As a distinctive resource of Chinese civilization， traditional Chinese medicine （TCM） technology transfer faces significant opportunities under the background of digital and intelligent transformation， while also being constrained by unique challenges such as the complexity of its theoretical system， lengthy industrial chains， and multidimensional policy restrictions， resulting in a "high-value-high-threshold" paradox. At present， TCM technology transfer is deeply trapped in a "threefold reluctance" dilemma， i.e.， unwillingness to transfer， inability to transfer， and lack of capacity to transfer. Specifically， the disconnection between scientific research evaluation systems and market demand leads to low conversion rates of research achievements， unclear ownership and compliance risks suppress innovation incentives， and the absence of professional services intensifies supply-demand mismatches. This article systematically analyzes the specific characteristics of TCM technology transfer and proposes a breakthrough pathway centered on full-chain digital and intelligent transformation. By integrating technologies such as intelligent sorting systems， blockchain-based traceability， and AI diagnostic models， the TCM ecosystem spanning "cultivation-production-service" can be reconstructed. In terms of standardization， promoting the progression from "experience-based data conversion" to "data standardization" and further to "intelligent standardization" is advocated to resolve quality control challenges. For example， a "three-no-one-full" certification system can strengthen quality trust. Policy coordination should focus on optimizing mechanisms for the transformation of scientific and technological achievements， while exploring intellectual property securitization and risk-sharing models to stimulate research momentum. In terms of internationalization， reliance on the Belt and Road Initiative platform to promote the export of geo-authentic medicinal material brands and standards is recommended to build a dual-driven model of "technology plus culture". Looking ahead， through the construction of national-level databases， the cultivation of interdisciplinary talent， and the mutual recognition of international standards， a new paradigm of "scientific intelligent manufacturing" can be formed， providing systematic solutions for the modernization of TCM and global health governance.

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.

This study aims to understand the epidemic distribution characteristics,antimicrobial resistance,virulence genes,and biofilm adhesion ability of Enterococcus in yaks on the Tibetan plateau.Three hundred and forty-six fresh yak fecal samples and 311 milk samples were collected from four provinces on the Tibetan plateau(Xizang,Sichuan,Gansu,Qinghai),totaling 657 sam-ples.Bacterial isolation and identification were conducted,followed by 16S rDNA gene detection and the construction of a systematic evolutionary tree.The isolated strains were tested for antimi-crobial resistance and virulence genes using PCR,and sensitivity tests were performed using 18 types of antibiotics.The biofilm adhesion ability of the isolated bacteria was determined using an improved semi-quantitative crystal violet staining method.The results showed that the total isola-tion rate of Enterococcus was 32.27％,with Sichuan having the highest at 60.23％,followed by Gansu,Qinghai,and Tibet autonomous region at 42.70％,23.47％,and 18.31％respectively.In terms of sample types,the isolation rate in fecal samples was 36.71％,and in milk samples,it was 27.33％.Through PCR amplification,bands of approximately 1 400 bp were obtained,and 5 strains were selected for evolutionary analysis,forming a separate cluster.Among the 212 isolated strains,a high resistance to clindamycin,quinupristin-dalfopristin,linezolid,levofloxacin,and erythromycin was observed,with various resistance phenomena,accounting for 60.85％.Only 5 out of 12 resist-ant genes were detected,namely erm(B),tet(L),tet(O),tet(M),and ant(6)-Ia.All 13 virulence genes were detected in Enterococcus,with detection rates in the range of 5.19％to 95.76％,where cpd was 95.75％,gelE was 91.98％,efaA was 86.79％,asal was 86.32％,and the rest ranged from 5.19％to 55.66％.The fsr virulence gene was not detected in Enterococcus from milk sources.Among the isolated strains,3.30％showed medium adhesive ability,48.58％showed weak adhesive ability,and 48.11％showed no adhesive ability.The above research revealed the preva-lence of yak derived Enterococcus,the carrying status of resistance and virulence genes,and the correlation between biofilm phenotypes,laying the foundation for mastering research data on yak-derived Enterococcus in the Tibetan plateau.

An increasing number of studies have shown that there is a close relationship between Alzheimer's disease(AD)and diabetes mellitus(DM).Traditional Chinese medicine holds that"kidney yin deficiency"is the common pathogenesis of these two diseases,while modern medicine believes that their pathogenesis involves abnormal aggregation of amyloid proteins,insulin deficiency and resistance,inflammatory response,oxidative stress,and autophagy,among others.The well-known traditional Chinese medicine formula Liuwei Dihuang Pills plays a significant role in the treatment of these two diseases with the same therapeutic approach.Therefore,this article will explore the connection between Liuwei Dihuang Pills and the treatment of AD and DM from different aspects;analyze the common etiology and pathogenesis of AD and DM,and explain the mechanism of prevention and treatment of Liuwei Dihuang Pills,with the aim of providing new ideas and methods for the integrated traditional and Western medicine prevention and treatment of AD and DM in the future.

Objective To provide a comprehensive review of the modeling method of the empty bottle stimulation(EBS)anxiety model,including commonly used experimental animal strains and genders,animal grouping,modeling procedures,modeling duration,primary behavioral evaluation method,and the underlying pathological mechanisms.This aims to offer a reference for the application of the EBS anxiety model in anxiety disorder research.Methods Searches were conducted in databases such as CNKI and PubMed to collect all literature related to the EBS anxiety model,which were then systematically summarized and organized.Results(1)Male adult SD or Wistar rats are predominantly used as experimental animals;(2)The optimal modeling period is 2 weeks;(3)Behavioral evaluations primarily utilize the open field test,elevated plus maze test,and light-dark box test;(4)Pathological mechanisms involve abnormal neurotransmitter metabolism in brain regions such as the hippocampus,prefrontal cortex,and amygdala.Conclusions The EBS anxiety model exhibits an anxiety-like behavioral phenotype and associated neurobiological mechanisms,validating its utility as an animal model for the study of anxiety disorders.However,further exploration and refinement are required for its standardized construction protocol and the understanding of its mechanistic underpinnings.

OBJECTIVE: To investigate the potential mechanisms of sepsis pathogenesis in intensive care unit (ICU), with a specific focus on the role of skin microbiota, and to evaluate the causal relationships between skin microbiota and ICU sepsis using Mendelian randomization (MR). METHODS: A two-sample MR analysis was performed using skin microbiota genome-wide association study (GWAS) summary data from German population cohorts as exposures, combined with ICU sepsis susceptibility and 28-day mortality GWAS summary data from the IEU OpenGWAS database as outcomes. The primary causal effect estimates were generated using the inverse variance weighted (IVW) method, supplemented by validation through MR-Egger and weighted median approaches. Heterogeneity and pleiotropy tests, along with sensitivity analyses, were conducted to evaluate the robustness of the results. RESULTS: Regarding risk of ICU sepsis, IVW analysis showed that order Pseudomonadales [odds ratio (OR) = 0.93, 95% confidence interval (95%CI) was 0.88-0.98], family Flavobacteriaceae (OR = 0.93, 95%CI was 0.90-0.96), and genus Acinetobacter (OR = 0.96, 95%CI was 0.93-0.99) were significantly negatively correlated with the risk of ICU sepsis (all P < 0.05). There was a significant positive correlation between the risk of ICU sepsis and the presence of β-Proteobacteria (OR = 1.05, 95%CI was 1.00-1.11) and Actinobacteria (OR = 1.05, 95%CI was 1.00-1.11), both P < 0.05. Regarding 28-day mortality of ICU sepsis, IVW analysis showed that phylum Bacteroidetes (OR = 0.92, 95%CI was 0.86-0.99), family Streptococcaceae (OR = 0.92, 95%CI was 0.85-0.98), family Flavobacteriaceae (OR = 0.90, 95%CI was 0.83-0.97), genus Streptococcus (OR = 0.92, 95%CI was 0.86-0.99), ASV016 [Enhydrobacter] (OR = 0.92, 95%CI was 0.87-0.98), and ASV042 [Acinetobacter] (OR = 0.92, 95%CI was 0.88-0.97) were significantly negatively correlated with the 28-day mortality of ICU sepsis (all P < 0.05); family Moraxellaceae (OR = 1.09, 95%CI was 1.00-1.18) and ASV008 [Staphylococcus] (OR = 1.08, 95%CI was 1.03-1.14) was significantly positively correlated with the 28-day mortality of ICU sepsis (both P < 0.05). Sensitivity analysis and MR-PRESSO showed no heterogeneity, pleiotropy, or horizontal pleiotropy between skin microbiota and ICU sepsis risk and 28-day mortality rate. Analysis of confounding factors showed that single nucleotide polymorphisms (SNPs) associated with relevant skin bacteria could independently and causally affect the risk of ICU sepsis or ICU sepsis related mortality rate, independent of other confounding factors. The Steiger test results indicated that the established causal relationship was not due to reverse causality. CONCLUSIONS Skin microbiota composition may influence both sepsis susceptibility and 28-day mortality in ICU settings. Family Flavobacteriaceae demonstrated protective effects against sepsis onset and mortality. These findings provide new perspectives for early detection and management strategies.
Humans ; Sepsis/mortality* ; Intensive Care Units ; Mendelian Randomization Analysis ; Microbiota ; Skin/microbiology* ; Genome-Wide Association Study ; Risk Factors ; Skin Microbiome

Objective:To construct a clinical decision-making ability indicator system based on evidence-based practice for pediatric nursing interns, and to provide a scientific basis for clinical teaching and evaluation.Methods:A method combining literature analysis, Delphi expert consultation, and empirical research was used. Firstly, a systematic search of Chinese and English databases (2018-2023) was conducted. Literature was screened based on the PICO framework and evidence-based data were extracted, resulting in a preliminary system consisting of 4 primary indicators, 12 secondary indicators, and 39 tertiary indicators. Subsequently, the indicators were revised through two rounds of Delphi expert consultation (25 experts with 19-27 years of work experience). The expert authority coefficients (Cr) were 0.898-0.907 and the Kendall's concordance coefficients were 0.351-0.420 ( P<0.001). Finally, the analytic hierarchy process was used to determine the weights, and the reliability and validity were verified through a questionnaire survey (sample size: 30 participants in preliminary survey and 58 participants in formal survey). Results:The constructed indicator system included 4 primary indicators (weights), 13 secondary indicators, and 42 tertiary indicators. The weights of the primary indicators were as follows: knowledge integration ability (0.300), evidence-based practice ability (0.250), clinical judgment ability (0.280), and ethical decision-making ability (0.170). The importance scores of all items exceeded 4.0 points (out of 5 points), and the coefficients of variation were less than 0.20. The reliability and validity tests showed that the Cronbach's α of the overall scale was 0.89, and the intraclass correlation coefficient was 0.88. The cumulative variance contribution rate of exploratory factor analysis was 69.30%. The confirmatory factor analysis demonstrated a good model fit with a comparative fit index of 0.93 and a root mean square error of approximation of 0.05. Conclusions:This indicator system has high scientificity and practicality, and can provide a reference for the standardized cultivation and evaluation of clinical decision-making ability of pediatric nursing interns. In the future, it is necessary to strengthen advanced evidence-based skills training and long-term application effectiveness tracking.

BACKGROUND:Transthoracic echocardiography and speckle tracking echocardiography parameters are closely related to stroke occurrence and prognosis.However,the role of transthoracic echocardiography and three-dimensional speckle tracking echocardiography parameters in predicting functional disability following acute ischemic stroke remains unclear.OBJECTIVE:To explore the relationship between transthoracic echocardiography and three-dimensional speckle tracking echocardiography parameters and functional disbility at 3 months post-stroke in patients with acute ischemic stroke.METHODS:A total of 299 patients with acute ischemic stroke admitted to the Second Affiliated Hospital of Soochow University between December 2020 and September 2022 were prospectively enrolled.Patients were divided into no disability(n=207)and disability(n=92)groups based on modified Rankin Scale(mRS)scores(≤ 1 as no disability;1＜mRS score ≤ 5 as disability)at 3 months.Baseline characteristics and transthoracic echocardiography and three-dimensional speckle tracking echocardiography parameters were compared between groups.Independent risk factors for disability were identified using multivariate logistic regression.Predictive models were developed by incorporating variables associated with poor prognosis,and their performance was assessed using the receiver operating characteristic curve analysis.The optimal cutoff value for left ventricular ejection fraction was determined from the receiver operating characteristic curve,and patients were stratified into high and low left ventricular ejection fraction groups.Chi-square test was used to compare prognosis rate between two groups.RESULTS AND CONCLUSION:(1)The disability group had significantly lower left ventricular ejection fraction compared with the no disability group(P=0.011).Significant differences in the National Institute of Health Stroke Scale scores,Trial of ORG 10172 in Acute Stroke Treatment,and Oxfordshire Community Stroke Project classifications were observed(P＜0.05).Multivariate logistic regression showed that left ventricular ejection fraction,National Institute of Health Stroke Scale scores,and Oxfordshire Community Stroke Project classification were independent predictors of 3-month disability(P＜0.05).(2)The National Institute of Health Stroke Scale scores and Oxfordshire Community Stroke Project classification at admission were included in model 1,which added the left ventricular ejection fraction as model 2,and all univariate significant difference variables were included in model 3.Receiver operating characteristic analysis showed the area under the curve values of 0.769,0.806,and 0.824 for the models used to predict the 3-month disability rate.(3)The optimal cutoff for left ventricular ejection fraction from the receiver operating characteristic curve was 60.25％,classifying patients into low left ventricular ejection fraction(≤ 60.25％)and high left ventricular ejection fraction(＞60.25％)groups.The 3-month disability rate was higher in the low left ventricular ejection fraction group than in the high left ventricular ejection fraction group(44％vs.26％,P=0.002).These findings highlight that reduced left ventricular ejection fraction plays an important role in the assessment of functional disability 3 months after acute ischemic stroke.Left ventricular ejection fraction can be incorporated into routine prognostic assessments when clinically evaluating the prognosis of ischemic stroke.

Objective To investigate the clinical prognosis of untreated residual coronary artery dissection treated with drug coated balloon(DCB).Methods A retrospective analysis was conducted on the clinical and imaging data of patients with primary coronary artery lesions(2.5-4.0 mm)treated with DCB under angiography guidance at Xuzhou Cancer Hospital,Xuzhou New Health Geriatric Hospital,and Peixian Guotai Hospital from September 2017 to April 2023.According to the observation of coronary artery dissection through angiography,the patients were divided into a dissection group and a non dissection group.The main endpoint of this study was the major adverse cardiovascular event(MACE)during a 12-month follow-up.Results A total of 381 patients were enrolled in the three research centers,with 30 cases(30 lesions)in the dissection group and 351 cases(367 lesions)in the non dissection group.There was no significant difference between the two groups in terms of age,gender,hypertension,hyperlipidemia,diabetes,smoking,previous myocardial infarction,previous percutaneous coronary intervention,coronary artery bypass grafting and other baseline clinical characteristics(all P＞0.05).Except for the reference vessel diameter(P=0.049)and DCB pressure(P=0.032),there was no statistically significant difference in the characteristics of coronary angiography lesions between the two groups of patients(both P＞0.05).During a 12-month follow-up,there was no statistically significant difference(P＞0.05)in the incidence of MACE between the dissection group and the non dissection group after DCB treatment for primary coronary artery lesions in situ.Conclusions Untreated residual dissection after DCB treatment of de novo coronary lesions does not lead to an increase in clinical MACE.