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.

Objective To evaluate the performance of lightweight Chinese large language models (LLMs) in answering specialized lung cancer questions, and to explore the impact of retrieval-augmented generation (RAG) on model performance. Methods Eleven lightweight Chinese LLMs with parameter sizes ranging from 7B to 32B were included. A lung cancer-specific evaluation dataset consisting of 200 questions [100 A1-type (basic knowledge) and 100 A2-type (clinical case) questions], constructed based on clinical guidelines and thoracic surgery textbooks, was used for assessment. Model performance was evaluated under two conditions (with and without RAG). Accuracy was used to assess model performance, and response latency was recorded to reflect inference efficiency. An accuracy–latency scatter plot was constructed for descriptive analysis of overall model performance. Results All models successfully completed the evaluation. With the introduction of RAG, the overall average accuracy improved from 61.68% to 76.36%. Smaller models demonstrated the most significant improvement (e.g., the accuracy of DeepSeek-7B increased from 32.50% to 60.00%, P<0.001). The average response latency increased from 12.58 s to 13.80 s. The Qwen3 series showed the best overall performance, and Qwen3-32B achieved the highest accuracy under both conditions (76.50% and 84.00%, respectively). After RAG integration, performance differences among model families were markedly reduced. Based on the accuracy-latency trade-off, Qwen3-32B achieved the best balance between accuracy and response latency under the baseline condition, whereas Qwen3-14B demonstrated superior overall performance in terms of accuracy, latency, and computational cost after RAG integration. Conclusion The integration of RAG technology improves the ability of lightweight Chinese LLMs to answer specialized lung cancer questions. Under the dual practical constraints of limited computational resources and medical data security requirements, the "lightweight model+RAG" technical framework may represent a promising deployment solution.

BACKGROUND: The STAR (Scientific, Transparent, and Applicable Rankings) working group conducts regular evaluations of Chinese guidelines and consensus statements. This study gathered insights from STAR working group members using qualitative interviews. METHODS: From March to August 2023, members of the STAR specialist committees were interviewed using semi-structured interview outline. The interviewees were selected through purpose-based sampling. Subject analysis was employed to summarize the findings. RESULTS: We conducted interviews with 37 members from 36 committees and summarized the contents into four main themes and 16 specific topics. The value of STAR in enhancing the development and selection of high-quality guidelines in China was commonly mentioned. Challenges identified included the lack of resources and suboptimal organizational structures, collaboration, and evaluation efficiency. Suggestions for the STAR tool included developing extensions for different guideline types, adjusting certain items, and better covering guideline applicability. The promotion of STAR and the consideration of an international committee for global outreach were also highlighted. CONCLUSION STAR has exerted a substantial influence on the evaluation of Chinese guidelines, and the insights gained from interviews offer valuable directions for its further enhancement.
Humans ; China ; Qualitative Research ; Practice Guidelines as Topic ; Interviews as Topic

To elucidate the mechanism by which steaming affects the quality of Curcuma kwangsiensis root tubers, methods such as LSCM, RVA, dual-wavelength spectrophotometry, LF-NMR, and LC-MS were employed to qualitatively and quantitatively detect changes in starch gelatinization characteristics, water distribution, and material composition of C. kwangsiensis root tubers under different steaming durations. Based on multivariate statistical analysis, the correlation between differences in gelatinization parameters, water distribution, and terpenoid material composition was investigated. The results indicate that steaming affects both starch gelatinization and water distribution in C. kwangsiensis. During the steaming process, transformations occur between amylose and amylopectin, as well as between semi-bound water and free water. After 60 min of steaming, starch gelatinization and water distribution reached an equilibrium state. The content of amylopectin, the amylose-to-amylopectin ratio, and parameters such as gelatinization temperature, viscosity, breakdown value, and setback value were significantly correlated(P≤0.05). Additionally, the amylose-to-amylopectin ratio was significantly correlated with total free water and total water content(P≤0.05). Steaming induced differences in the material composition of C. kwangsiensis root tubers. Clustering of primary metabolites in the OPLS-DA model was distinct, while secondary metabolites were classified into 9 clusters using the K-means clustering algorithm. Differential terpenoid metabolites such as(-)-α-curcumene were significantly correlated with zerumbone, retinal, and all-trans-retinoic acid(P<0.05). Curcumenol was significantly correlated with isoalantolactone and ursolic acid(P<0.05), while all-trans-retinoic acid was significantly correlated with both zerumbone and retinal(P<0.05). Alpha-tocotrienol exhibited a significant correlation with retinal and all-trans-retinoic acid(P<0.05). Amylose was extremely significantly correlated with(-)-α-curcumene, curcumenol, zerumbone, retinal, all-trans-retinoic acid, and α-tocotrienol(P<0.05). Amylopectin was significantly correlated with zerumbone(P<0.05) and extremely significantly correlated with(-)-α-curcumene, curcumenol, zerumbone, retinal, all-trans-retinoic acid, and 9-cis-retinoic acid(P<0.01). The results provide scientific evidence for elucidating the mechanism of quality formation of steamed C. kwangsiensis root tubers as a medicinal material.
Curcuma/chemistry* ; Starch/chemistry* ; Multivariate Analysis ; Water/chemistry* ; Terpenes/analysis* ; Plant Roots/chemistry* ; Plant Tubers/chemistry* ; Drugs, Chinese Herbal/chemistry*

Immune checkpoint inhibitor-associated enterocolitis is an immune-related adverse reaction during tumor treatment with immune checkpoint inhibitors.In this article,we present the clinical data and ultrasound manifestations of a patient with immune checkpoint inhibitor-associated enterocolitis,aiming to share diagnostic and therapeutic insights.
Humans ; Immune Checkpoint Inhibitors/adverse effects* ; Enterocolitis/chemically induced* ; Ultrasonography ; Male

In recent years,significant breakthroughs have been achieved in the immunotherapy for Alzheimer's disease.In line with global advancements,two anti-amyloid-β monoclonal antibodies have been approved and successfully launched in China for clinical use.Lecanemab and Donanemab were officially used in June 2024 and April 2025 in China,respectively.In order to standardize the rational and safe application of anti-amyloid-β monoclonal antibodies for Alzheimer's disease in China,this article integrates recom-mendations from the clinical trials and real-world experience from the author's team and domestic peers to further update the recom-mendations for the clinical use of anti-amyloid-β monoclonal antibody based on the 2024 version.It includes indications for therapy,pre-treatment evaluation and preparation,administration protocols and safety measures during treatment,and post-treatment monitor-ing strategies.

Aging is characterized by a gradual deterioration of the physiological integrity of cells,tissues,and or-gans,resulting in a decrease in the body's physiological functions and an acceleration of the onset of age-related diseases,ultimately leading to death.The aging of the liver,which is a critical metabolic organ,is closely linked to various chronic liver diseases,such as hepatitis,liver fibrosis,and cirrhosis,and it ex-acerbates their prognosis and is a primary risk factor for their development at all stages.Therefore,a comprehensive understanding of the causes,mechanisms,and potential therapeutic targets associated with liver aging holds significant clinical importance for delaying or potentially reversing liver aging and for treating chronic liver diseases.Stem cells,which are potential anti-aging agents,present a promising and effective alternative for managing liver aging.In this review,we systematically assess the driving factors,characteristics,and underlying mechanisms of liver aging.We then discuss the current status of the use of stem cells to mitigate liver senescence and address related liver diseases.The review reveals that a stem cell-based approach represents a promising therapeutic strategy for combating liver aging and associated diseases.

Objective To investigate the relationship between the protective mechanism of dexmedetomidine(Dex)against myocardial ischemia-reperfusion(I/R)injury and cuproptosis.Methods The Langendorff models were con-structed using SD rats(I/R group),which were divided into 4 groups according to different interventions during reperfusion as:sham group,I/R group,Dex group and Dex+ES-Cu group.The left ventricular peak pressure(LVSP)of the rats in the above four groups were continuously monitored in the immediate pre-ischemic period(T0),30 min of reperfusion(T1),60 min reperfusion(T2),90 min reperfusion(T3),2 h of reperfusion(T4).Left ventricular end-diastolic pressure(LVEDP),heart rate(HR),maximum rate of rise of left ventricular pressure(+dp/dtmax)and maximum rate of drop.Subsequently,the extent of myocardial infarction was shown by 1%triphenyltetrazoliumchloride(TTC)staining,and the degree of myocardial fibrosis was assessed by Sirius red staining;Myocardial enzyme profiles,oxidative stress and inflammation indexes were detected by ELISA;Copper ions were detected by copper ion detection kit in myocardial tissues;ATF3,SPI1 and FDX1 protein level expres-sion was detected by Western blot.Results Compared with the sham-operated group,the extent of myocardial in-farction and fibrosis increased in the I/R group(P＜0.05),the level of serum MDA,IL-6,IL-1β,and TNF-α was elevated(P＜0.05),and the activity of SOD and GSH-Px decreased(P＜0.05).The Dex group significantly alleviated the above changes in the I/R group,and compared with the Dex group,in the Dex+ES-Cu group myocardi-al tissue copper ion content at the end of perfusion was increased(P＜0.05).Both ATF3 and SPI1 protein were in-creased and FDX1 protein was decreased(P＜0.05).Conclusions Dex can regulate copper metabolism and improve myocardial ischemia-reperfusion injury(MI/RI)resulted from oxidative stress and inflammation in rat model.

Objective To investigate the protective effects of paeonol(PAE)on autophagy in human neuroblastoma cells(SH-SY5Y)induced by overexpression of α-synuclein(α-Syn),and to explore its related mechanism.Methods SH-SY5Y cells served as control group,while those induced with A53T-α-Syn mutation were used as model group.Additional groups included PAE(150 μg/ml)group,3-MA(1 mmol/L)group,and PAE(150 μg/ml)+3-MA(1 mmol/L)group.Cell viability was assessed using CCK-8 method,cell morphology was observed under an optical microscope,and protein expressions of α-Syn,LC3-Ⅱ,p62,Beclin-1,phosphorylated c-Jun N-terminal kinase(p-JNK),and p-Bcl-2 were determined by Western blotting.Results Compared with control group,model control exhibited decreased cell survival(P＜0.01),increased α-Syn expression(P＜0.001),reduced expression of autophagy-related proteins LC3-Ⅱ and Beclin-1(P＜0.01,P＜0.05),elevated autophagy substrate protein p62(P＜0.05),and decreased expression of autophagy pathway-related proteins p-JNK and Bcl-2(P＜0.05,P＜0.01).Compared with model group,PAE group showed increased cell survival(P＜0.01),decreased α-Syn and p62 protein expression(P＜0.01,P＜0.05),and increased expression of LC3-Ⅱ,Beclin-1,p-JNK and Bcl-2(P＜0.05).Compared with PAE group,3-MA+PAE group demonstrated increased α-Syn expression(P＜0.05).Conclusions PAE could attenuate the injury of SH-SY5Y cells induced by A53T-α-Syn and eliminate over-expressed α-Syn by activating autophagy pathway,which may be associated with the upregulation of JNK/Bcl-2 mediated autophagy pathway.