functional regions, thereby addressing the limitations of existing evaluation criteria that overemphasize global structure while inadequately capturing modeling quality in key functional areas. This establishes a unified analytical framework for MHC-I and MHC-II complexes to guide data resource selection, modeling strategy formulation, and evaluation system development. The framework further advances computational modeling and provides crucial support for multi-scale analysis of TCR-pMHC recognition mechanisms and their biological functions.

ObjectiveTo investigate the mechanisms by which Bushen Tongluo Jiangzhuo prescription improves renal fibrosis in rats with chronic kidney disease （CKD） through the phosphatidylinositol 3-kinase （PI3K）/protein kinase B （Akt）/mammalian target of rapamycin （mTOR） signaling pathway. MethodsSeventy specific pathogen-free （SPF） Sprague-Dawley （SD） rats were randomly divided into a control group （n=15） and a modeling group （n=55）. Rats in the modeling group were administered a 2.5% adenine suspension at a dose of 200 mg·kg^-1·d^-1 by gavage for 4 weeks to establish a CKD model. Successfully modeled rats were randomly divided into a model group， an irbesartan group （20.25 mg·kg^-1·d^-1）， and Bushen Tongluo Jiangzhuo prescription low-， medium-， and high-dose groups （5.82， 11.64， and 23.28 g·kg^-1·d^-1， respectively）， with 10 rats in each group. Each group was administered an equal volume of physiological saline， the corresponding concentration of irbesartan， or Bushen Tongluo Jiangzhuo prescription by gavage for 12 weeks. Body weight and renal function indices were dynamically monitored. Serum creatinine （SCr）， blood urea nitrogen （BUN）， urine albumin-to-creatinine ratio （ACR）， 24-hour urinary total protein （24 hUTP）， aspartate aminotransferase （AST）， alanine aminotransferase （ALT）， interleukin-1β （IL-1β）， interleukin-6 （IL-6）， and tumor necrosis factor-α （TNF-α） levels were measured using an automatic biochemical analyzer. Renal histopathological changes were observed by hematoxylin-eosin （HE） and Masson staining. Immunohistochemistry （IHC） was used to detect the expression of PI3K， Akt， phosphorylated Akt （p-Akt）， and mTOR in renal tissues. Western blot was performed to assess the protein expression of PI3K， p-Akt， Akt， phosphorylated mTOR （p-mTOR）， and mTOR in renal tissues. Real-time quantitative polymerase chain reaction （Real-time PCR） was used to determine the mRNA expression levels of PI3K， Akt， and mTOR in renal tissues. ResultsCompared with the model group， rats in the irbesartan group and the low-， medium-， and high-dose Bushen Tongluo Jiangzhuo prescription groups showed significantly decreased levels of SCr， BUN， ACR， 24 hUTP， IL-1β， IL-6， and TNF-α （P<0.01）. AST levels were significantly increased （P<0.01）， while no significant difference was observed in ALT levels. Histopathological examination revealed that， compared with the model group， renal tubular epithelial cell edema and necrosis and Bowman's capsule dilation were alleviated， inflammatory cell infiltration was reduced， and interstitial and glomerular fibrosis was markedly improved in all treatment groups， with the most pronounced effect observed in the high-dose Bushen Tongluo Jiangzhuo prescription group. Real-time PCR results showed that mRNA expression levels of PI3K， Akt， and mTOR were significantly downregulated in the high-dose group （P<0.01）. IHC results demonstrated that PI3K and p-Akt expression levels in renal tissues were significantly decreased in the high-dose group （P<0.01）. Western blot analysis further confirmed that the expression levels of PI3K， p-Akt/Akt， and p-mTOR/mTOR were significantly reduced in the high-dose group （P<0.01）. ConclusionBushen Tongluo Jiangzhuo prescription improves renal function indices in CKD rats， reduces collagen deposition in renal tissues， and decreases serum inflammatory factor levels. Its protective effect on renal function may be achieved by activating autophagy through downregulation of the PI3K/Akt/mTOR signaling pathway， thereby alleviating renal fibrosis.

Objective To explore the efficacy and safety of oral solution of magnesium sodium potassium sulfate in bowel preparation before colonoscopy. Methods Patients who planned to undergo colonoscopy at the digestive department of the Ninth People’s Hospital, affiliated to School of Medicine of Shanghai Jiao Tong University from January 2023 to August 2023 were selected and eligible subjects were divided into two groups: Group A took polyethylene glycol （PEG） and Group B took oral solution of magnesium sodium potassium sulfate （OSS）. The quality, drug tolerance, and safety of intestinal preparation were evaluated. The quality of bowel preparation was evaluated by the boston bowel preparation scale （BBPS）. Results The right colon BBPS score of Group B was (2.39±0.82) points, which was significantly higher than of Group A (2.11±0.43) points （P<0.05）. The overall score of Group B was higher than that of Group A （P<0.05）. OSS was easier to take than PEG, with a good taste and overall sensation. Patients were willing to use OSS to clean their bowels even when they were willing to undergo another examination （P<0.05）. There was a significant difference in nausea and vomiting symptoms between the two groups （P<0.05）, and there were no significant changes in renal function and electrolytes before and after medication in the two groups of patients. Conclusion OSS had a higher quality of bowel cleaning and was easier for patients to accept.

ObjectiveTo investigate the therapeutic efficacy of Qizhi Tongluo granules on proteinuria in membranous nephropathy （MN） and its potential protective effects and underlying mechanism against endoplasmic reticulum stress. MethodsAfter 70 Sprague-Dawley （SD） rats were adaptively fed for one week， the MN rat model was established by injecting cationic bovine serum albumin （C-BSA） into the tail vein. Rats were divided into the normal group， model group， low-dose Qizhi Tongluo granules group （2.43 g·kg^-1）， medium-dose group （4.86 g·kg^-1）， high-dose group （9.72 g·kg^-1）， and benazepril group （0.01 g·kg^-1）， with 10 rats in each group. Treatment was administered for four weeks. The 24-hour urinary total protein （UTP） content， as well as the levels of reactive oxygen species （ROS）， malondialdehyde （MDA）， and glutathione peroxidase （GPX） in renal tissues， were measured. Renal pathological changes were assessed using immunoglobulin G （IgG） staining， periodic acid-silver methenamine （PASM） staining， and transmission electron microscopy （TEM）. The localization and expression levels of glucose-regulated protein 78 （GRP78）， phosphorylated inositol-requiring enzyme 1α （p-IRE1α）， phosphorylated protein kinase R-like endoplasmic reticulum kinase （p-PERK）， activating transcription factor 4 （ATF4）， nuclear factor erythroid 2-related factor 2 （Nrf2）， and 2'-5' oligoadenylate synthetase-like protein 1 （OASL1） in rat kidneys were detected by immunohistochemistry （IHC）. The mRNA and protein expression levels of Nrf2， thioredoxin 1 （Trx1）， thioredoxin-interacting protein （TXNIP）， and OASL1 in rat kidneys were measured using real-time quantitative polymerase chain reaction （Real-time PCR） and Western blot analysis. ResultsCompared with the normal group， UTP levels were significantly increased in the model rats （P<0.05）， with obvious renal pathological damage. GPX content levels were significantly decreased in renal tissue （P<0.05）， while ROS and MDA content levels were significantly increased （P<0.05）. The expression of GRP78， p-IRE1α， p-PERK， and ATF4 proteins was significantly increased in the kidneys （P<0.05）， while the mRNA and protein expression levels of Trx1 and Nrf2 were significantly decreased （P<0.05）. The mRNA and protein expression levels of TXNIP and OASL1 were significantly increased （P<0.05）. Compared with the model group， the UTP levels of rats in the Qizhi Tongluo granules groups and the benazepril group decreased to varying degrees （P<0.05）， and renal pathological damage was significantly alleviated. The GPX content in renal tissue was significantly increased （P<0.05）， while the ROS and MDA levels were significantly decreased （P<0.05）. The expression of GRP78， p-IRE1α， p-PERK， and ATF4 proteins in the kidney was significantly decreased （P<0.05）. The mRNA and protein expression levels of Trx1 and Nrf2 were significantly increased （P<0.05）， while the mRNA and protein expression levels of TXNIP and OASL1 were significantly decreased （P<0.05）. ConclusionQizhi Tongluo granules alleviates proteinuria in MN rats by modulating the Nrf2/OASL1 signaling pathway in renal tissues to reduce endoplasmic reticulum stress， which represents its underlying mechanism.

ObjectiveThis paper aims to observe the syndrome improvement and negative antigen conversion rate of Qingxuan Daozhi formula in the treatment of influenza in children （heat accumulation in the lung and stomach syndrome）. MethodsThrough a multi-center randomized controlled methodology design，confirmed influenza cases were collected from October 2022 to April 2023 in the pediatrics department of eight hospitals，such as Dongfang Hospital of Beijing University of Chinese Medicine. A total of 180 children with influenza and heat accumulation in the lung and stomach syndrome conforming to the standard were recruited through the clinic. The sick children meeting the inclusion criteria were randomly divided into groups by a block-randomized method. The children in the experimental group were treated with Qingxuan Daozhi formula for five days，and those in the control group were treated with Oseltamivir Phosphate Granules for five days. The primary efficacy indicator was the negative conversion rate of influenza antigen detection. Secondary efficacy indicators were the Canadian acute respiratory illness and flu scale （CARIFS） and the incidence of complications，severe cases， and critical cases. Follow-up observation was conducted on the day of enrollment，48 hours after medication，72 hours after medication， and （6+1） d after medication. ResultsOne hundred and eighty participants were randomly assigned to the experimental group （90 cases） or the control group （90 cases）. All participants were followed up during the study. Comparison of influenza antigen detection results in the primary efficacy indicators showed that the average time of negative influenza antigen conversion in the experimental group was （5.29±1.25） d，and that in the control group was （5.40±1.68） d，without a statistically significant difference. After five days of intervention，52 cases in the experimental group and 51 cases in the control group converted to negative，without a statistically significant difference. CARIFS score results in the secondary efficacy indicators showed that during 72 hours after intervention，there were statistically significant differences between the experimental group and the control group in three dimensions， including headache，muscle soreness， and the need for extra care （P<0.05）. On the （6+1） days after the intervention，the differences in both the experimental group and the control group were statistically significant in 10 dimensions， including sore throat，bad sleep，uncomfortable feeling，poor spirit and fatigue，crying more than usual，the need for extra care，symptom，function，influence on parents，and total score （P<0.05）. The comparison results within the group in the dimensional scores of symptom， function， and influence on parents，as well as the CARIFS total score showed that with the delay of follow-up time，scores of both groups decreased significantly，with a statistically significant difference （P<0.01）. Inter-group comparison results showed that the mean score of the experimental group was higher than that of the control group at the time of enrollment. With the progress of intervention，the score of the experimental group was significantly decreased compared with that of the control group. At the end of follow-up，the mean score of the experimental group was lower than that of the control group，with no statistically significant difference. In terms of the incidence of complications，severe cases， and critical cases， there were no complications，severe cases， and critical cases in the two groups，without a statistically significant difference. ConclusionThe symptom improvement effect and negative antigen conversion rate of Qingxuan Daozhi formula in the treatment of influenza in children （heat accumulation in the lung and stomach syndrome） are not inferior to Oseltamivir Phosphate granules， and children's acceptance is better. It can be more widely used in clinical treatment of influenza in children （heat accumulation in the lung and stomach syndrome）.

OBJECTIVE To investigate the prevalence and influencing factors of potentially inappropriate medication （PIM） among the elderly in nursing homes in Urumqi based on three PIM screening tools， and to compare the applicability of different tools. METHODS A cross-sectional study design was adopted. Elderly individuals from six nursing homes in Urumqi were selected as the research subjects from May 2021 to September 2023. Demographic characteristics， disease burden and medication records of the elderly were collected. PIM screening was performed using the Chinese PIM criteria （2024 edition）， the American Geriatrics Society （AGS） Beers criteria （2023 edition）， and the Screening Tool of Older Person’S Prescriptions（STOPP）/Screening Tool to Alert to Right Treatment（START） （2023 edition）. Fleiss’s Kappa test was used to assess the consistency among the three screening tools， and multivariate Logistic regression was used to analyze the influencing factors of PIM. RESULTS The prevalence of PIM screened by the Chinese PIM criteria was 47.4% （323/682）， by the AGS Beers criteria was 43.4% （296/682）， and by the STOPP criteria was 50.9% （347/682）. The consistency among the three screening tools was low （Fleiss’s Kappa＝0.12， P ＜0.001）. Multivariate Logistic regression analysis showed that all three screening tools indicated that polypharmacy， aspirin use and psychotropic drug use were independent risk factors for PIM among elderly in nursing houses （all OR＞1， P ＜0.05）. CONCLUSIONS The prevalence of PIM among the elderly in nursing homes in Urumqi is relatively high. Polypharmacy， aspirin use and psychotropic drug use are common independent risk factors for PIM. There are differences in screening results among the three tools with low consistency. The Chinese PIM criteria can serve as a first-line tool for PIM screening in nursing homes.

Effective symptom management can alleviate the physical and psychological distress experienced by patients with cancer, improve quality of life, and contribute to treatment adherence and improve clinical outcomes. However, most existing guidelines are developed for healthcare professionals, and patients and the public have limited access to standardized and comprehensible guidance on symptom management. To address this gap and to facilitate effective communication and shared decision-making, this study proposes the development of a patient version of the cancer symptom management guideline. The development process will adhere to the methodological framework recommended by the Guidelines International Network and the World Health Organization. The GRADE approach will be employed to assess the certainty of evidence and to formulate recommendations. In addition, the process will be informed by the Appraisal of Guidelines for Research and Evaluation Ⅱ (AGREE Ⅱ) instrument and the Reporting Items for Practice Guidelines in Healthcare-Public or Patient Versions of Guidelines (RIGHT-PVG). This protocol outlines the establishment of the guideline working group, the identification and prioritization of key questions, evidence retrieval and appraisal, and the formulation of recommendations, with the aim of ensuring methodological rigor and transparency in the development of the patient guideline and providing methodological reference for similar guideline initiatives.