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.

Artificial intelligence (AI) researchers and cheminformatics specialists strive to identify effective drug precursors while optimizing costs and accelerating development processes. Digital molecular representation plays a crucial role in achieving this objective by making molecules machine-readable, thereby enhancing the accuracy of molecular prediction tasks and facilitating evidence-based decision making. This study presents a comprehensive review of small molecular representations and AI-driven drug discovery downstream tasks utilizing these representations. The research methodology begins with the compilation of small molecule databases, followed by an analysis of fundamental molecular representations and the models that learn these representations from initial forms, capturing patterns and salient features across extensive chemical spaces. The study then examines various drug discovery downstream tasks, including drug-target interaction (DTI) prediction, drug-target affinity (DTA) prediction, drug property (DP) prediction, and drug generation, all based on learned representations. The analysis concludes by highlighting challenges and opportunities associated with machine learning (ML) methods for molecular representation and improving downstream task performance. Additionally, the representation of small molecules and AI-based downstream tasks demonstrates significant potential in identifying traditional Chinese medicine (TCM) medicinal substances and facilitating TCM target discovery.
Artificial Intelligence ; Drug Discovery/methods* ; Humans ; Machine Learning ; Medicine, Chinese Traditional ; Small Molecule Libraries/chemistry*

Objective:To evaluate the utility of the Rapid Axial Roll Test （RART）, Supine Roll Test （SRT）, and Lying-Down Test （LDT） in determining the affected semicircular canal in cases of horizontal semicircular canal benign paroxysmal positional vertigo （HSC-BPPV）. Methods:A total of 330 patients diagnosed with HSCBPPV from September 2022 to September 2023 were collected and divided into three groups based on the different positional tests received: ①SRT Group, ②LDT+SRT Group, ③RART+SRT Group. The trial was divided into two stages: LDT/RART for patients in the first stage, and SRT for patients in the second stage. The elicitation rate of nystagmus among the three groups was compared to evaluate the accuracy in determining the affected semicircular canal in HSCBPPV. Results:Nystagmus was elicited in 84.55% （279/330） of the patients by positional tests. The elicitation rate of nystagmus in the RART+SRT/LDT group was 94.55% （104/110）, in the LDT+SRT group it was 84.11% （90/107）, and in the SRT group it was 69.91% （79/113）. The differences among the three groups were statistically significant （χ²= 23.88, P<0.001）. In the ② and ③ groups, there was a statistically significant difference in the elicitation rate of nystagmus between stage Ⅰ （patients with LDT or RART） （χ²=43.842, P<0.001）. SRT was performed in the stage Ⅱ, and there was a statistically significant difference in nystagmus extraction rate between the two groups （χ² =4.690, P=0.030）. The difference in the proportion of agreement between stage Ⅰ（LDT or RART） and stageⅡ （SRT） in determining the affected side of the semicircular canal was also statistically significant （χ² =40.502, P<0.001）. For patients with a consistent diagnosis of the affected semicircular canal, the difference in cure rate was not significant （P=0.149）. The Kappa statistic indicated substantial agreement between RART and SRT in terms of eliciting nystagmus （agreement 96.36%, Kappa = 0.730, P<0.001）. Conclusion:RART and SRT show a high degree of agreement regarding the elicitation rate of nystagmus. RART is simple and safe, and it can effectively induce the characteristic nystagmus of HSC-BPPV, accurately identify the responsible semicircular canal and provide a more optimized examination protocol for clinical practice in HSCBPPV.
Humans ; Semicircular Canals/physiopathology* ; Benign Paroxysmal Positional Vertigo/diagnosis* ; Female ; Male ; Middle Aged ; Nystagmus, Pathologic/diagnosis* ; Vestibular Function Tests/methods* ; Aged ; Vertigo/diagnosis* ; Adult

Adriamycin is a widely used anti-tumor drug.Targeting mitochondrial fusion proteins/mitofusion 1/2(MFN1/2)and nuclear factor-erythroid 2-related factor 2(NRF2)can up-regulate the expression of mitochondrial fusion protein through PKCε/Stat3/MFN2,SIRT1/MFN2,AMPK/NRF2 and other signaling pathways,promote mitochondrial fusion,maintain kinetic balance and protect mitochondrial function,reduce myocardial cell apoptosis and reduce cardiac toxicity.Understanding the regulatory role and mechanism of mitochondrial fusion in doxorubicin-induced cardio toxicity will provide new strategies for the prevention and treatment of diseases.

Objective To investigate the expressions of long non-coding RNA antisense non-cod-ing RNA in the INK4 locus(lncRNA ANRIL)and microRNA-181b-5p(miR-181b-5p)in the serum of patients with colon cancer complicated with type 2 diabetes mellitus(T2DM)and their correlations with lymph node metastasis.Methods A total of 117 patients with colon cancer complicated with T2DM in the hospital from May 2019 to August 2022 were selected as colon cancer with T2DM group and divided into lymph node metastasis group(n=56)and no lymph node metastasis group(n=61)according to the lymph node metastasis status.Additionally,117 healthy volunteers with physical ex-aminations in the same period were selected as control group.Reverse transcription real-time quantita-tive PCR was used to detect the relative expression levels of serum lncRNA ANRIL and miR-181b-5p.Logistic regression analysis was conducted to explore the factors influencing lymph node metastasis in patients with colon cancer complicated with T2DM.Receiver operating characteristic(ROC)curve was plotted to analyze the diagnostic values of serum lncRNA ANRIL and miR-181b-5p levels for lymph node metastasis in patients with colon cancer complicated with T2DM.Pearson correlation a-nalysis was used to investigate the correlation between serum lncRNA ANRIL and miR-181b-5p ex-pression in patients with colon cancer complicated with T2DM.Results Compared with the control group,patients in the colon cancer with T2DM group had significant increased serum lncRNA ANRIL level and decreased miR-181b-5p level(P＜0.01).Compared with the no lymph node metastasis group,patients in the lymph node metastasis group had significant increased serum lncRNA ANRIL level and decreased miR-181b-5p level(P＜0.01).There were significant differences in TNM stage,degree of differentiation,and glycated hemoglobin(HbA1C)between the lymph node metas-tasis group and the no lymph node metastasis group(P＜0.05).History of diabetes,TNM stage,degree of differentiation,HbA1 C,and lncRNA ANRIL were influencing factors for lymph node me-tastasis(P＜0.05),while miR-181b-5p was a protective factor against lymph node metastasis(P＜0.05).There was a negative correlation between serum lncRNA ANRIL and miR-181b-5p levels(r=-0.440,P＜0.001).The ROC curve result showed that the areas under the curve(AUCs)for the diagnosis of lymph node metastasis by serum lncRNA ANRIL,miR-181b-5p,and their com-bination were 0.800,0.837 and 0.930 respectively.The combined diagnostic value was significant-ly higher than that of lncRNA ANRIL(Z=2.956,P=0.003)and miR-181b-5p(Z=2.117,P=0.034)alone.Conclusion Patients with colon cancer complicated with T2DM have increased ser-um lncRNA ANRIL level and decreased miR-181b-5p level,and both two indexes are correlated with lymph node metastasis.

The health of women and children serves as the cornerstone of comprehensive public health and represents a crucial barometer for measuring social progress and civilization. It directly impacts family well-being and social harmony. As a national-level guidance center for complex disease diagnosis and treatment, Beijing's critical maternal care center, and the designated consultation hospital for pregnancy complicated by rheumatic immune and endocrine disorders, Peking Union Medical College Hospital bears significant responsibilities in managing complex medical cases and implementing counterpart assistance programs. Confronted with diverse and complicated maternal sources, particularly emergency cases lacking standardized prenatal care, the hospital has established a multi-tiered, whole-process, and comprehensive maternal-infant safety management system. Through implementing high-risk maternal management protocols, optimizing critical care procedures, promoting informatization development, and enhancing multidisciplinary collaboration, Peking Union Medical College Hospital has substantially improved the efficiency of critical maternal care and maternal-infant safety assurance. This paper systematically summarizes the institutional development experience in maternal management and explores potential optimization approaches, aiming to provide valuable references for enhancing maternal-infant safety management systems in domestic healthcare institutions.

This paper presents an automatic acquisition and analytic procedure of acupuncture manipulation based on optical navigation, aiming at solving the shortcomings of existing acquisition methods of acupuncture manipulation. An acquisition holder installed at the handle tail of filiform needle was designed to display the movement trajectory of the needle during acupuncture delivery by collecting the movement trajectory of holder. The 3-month old male Bama miniature pig was selected as the experimental subject, and 6 points, "Bojian" "Qiangfeng" "Housanli" "Xiaokua" "Huiyang" (BL35) and "Baihui" (GV20), were selected during acupuncture manipulation. The optical navigation system was used to collect the real-time data, and these data were per-processed and analyzed using mean filtering and Fourier transform. The acupuncture procedure was divided into 3 stages, inserting, lifting-thrusting, and twisting. The results showed that the accuracy was 96.3% at lifting-thrusting stage, and that was 100.0% at twisting stage. The decomposition effect of the entire procedure was satisfactory. This study provides a new approach to the quantitative analysis of acupuncture manipulation. In the future, it needs to further optimize the algorithm and expand the sample size so as to improve the accuracy of this analytic technique.
Acupuncture Therapy/methods* ; Male ; Animals ; Swine ; Acupuncture Points ; Humans ; Swine, Miniature ; Needles

The study investigated the specific mechanism by which oxocrebanine, the anti-hepatic cancer active ingredient in Stephania hainanensis, inhibits the proliferation of hepatic cancer cells. Firstly, methyl thiazolyl tetrazolium(MTT) assay, 5-bromodeoxyuridine(BrdU) labeling, and colony formation assay were employed to investigate whether oxocrebanine inhibited the proliferation of HepG2 and Hep3B2.1-7 cells. Propidium iodide(PI) staining was used to observe the oxocrebanine-induced apoptosis of HepG2 and Hep3B2.1-7 cells. Western blot was employed to verify whether apoptotic effector proteins, such as cleaved cysteinyl aspartate-specific protease 3(c-caspase-3), poly(ADP-ribose) polymerase 1(PARP1), B-cell lymphoma-2(Bcl-2), Bcl-2-associated X protein(Bax), Bcl-2 homologous killer(Bak), and myeloid cell leukemia-1(Mcl-1) were involved in apoptosis. Secondly, HepG2 cells were simultaneously treated with oxocrebanine and the autophagy inhibitor 3-methyladenine(3-MA), and the changes in the autophagy marker LC3 and autophagy-related proteins [eukaryotic translation initiation factor 4E-binding protein 1(4EBP1), phosphorylated 4EBP1(p-4EBP1), 70-kDa ribosomal protein S6 kinase(P70S6K), and phosphorylated P70S6K(p-P70S6K)] were determined. The results of MTT assay, BrdU labeling, and colony formation assay showed that oxocrebanine inhibited the proliferation of HepG2 and Hep3B2.1-7 cells in a dose-dependent manner. The results of flow cytometry suggested that the apoptosis rate of HepG2 and Hep3B2.1-7 cells increased after treatment with oxocrebanine. Western blot results showed that the protein levels of c-caspase-3, Bax, and Bak were up-regulated and those of PARP1, Bcl-2, and Mcl-1 were down-regulated in the HepG2 cells treated with oxocrebanine. The results indicated that oxocrebanine induced apoptosis, thereby inhibiting the proliferation of hepatic cancer cells. The inhibition of HepG2 cell proliferation by oxocrebanine may be related to the induction of protective autophagy in hepatocellular carcinoma cells. Oxocrebanine still promoted the conversion of LC3-Ⅰ to LC3-Ⅱ, reduced the phosphorylation levels of 4EBP1 and P70S6K, which can be reversed by the autophagy inhibitor 3-MA. It is prompted that oxocrebanine can inhibit the proliferation of hepatic cancer cells by inducing autophagy. In conclusion, oxocrebanine inhibits the proliferation of hepatic cancer cells by inducing apoptosis and autophagy.
Humans ; Apoptosis/drug effects* ; Autophagy/drug effects* ; Cell Proliferation/drug effects* ; Hep G2 Cells ; Liver Neoplasms/genetics* ; Carcinoma, Hepatocellular/genetics* ; Caspase 3/genetics*