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.

This paper outlines the development of artificial intelligence （AI） and its applications in traditional Chinese medicine （TCM） research， and elucidates the roles and advantages of large language models， knowledge graphs， and natural language processing in advancing syndrome identification， prescription generation， and mechanism exploration. Using spleen-stomach diseases as an example， it demonstrates the empowering effects of AI in classical literature mining， precise clinical syndrome differentiation， efficacy and safety prediction， and intelligent education， highlighting an upgraded research paradigm that evolves from data-driven and knowledge-driven approaches to intelligence-driven models. To address challenges related to privacy protection and regulatory compliance in cross-institutional data collaboration， a "trusted federated evidence-based analysis platform for TCM spleen-stomach diseases" is proposed， integrating blockchain-based smart contracts， federated learning， and secure multi-party computation. The deep integration of AI with privacy-preserving computing is reshaping research and clinical practice in TCM spleen-stomach diseases， providing feasible pathways and a technical framework for building a high-quality， trustworthy TCM big-data ecosystem and achieving precision syndrome differentiation.

[This corrects the article DOI: 10.1016/j.apsb.2022.05.019.].

Tailored lipid nanoparticles (LNPs)-mediated small interfering RNA (siRNA) nanomedicines show promise in treating liver disease, such as acute liver injury (ALI) and non-alcoholic steatohepatitis (NASH). However, constructing LNPs that address biosafety concerns, ensure efficient delivery, and target specific hepatic subcellular fractions has been challenging. To evade above obstacles, we develop three novel self-degradable "gemini-like" ionizable lipids (SS-MA, SS-DC, SS-MH) by incorporating disulfide bonds and modifying the length of ester bond and tertiary amino head. Our findings reveal that the disulfide-bond-bridged LNPs exhibit reduction-responsive drug release, improving both biosafety and siRNA delivery efficiency. Furthermore, the distance of ester bond and tertiary amino head significantly influences the LNPs' pK _a, thereby affecting endosomal escape, hemolytic efficiency, absorption capacity of ApoE, uptake efficiency of hepatocytes and liver accumulation. We also develop the modified-mannose LNPs (M-LNP) to target liver macrophages specifically. The optimized M-MH_LNP@TNFα exhibits potential in preventing ALI by decreasing tumor necrosis factor α (TNFα) levels in the macrophages, while MH_LNP@DGAT2 could treat NASH by selectively degrading diacylglycerol O-acyltransferase 2 (DGAT2) in the hepatocytes. Our findings provide new insights into developing novel highly effective and low-toxic "gemini-like" ionizable lipids for constructing LNPs, potentially achieving more effective treatment for hepatic diseases.

ObjectiveExploring the formula rules of commonly used traditional Chinese medicines（TCMs） for epidemic treatment from the Qin and Han dynasties to the Qing dynasty through data mining， providing reference for the prevention and control of contemporary epidemics. MethodsThe articles on epidemic treatment in the electronic database of Chinese Medical Code V5.0 were systematically searched， and the contents such as source， dynasty， author， diagnosis， formula name， therapeutic method and efficacy， and composition of medicines from each article that met the inclusion criteria were extracted. Then， an Excel standardized database was established， and Python programs were used for data mining to summarize the frequency of commonly used medicines and perform hierarchical cluster analysis， Pearson correlation analysis， and association rule analysis. ResultsA total of 1 595 formulas were included， involving 558 TCMs. The efficacy of these medicines could be classified into two categories， namely， expeling pathogenic factors and reinforcing healthy Qi. According to the frequency deconstruction analysis， high-frequency medicines were mainly detoxification， Fu-organ dredging， aromatization and promoting blood circulation， followed by the medicines with the effect of treating the lungs， such as clearing the lungs and resolving phlegm， clearing heat and purging the lungs， relieving cough and asthma， and purging the lungs and relieving asthma. And the proportions of acrid-warm herbs and acrid-cold herbs varied in different periods. Hierarchical clustering and correlation analysis both suggested TCMs for expeling pathogenic factors and reinforcing healthy Qi often formed stable combinations with high association degrees. Association rule analysis showed that the core acrid-warm herb was mainly Ephedrae Herba， and the core acrid-cold herb was mainly Forsythiae Fructus， resulting in the core formulas of Maxing Shigantang and Yinqiaosan. ConclusionThroughout history， the prevention and control of epidemics have been based on the principle of "preserving healthy Qi and avoiding toxic Qi"， focusing on the treatment of the causes and characteristics of epidemics through detoxification， Fu-organ dredging， and aromatization， emphasizing the use of Rhei Radix et Rhizoma and other herbs to dredge Fu-organ， eliminate toxins and pathogens， and playing the role of actively intervene with symptomatic medication. And based on the external manifestations of the body's struggle between evil and righteousness， diagnose and treatment according to syndrome differentiation was performed.

ObjectiveExploring the formula rules of commonly used traditional Chinese medicines（TCMs） for epidemic treatment from the Qin and Han dynasties to the Qing dynasty through data mining， providing reference for the prevention and control of contemporary epidemics. MethodsThe articles on epidemic treatment in the electronic database of Chinese Medical Code V5.0 were systematically searched， and the contents such as source， dynasty， author， diagnosis， formula name， therapeutic method and efficacy， and composition of medicines from each article that met the inclusion criteria were extracted. Then， an Excel standardized database was established， and Python programs were used for data mining to summarize the frequency of commonly used medicines and perform hierarchical cluster analysis， Pearson correlation analysis， and association rule analysis. ResultsA total of 1 595 formulas were included， involving 558 TCMs. The efficacy of these medicines could be classified into two categories， namely， expeling pathogenic factors and reinforcing healthy Qi. According to the frequency deconstruction analysis， high-frequency medicines were mainly detoxification， Fu-organ dredging， aromatization and promoting blood circulation， followed by the medicines with the effect of treating the lungs， such as clearing the lungs and resolving phlegm， clearing heat and purging the lungs， relieving cough and asthma， and purging the lungs and relieving asthma. And the proportions of acrid-warm herbs and acrid-cold herbs varied in different periods. Hierarchical clustering and correlation analysis both suggested TCMs for expeling pathogenic factors and reinforcing healthy Qi often formed stable combinations with high association degrees. Association rule analysis showed that the core acrid-warm herb was mainly Ephedrae Herba， and the core acrid-cold herb was mainly Forsythiae Fructus， resulting in the core formulas of Maxing Shigantang and Yinqiaosan. ConclusionThroughout history， the prevention and control of epidemics have been based on the principle of "preserving healthy Qi and avoiding toxic Qi"， focusing on the treatment of the causes and characteristics of epidemics through detoxification， Fu-organ dredging， and aromatization， emphasizing the use of Rhei Radix et Rhizoma and other herbs to dredge Fu-organ， eliminate toxins and pathogens， and playing the role of actively intervene with symptomatic medication. And based on the external manifestations of the body's struggle between evil and righteousness， diagnose and treatment according to syndrome differentiation was performed.

OBJECTIVE: To investigate the effects of acupuncture on the neurotransmitter levels and gut microbiota in a mouse model of Tourette syndrome (TS). METHODS: Thirty-six male C57/BL6 mice were randomly divided into 4 groups using a random number table method: 3,3'-iminodipropionitrile (IDPN) group, control group, acupuncture group, and tiapride group, with 9 mice in each group. In the IDPN group, acupuncture group, and tiapride group, mice received daily intraperitoneal injections of IDPN (300 mg/kg body weight) for 7 consecutive days to induce stereotyped behaviors. Subsequently, in the acupuncture intervention group, standardized acupuncture treatment was administered for 14 consecutive days to IDPN-induced TS model mice. The selected acupoints included Baihui (DU 20), Yintang (DU 29), Waiguan (SJ 5), and Zulinqi (GB 41). In the tiapride group, mice were administered tiapride (50 mg/kg body weight) via oral gavage daily for 14 consecutive days. The control group, IDPN group, and acupuncture group received the same volume of saline orally for 14 consecutive days. Stereotypic behaviors were quantified through behavioral assessments. Neurotransmitter levels, including dopamine (DA), glutamate (Glu), and aspartate (ASP) in striatal tissue were measured using enzyme-linked immunosorbent assay. Dopamine transporter (DAT) expression levels were additionally quantified through quantitative polymerase chain reaction (qPCR). Gut microbial composition was analyzed through 16S ribosomal RNA gene sequencing, while metabolic profiling was conducted using liquid chromatography-mass spectrometry (LC-MS). RESULTS: Acupuncture administration significantly attenuated stereotypic behaviors, concurrently reducing striatal levels of DA, Glu and ASP concentrations while upregulating DAT expression compared with untreated TS controls (P<0.05 or P<0.01). Comparative analysis identified significant differences in Muribaculaceae (P=0.001), Oscillospiraceae (P=0.049), Desulfovibrionaceae (P=0.001), and Marinifilaceae (P=0.014) following acupuncture intervention. Metabolomic profiling revealed alterations in 7 metabolites and 18 metabolic pathways when compared to the TS mice, which involved various amino acid metabolisms associated with DA, Glu, and ASP. CONCLUSIONS Acupuncture demonstrates significant modulatory effects on both central neurotransmitter systems and gut microbial ecology, thereby highlighting its dual therapeutic potential for TS management through gut-brain axis regulation.
Animals ; Tourette Syndrome/metabolism* ; Gastrointestinal Microbiome ; Neurotransmitter Agents/metabolism* ; Acupuncture Therapy ; Male ; Mice, Inbred C57BL ; Mice

Objective To develop a deep learning model based on fundus retinal images to improve the detection rate of mild cognitive impairment(MCI)in patients with coronary heart disease,achieve early intervention and improve prognosis.Methods The study was a single-center cross-sectional study that retrospectively included patients diagnosed with coronary heart disease(CHD)by coronary angiography(≥50％ stenosis of at least one coronary vessel)from Beijing Anzhen Hospital between November 2021 and December 2022.The whole data set was randomly divided into the training set and the testing set according to the ratio of 8∶2 for model development.After that,the patient data of the same center from January 2023 to April 2023 were included in the time verification method to verify the model.The diagnostic criteria for MCI were MMSE＜27 or MoCA＜26.Four kinds of convolutional neural network(CNN)architectures were used to train fundus images,and a comprehensive vision model of MCI detection was established through model integration.The area under the curve(AUC),sensitivity and specificity of the receiver operating curve(ROC)were used to evaluate the performance of the AI model.Results We collected 5 880 eligible fundus images from 3 368 CHD patients.Based on the results of the MMSE scale,the algorithm was labeled,including 2 898 males and 527 MCI patients.The AUC of the deep learning model in the test group is 0.733(95％CI 0.688-0.778),and the sensitivity of the algorithm in the test group is 0.577(95％CI 0.528-0.625)by using the operating point with the maximum sum of sensitivity and specificity.With a specificity of 0.758(95％CI 0.714-0.802),corresponding to a validated AUC of 0.710(95％CI 0.601-0.818).Based on the results of the MoCA scale,the algorithm labels 2 437 males and 1 626 MCI patients.The AUC of the deep learning model in the test group was 0.702(95％CI 0.671-0.733).The operating point with the maximum sum of sensitivity and specificity was selected,and the sensitivity of the algorithm was 0.749(95％CI 0.719-0.778)and the specificity was 0.561(95％CI 0.527-0.595),corresponding to the AUC value of the verification group was 0.674(95％CI 0.622-0.726).Conclusions The deep learning algorithm model based on fundus images has good diagnostic performance,and may be used as a new non-invasive,convenient and rapid screening method for MCI in CHD population.

Objective:To analyze the clinical characteristics, RAN-binding protein 2 ( RANBP2) gene variations, and prognosis in Chinese acute necrotizing encephalopathy (ANE) patients. Methods:A retrospective analysis of ANE cases registered in the Peking Union Medical College Hospital Encephalitis Registry System from 2022 to 2024, involving patients from Peking Union Medical College Hospital and other hospitals, was conducted. A descriptive study was performed on the clinical characteristics, treatments and prognosis, cerebrospinal fluid examination results, and imaging findings of these patients based on adjusted ANE diagnostic criteria. Whole-exome sequencing technology was used to detect gene mutations in these patients.Results:A total of 18 ANE cases were included, ranged in age from 2 to 72 [20(5, 43)] years. The male-to-female ratio was 4∶5. All patients were found with precipitating infections including COVID-19, influenza A virus and Mycoplasma pneumoniae infections. All patients presented with fever, with varying degrees of consciousness disturbance observed in 16 cases, and seizures in 10 cases. All patients underwent lumbar puncture, with normal or mildly elevated white cell counts [3(2, 13)×10 6/L] and mildly to moderately elevated protein levels [1.90(0.92, 4.65) g/L]. A total of 6 patients were found with extremely elevated interleukin-6 level [950(164, 2 000) pg/ml] in cerebrospinal fluid. Bilateral symmetric thalamic lesions were typical imaging features of ANE, while involvement of other areas such as cortical and subcortical white matter, brainstem, and cerebellum was also observed. A total of 14 patients performed genetic tests while 4 patients were identified with RANBP2 gene mutations (c.1754C>T in 3 cases, c.1966A>G in 1 case). All patients received immunotherapy, and 7 patients died at discharge while other patients presented with neurological sequelae of varying degrees. Conclusions:ANE is a rare and severe parainfectious encephalopathy that can occur in both children and adults. Clinically, it is characterized by rapidly progressing encephalopathy following systematic infection, with bilateral symmetric thalamic lesions. The detection of RANBP2 gene mutations could help make the diagnosis.

Objective To study the effects of Shugan Jieyu capsules on the cardiac function and state of mind of chronic heart failure(CHF)patients with anxiety and depression.Methods Ninety-four CHF patients with anxiety and depression were randomly divided into the Shugan Jieyu capsule treatment group and mental therapy control group.Self-rating depression Scale(SDS),self-rating anxiety scale(SAS),left ventricular ejection fraction(LVEF),N-terminal pro-B-type natriuretic peptide(NT-proBNP),the 6-minute walking test(6MWT),hemoglobin(Hb),interleukin-6(IL-6),albumin(ALB)and high-sensitivity c-reactive protein(hs-CRP)were compared between the two groups before and after treatment using t-tests and chi-square tests in order to find out about the efficacy of Shugan Jieyu capsules in CHF patients with anxiety and depression.Results After 8 weeks of treatment,SDS,SAS,NT-proBNP,hs-CRP and IL-6 were all significantly lower,especially in the treatment group,while LVEF,6MWT,Hb and ALB were significantly higher or longer,particularly in the treatment group.Conclusion Shugan Jieyu capsules can effectively alleviate anxiety and depression in CHF patients,improve the cardiac function and nutritional status,and mitigate inflammation.