ObjectiveThe essence of syndrome manifestation recognition in traditional Chinese medicine (TCM) is to infer the body’s latent pathogenesis state from clinical observational information, rather than to perform simple label matching. However, previous studies have largely modeled this task as syndrome pattern classification within a fixed label space, which does not adequately reflect the cognition process of TCM syndrome differentiation centered on pathogenesis reasoning, and is also insufficient to capture the openness, semantic variability, and cross-disease reusability of syndrome manifestation expression. This study aimed to investigate whether introducing pathogenesis reasoning chain-of-thought (PR-CoT) supervision into large language models (LLMs) could improve the quality and cognitive consistency of syndrome manifestation recognition and support cross-disease transfer. MethodsSyndrome manifestation recognition was formulated as a conditional generation task under the framework of clinical observational information (X)→pathogenesis structure (Z)→syndrome pattern output (Y), where Z serves as an explicit intermediate structural variable linking the clinical evidence and syndrome judgment. Within this framework, a PR-CoT-supervised dataset for syndrome manifestation recognition was constructed based on medical case records of spleen-stomach disorders. After preprocessing, information extraction, manual proofreading, and data cleaning, the dataset comprised 4 800 training cases, 400 development cases, and 400 test cases. Each sample was annotated with a structured PR-CoT consisting of three progressive levels: clinical information summarization, comprehensive pathogenesis analysis, and syndrome pattern output. Supervised fine-tuning was conducted on open-source LLMs, with an end-to-end model serving as the baseline. Qwen3-32B was used as the primary experimental model, and Qwen3-14B as the scale comparison model. A progressive multidimensional evaluation framework was further established, comprising a structural parsing level, a semantic similarity level, and an expert blind review level. At the structural parsing level, syndrome pattern expressions were decomposed into structural elements and evaluated using Precision, Recall, F1 score, and Jaccard similarity. At the semantic similarity level, independent LLMs scored the theoretical proximity between predicted and reference syndrome patterns. At the expert blind review level, three TCM experts independently evaluated model outputs on two dimensions: syndrome differentiation consistency and terminology standardization of syndrome patterns. In addition, zero-shot cross-disease transfer evaluation was conducted on gynecological and heart-system disorder test sets. ResultsAt the structural parsing level, PR-CoT supervision did not lead to a stable improvement in the element-wise overlap of syndrome pattern structural components. Compared with the corresponding baselines, neither Qwen3-32B nor Qwen3-14B showed consistent advantages in structural matching metrics after the introduction of PR-CoT supervision. In contrast, at the semantic similarity level, PR-CoT supervision produced stable positive gains across different model scales and evaluation systems. The average semantic score of Qwen3-32B increased from 6.425 8 in the baseline model to 6.585 0 after PR-CoT supervision, and that of Qwen3-14B increased from 5.870 0 to 5.964 2. At the expert blind review level, the overall score of Qwen3-32B (PR-CoT) was 7.026 0±0.107 7, higher than 6.416 3±0.288 9 for its baseline. In zero-shot cross-disease testing, the PR-CoT model still showed advantages in semantic evaluation and expert evaluation on both gynecological and heart-system disorder test sets, indicating a certain degree of transferability. ConclusionThe benefits of PR-CoT supervision are mainly reflected in TCM semantic consistency and clinical plausibility, rather than in improved hard matching of structural elements. These findings support understanding syndrome manifestation recognition as a process of generating and expressing latent pathogenesis structures, rather than as a classification task within a traditional fixed label space. By introducing pathogenesis reasoning as an explicit intermediate structure into the modeling process and combining it with a progressive multidimensional evaluation framework, this study provides a methodological pathway for intelligent TCM syndrome differentiation that integrates theoretical alignment, interpretability, and multi-level evaluation.

ObjectiveThe essence of syndrome manifestation recognition in traditional Chinese medicine (TCM) is to infer the body’s latent pathogenesis state from clinical observational information, rather than to perform simple label matching. However, previous studies have largely modeled this task as syndrome pattern classification within a fixed label space, which does not adequately reflect the cognition process of TCM syndrome differentiation centered on pathogenesis reasoning, and is also insufficient to capture the openness, semantic variability, and cross-disease reusability of syndrome manifestation expression. This study aimed to investigate whether introducing pathogenesis reasoning chain-of-thought (PR-CoT) supervision into large language models (LLMs) could improve the quality and cognitive consistency of syndrome manifestation recognition and support cross-disease transfer. MethodsSyndrome manifestation recognition was formulated as a conditional generation task under the framework of clinical observational information (X)→pathogenesis structure (Z)→syndrome pattern output (Y), where Z serves as an explicit intermediate structural variable linking the clinical evidence and syndrome judgment. Within this framework, a PR-CoT-supervised dataset for syndrome manifestation recognition was constructed based on medical case records of spleen-stomach disorders. After preprocessing, information extraction, manual proofreading, and data cleaning, the dataset comprised 4 800 training cases, 400 development cases, and 400 test cases. Each sample was annotated with a structured PR-CoT consisting of three progressive levels: clinical information summarization, comprehensive pathogenesis analysis, and syndrome pattern output. Supervised fine-tuning was conducted on open-source LLMs, with an end-to-end model serving as the baseline. Qwen3-32B was used as the primary experimental model, and Qwen3-14B as the scale comparison model. A progressive multidimensional evaluation framework was further established, comprising a structural parsing level, a semantic similarity level, and an expert blind review level. At the structural parsing level, syndrome pattern expressions were decomposed into structural elements and evaluated using Precision, Recall, F1 score, and Jaccard similarity. At the semantic similarity level, independent LLMs scored the theoretical proximity between predicted and reference syndrome patterns. At the expert blind review level, three TCM experts independently evaluated model outputs on two dimensions: syndrome differentiation consistency and terminology standardization of syndrome patterns. In addition, zero-shot cross-disease transfer evaluation was conducted on gynecological and heart-system disorder test sets. ResultsAt the structural parsing level, PR-CoT supervision did not lead to a stable improvement in the element-wise overlap of syndrome pattern structural components. Compared with the corresponding baselines, neither Qwen3-32B nor Qwen3-14B showed consistent advantages in structural matching metrics after the introduction of PR-CoT supervision. In contrast, at the semantic similarity level, PR-CoT supervision produced stable positive gains across different model scales and evaluation systems. The average semantic score of Qwen3-32B increased from 6.425 8 in the baseline model to 6.585 0 after PR-CoT supervision, and that of Qwen3-14B increased from 5.870 0 to 5.964 2. At the expert blind review level, the overall score of Qwen3-32B (PR-CoT) was 7.026 0±0.107 7, higher than 6.416 3±0.288 9 for its baseline. In zero-shot cross-disease testing, the PR-CoT model still showed advantages in semantic evaluation and expert evaluation on both gynecological and heart-system disorder test sets, indicating a certain degree of transferability. ConclusionThe benefits of PR-CoT supervision are mainly reflected in TCM semantic consistency and clinical plausibility, rather than in improved hard matching of structural elements. These findings support understanding syndrome manifestation recognition as a process of generating and expressing latent pathogenesis structures, rather than as a classification task within a traditional fixed label space. By introducing pathogenesis reasoning as an explicit intermediate structure into the modeling process and combining it with a progressive multidimensional evaluation framework, this study provides a methodological pathway for intelligent TCM syndrome differentiation that integrates theoretical alignment, interpretability, and multi-level evaluation.

To analyze the standard establishment approach and compilation rationale for metallic pharmaceutical packaging standard development in the 2025 edition of the Pharmacopeia of the People's Republic of China.This article systematically explained the background and process of establishing the guiding principles for metallic materials and containers used in pharmaceutical packaging in the Chinese Pharmacopoeia through basic information,relevant domestic and international standards,the establishment of key quality attributes of metallic pharmaceutical packaging materials,and the construction of metallic pharmaceutical packaging material standards.The newly established guidelines,the Pharmacopeia of the People's Republic of China 9625,prioritized product critical quality attributes(CQAs)and real-world applicability.This dual emphasis on rigidity and adaptability enhances drug safety,meets the regulatory requirements,and promotes the globalization and scientific advancement of China's pharmaceutical packaging industry.

Aim To investigate the effect of Huangqi injection(HI)and Huangqi oral solution(HO)on cisplatin-induced nephrotoxicity(CIN)based on un-targeted metabolomics technology and the underlying mechanisms.Methods Sprague Dawley(SD)rats were randomly divided into the blank group,cisplatin(CDDP)model group,HI treatment group,and HO treatment group,then the CIN model was built with low dose multiple intraperitoneal injections of CDDP.Pre-liminary evaluation of the renal protective efficacy of HI and HO was performed by measuring serum creatinine(Scr),blood urea nitrogen(BUN),and organ indi-ces.Further screening and identification of potential biomarkers(PBs)related to CIN and HI/HO pharma-cological effects were attained through metabolomics studies of renal tissues,and pathway enrichment analy-sis was conducted.Results HI and HO significantly restored the abnormal increase in renal function indica-tors and abnormal decrease in organ indices caused by CDDP,as well as significantly improved the abnormal renal metabolic profile induced by CDDP,indicating that both HI and HO had good alleviating effects on CIN.HI significantly reversed 47 out of 54 CIN related PBs,mainly involving metabolic pathways such as glycerophospholipid metabolism,tryptophan metabo-lism,pantothenate and CoA biosynthesis;HO signifi-cantly reversed 18 out of 54 CIN related PBs,mainly involving metabolic pathways such as taurine and hypo-taurine metabolism,ascorbate and aldarate metabo-lism,pentose and glucuronate interconversions.Con-clusions Both HI and HO have significant alleviating effects on CIN.In the short term,HI salleviating effect is superior to that of HO.Overall,the mechanisms by which both alleviate CIN are mainly related to regula-ting lipid metabolism,amino acid metabolism.

Objective::To analyze fetal renal abnormality genetic features and the prenatal characteristics of the 17q12 microdeletion syndrome.Methods::This prospective cohort study examined prenatal ultrasound findings of renal abnormalities in pregnant women who underwent single nucleotide polymorphism (SNP) array or copy number variation sequencing (CNV-seq) testing on amniotic fluid or fetal tissue at Tianjin Central Obstetrics and Gynecology Hospital between January 2016 and August 2022. The study cohort comprised women with advanced maternal age, fetal ultrasound anomalies, high-risk non-invasive prenatal testing results, or suspected 17q12 microdeletion syndrome. Comprehensive clinical data, including maternal age, detailed ultrasound findings, and pregnancy outcomes, were systematically collected. SNP-array analysis was conducted using an Affymetrix CytoScan 750 K Array Chip to identify CNVs and loss of heterozygosity, while CNV-seq was performed on the Illumina HiSeq 2000 platform. Detected variants were classified according to the American College of Medical Genetics and Genomics guidelines. Statistical analyses were performed using SPSS version 27.0.Results::Abnormal renal development was identified in 141 patients, among whom 26 exhibited hyperechogenic kidneys (HCK). Of these, 12 cases were associated with 17q12 microdeletion syndrome, while the remaining 14 were linked to other chromosomal abnormalities. When excluding patients with HCK, those diagnosed with polycystic kidney disease demonstrated a higher prevalence of chromosomal abnormalities compared to those with multicystic dysplastic kidney and renal dysplasia. Although isolated conditions such as horseshoe kidney, hydronephrosis, ectopic kidney, and unilateral kidney typically presented with normal chromosomal findings, the incidence of chromosomal abnormalities increased when these conditions coexisted with other anomalies. A detailed analysis of the correlation between 17q12 microdeletion syndrome and HCK revealed that 12 out of the 14 patients diagnosed with 17q12 microdeletion syndrome exhibited HCK. Genetic testing confirmed the syndrome in seven patients, with five cases attributed to novel mutations and two cases resulting from inherited mutations.Conclusion::Fetal HCK was closely associated with the 17q12 microdeletion syndrome, and polycystic kidney disease showed a higher rate of chromosomal abnormalities. Chromosome test results were mostly normal in patients with other renal abnormalities, such as kidney dysplasia, horseshoe kidneys, hydronephrosis, kidney deficiency, and ectopic kidneys. Prenatal diagnosis is recommended, especially in cases of non-isolated fetal renal abnormalities. This study provides strong evidence supporting a link between fetal renal abnormalities and genetic syndromes.

Objective:To evaluate the value of ultrasound radiomics combined with machine learning for early diagnosis of seronegative Hashimoto’s thyroiditis (SN-HT) .Methods:This retrospective study included 164 patients from Liaoning Provincial People’s Hospital , Lixin County People’s Hospital, Linghai Dalinghe Hospital, Fengcheng Phoenix Hospital, who underwent thyroidectomy for solitary nodules with normal thyroid function between Nov. 2016 and Jan. 2024. Postoperative pathology confirmed Hashimoto’s thyroiditis (HT) in some cases, who were further categorized into antibody-positive and antibody-negative groups based on serum antibody status. Patients without Hashimoto’s thyroiditis served as the control group. A total of 298 ultrasound images were analyzed. Radiomics features were extracted from hypoechoic non-nodular areas within 0.5 cm surrounding the tumor. Two senior pathologists and two senior ultrasound physicians independently assessed lymphocytic infiltration, eosinophilic changes of follicular epithelium, and the proportion of hypoechoic areas in pathology and ultrasound images, respectively. A machine learning model, CCH-NET, was developed using linear regression and t-distributed stochastic neighbor embedding (t-SNE) techniques. The dataset was divided into a training set (80%) and a validation set (20%) to compare the diagnostic accuracy of CCH-NET with that of senior ultrasound physicians. Results:In internal validation, CCH-NET achieved a diagnostic accuracy of 88.89% for both antibody-positive and antibody-negative groups, significantly higher than the 66.67% accuracy of senior ultrasound physicians ( P<0.01). In external validation, CCH-NET achieved 75.00% and 66.67% accuracy for the two groups, compared to 50.00% by senior ultrasound physicians. For the control group, both methods achieved 93.33% accuracy. The AUC of CCH-NET was 0.848, outperforming senior ultrasound physicians (0.681) ,demonstrating superior diagnostic performance. Conclusion:The radiomics-based CCH-NET model, using non-nodular hypoechoic areas as a specific indicator, can accurately identify early SN-HT in euthyroid patients. It significantly outperforms senior ultrasound physicians, improving diagnostic accuracy and reducing missed diagnoses.

Aim To study the effect of anti-PD-L1 monoclonal antibody on high-fat diet-induced athero-sclerosis in ApoE-/-mice.Methods Twenty-four ApoE-/-mice were randomly divided into the normal group,high-fat group,and high-fat+anti-PD-L1 mAb group.After 70 days,the blood samples were harves-ted.Blood vessels(aortic root to abdominal aorta)and liver from each groups were stained with Oil Red O.Hematoxylin-eosin staining(HE)was employed to vis-ualize structural changes in liver.Enzyme-linked im-munosorbent assay(ELISA)was applied to detect the serum levels of total cholesterol(CHO),triglyceride(TG),high-density lipoprotein(HDL-c),low-density lipoprotein(LDL-c)and inflammatory factors(IFN-γ,TNF-α,IL-1 β).Flow cytometry was used to detect the proportion of lymphocytes(CD4 and CD8).RT-PCR was utilized to assess the expressions of IFN-γ,TNF-α,IL-1 β,CD4 and CD8 in liver.Results Compared with the high-fat group,the treatment with anti-PD-L1 monoclonal antibody promoted vascular wall and liver lipid accumulation,and also up-regulated serum and liver content of cholesterol(CHO),triglyceride(TG)and high-density lipoprotein(HDL-c).Treatment with anti-PD-L1 monoclonal antibody up-regulated the con-tent of alanine aminotransferase(GPT)and aspartate aminotransferase(GOT)in serum and liver,but not al-kaline phosphatase(AKP).ELISA test indicated that treatment with anti-PD-L1 monoclonal antibody stimu-lated the serum level of IFN-γ,TNF-α and IL-1 β.Fur-thermore,the mRNA level of IFN-γ,TNF-α and IL-1 βin liver was also up-regulated after treatment with anti-PD-L1 monoclonal antibody.With flow cytometry,we observed that treatment with anti-PD-L1 monoclonal antibody promoted hepatic CD8+T and CD8+IFN-γ+T cell activation,but had no effect on CD4+IFN-γ+T cell activation under high-fat feeding conditions.Con-clusions Anti-PD-L1 monoclonal antibody adminis-tered under high-fat feeding conditions can damage liv-er function and aggravate atherosclerosis by activating liver CD8+IFN-γ+T cells.

Objective To study the medication law of Professor Wang Zhongyi in the treatment of tic disorder(TD)based on data mining technology.Methods From January 1,2022 to December 31,2023,the cases treated for TD in Professor Wang Zhongyi's outpatient clinic,which participated in the real-world study were collected.A comprehensive database has been established,screening information related to effective case diagnosis and treatment.Utilizing Excel 2021,R 4.4.2,Origin 2024 and Cytoscape 3.9.1,this study conducted medication frequency analysis,property-flavor-meridian tropism analysis,efficacy analysis,association rule analysis,clustering analysis and co-occurrence network analysis to summarize medication law.Results Totally 640 effective prescriptions were included,involving 208 kinds of Chinese materia medica.The properties were mainly warm,cold,and neutral.The flavors were mainly pungent,bitter and sweet.The meridians were mainly liver meridians.The therapeutic categories were primarily composed of liver-calming and endogenous wind-stopping drugs,along with exterior-resolving prescriptions.Correlation analysis obtained 17 strongly correlated rules.Clustering analysis obtained 5 types of medicinal combinations.The therapeutic categories were primarily composed of liver-calming and endogenous wind-stopping drugs,along with exterior-resolving prescriptions.Conclusion According to the comprehensive statistical analysis,Uncariae Ramulus cum Uncis,Gastrodiae Rhizoma,Haliotidos Concha,Paeoniae Radix alba,Bupleuri Radix,Puerariae Lobatue Radix and Scorpio are the core drugs used by Professor Wang Zhongyi to treat TD.Professor Wang Zhongyi believes that the core pathogenesis of TD is the internal movement of liver wind,and the treatment mainly focuses on calming the liver,calming the wind and stopping spasms,while also nourishing the heart,calming the mind,harmonizing blood and relieving qi.Based on different clinical symptoms of TD,modifications and adjustments are made to the core prescription to treat children with TD.

Aim To investigate the intervention effect of Rehmannia radix water extract on bleomycin(BLM)-induced pulmonary fibrosis in mice combined with metabolomics and to reveal the potential mechanism,in order to provide new ideas for clinical treatment of pul-monary fibrosis.Methods Male C57BL/6N mice were randomly divided into the control group,model group,pirfenidone group(positive control,PFD,270 mg·kg-1),and low dose(DH-L,4.55 g·kg-1)group,medium dose(DH-M,9.1 g·kg-1)group and high dose(DH-H,18.2 g·kg-1)group of Rehman-nia.Except for the control group,BLM(5 mg·kg-1)was instilled into the trachea to establish the model of pulmonary fibrosis in the other groups.The survival rate,lung index and blood oxygen saturation of mice in each group were evaluated.HE and Masson staining were used to observe the pathological changes of lung tissue.WBP was used to detect lung function.Flow cytometry was used to detect the apoptosis of primary lung cells,ROS and immune cells.ELISA was used to detect the levels of fibrosis markers and inflammatory factors(α-SMA,collagen Ⅰ,collagen Ⅲ,TGF-β1,TNF-α,IL-1 β,and IL-6).Biochemical method was employed to detect the contents of GSH-Px,T-SOD and MDA.Liquid chromatograph mass spectrometer(LC-MS)metabolomics was used to analyze the changes of serum metabolic profile.Results Water extract of Re-hmannia significantly increased the survival rate,oxy-gen saturation and lung function of mice with pulmona-ry fibrosis,reduced the lung coefficient,ameliorated pathological damage and collagen deposition in lung tissue,reduced the levels of apoptosis and oxidative stress,and down-regulated the levels of inflammatory factors in lung tissue.It regulated the levels of metabo-lites such as bile acid metabolism,sphingolipid metabo-lism,and unsaturated fatty acid metabolism.Conclu-sions Water extract of Rehmannia inhibits lung injury and collagen deposition in mice with pulmonary fibrosis by inhibiting inflammatory response,which may be a-chieved by regulating the levels of inflammatory factors through the metabolic pathways of bile acid and sphin-golipid.

Purpose To evaluate the predictive value of multifunctional parameters of single photon emission computed tomography gated myocardial perfusion imaging(SPECT G-MPI)for major adverse cardiovascular events(MACE)in chronic kidney disease(CKD)with abnormal stress myocardial perfusion.Materials and Methods A total of 99 patients diagnosed with CKD from June 2017 to March 2024 who underwent stress and rest G-MPI indicating abnormal myocardial perfusion in Beijing Anzhen Hospital,Capital Medical University.The American Heart Association 17-segment 5-point method and PHASE software were used to obtain the left ventricular myocardial perfusion,functional and synchronization parameters.According to the occurrence of MACE,the patients were divided into MACE group and non-MACE group.Cox regression was used to analyze the predictors related to MACE.The receiver operator characteristic curve was used to analyze the performance of predictors,the survival curves were obtained by the Kaplan-Meier method,Log-rank test was used to compare the differences in different groups.Results Finally,we enrolled 99 CKD patients with abnormal stress myocardial perfusion.35 patients(35.35%)developed MACE during the follow-up period.Cox regression analysis showed that stress phase bandwidth(SPBW)(HR=1.015,95%CI 1.002-1.028)and sum difference score(SDS)(HR=1.105,95%CI 1.008-1.211)were independent risk factors for predicting MACE(both P<0.05).The optimal cut-off value of SPBW and SDS for predicting MACE were 69° and 6 points,the area under the curve was 0.801 and 0.778,respectively.The incidence of MACE in the SPBW≥69° group and SDS≥6 points group was higher than that in SPBW<69° group and SDS<6 points group(66.6%vs.13.2%,53.3%vs.20.4%,both P<0.05).Conclusion SPECT G-MPI multifunctional parameters can be used to predict the prognosis of CKD patients with abnormal stress myocardial perfusion.SPBW and SDS are independent risk factors for MACE in these patients.