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.

Glycosylation constitutes a critical, highly intricate, and diverse co- and post-translational modification characterized by the covalent attachment of sugar moieties to proteins, lipids, or small RNAs. Complex glycans are ubiquitously present across nearly all living organisms. Despite their prevalence, our comprehension of glycan diversity remains limited, likely due to the inherent challenges associated with elucidating their structural complexity. Among post-translational modifications, protein glycosylation is notably prevalent, involving the enzymatic transfer of oligosaccharides to specific amino acid residues by glycosyltransferases. This modification plays a pivotal role in modulating protein function, including participation in various biological and biochemical recognition processes. G protein-coupled receptors (GPCRs), encoded by approximately one thousand genes, share a conserved architecture comprising seven transmembrane helices interconnected by three intracellular and three extracellular loops. Representing the largest family of human membrane proteins, GPCRs regulate a vast array of physiological and pathological processes, thereby constituting the most extensive class of therapeutic targets. In mammalian systems, the majority of GPCRs undergo glycosylation predominantly at their extracellular N-terminus or extracellular loops, primarily through N-linked and O-linked glycosylation. These covalent carbohydrate modifications exert profound effects on multiple facets of GPCR biology, including endoplasmic reticulum folding and quality control, membrane trafficking and surface expression, receptor internalization and recycling or degradation, ligand binding and signal transduction, biased signaling, and receptor dimerization. Notably, glycosylation can exert both positive and negative regulatory influences on these processes. Dysregulation of GPCR glycosylation has been implicated in a range of pathological conditions, such as cancer, diabetes, and neurological disorders, underscoring its physiological and pathological significance. Aberrant glycosylation patterns may lead to dysfunctional receptor signaling, thereby contributing to disease progression. Consequently, elucidating the precise roles of glycosylation in GPCR function not only enhances fundamental understanding of receptor biology but also facilitates the development of novel therapeutic strategies targeting glycosylation pathways or specific GPCR glycoforms. Although the functional consequences of glycosylation have been investigated for several decades, delineating their exact structural underpinnings has remained challenging due to the intrinsic flexibility and heterogeneity of carbohydrate structures. Recent advances in structural biology, particularly single-particle cryo-electron microscopy (cryo-EM) and X-ray crystallography, have catalyzed a paradigm shift in our understanding of GPCR glycosylation. The integration of these sophisticated structural techniques with biochemical approaches has redefined glycosylation as a complex structural element integral to receptor function. These developments provide a molecular framework for comprehending how glycans influence receptor pharmacology and open new avenues for the rational design of glyco-engineered biologics and allosteric modulators targeting specific extracellular motifs. This mini-review concentrates on glycosylation within the GPCR superfamily, summarizing the impact of glycosylation modifications on receptor function and regulatory mechanisms, recent progress in the structural biology of GPCR glycosylation, and prospective directions for future research in this field.

This article analyzed the use of veno-arterio-venous extracorporeal membrane oxygenation (VAV-ECMO) in the treatment of a patient with severe cardiopulmonary insufficiency caused by inhalation of dilute nitric acid liquid and aerosol. Combined with relevant literature, the pathogenesis was discussed and the treatment experience was summarized. The inhalation of a large amount of dilute nitric acid liquid and aerosol caused severe chemical pneumonia in the patient, which resulted in severe cardiac insufficiency due to the dysregulation of the ventricular artery coupling. After the administration of VAV-ECMO, the well-oxygenated blood was effectively supplied to the systemic circulation and pulmonary circulation, and the load of the heart was reduced, providing valuable time for the recovery of the patient's cardiopulmonary function.

Objectives:To investigate association of the non-high-density lipoprotein cholesterol to high-density lipoprotein cholesterol ratio (NHHR) with the stroke severity and short-term outcome in patients with acute ischemic stroke (AIS), and to evaluate the predictive value of NHHR for outcome.Methods:Patients with the first-ever AIS admitted to the Affiliated Hospital of Qingdao University from June 2018 to June 2024 whose etiological types were large artery atherosclerosis (LAA), small vessel occlusion (SVO) and cardiac embolism (CE) were included retrospectively. According to the National Institutes of Health Stroke Scale (NIHSS) score at admission, the patients were divided into mild stroke group (≤8) and moderate to severe stroke group (>8). According to the modified Rankin Scale score at discharge, they were divided into good outcome group (≤2) and poor outcome group (>2). Multivariate logistic regression analysis was use to determine the independent correlation between NHHR and stroke severity and short-term outcome in patients with AIS. Receiver operating characteristic (ROC) curve was used to evaluate the predictive value of NHHR for short-term poor outcome in overall patients with AIS and different etiological subtypes. Results:A total of 2 865 patients with AIS were enrolled, including 1 925 males (67.2%), aged (61.00 ± 10.17) years. 2 483 patients (86.67%) had mild stroke and 382 (13.33%) had moderate to severe stroke; 2 161 (75.43%) had good short-term outcome, while 704 (24.57%) had poor short-term outcome. Multivariate logistic regression analysis showed that NHHR was significantly and independently associated with moderate to severe stroke (odds ratio [ OR] 2.251, 95% confidence interval [ CI] 1.895-2.675; P<0.001) and poor short-term outcome ( OR 3.454, 95% CI 2.936-4.063; P<0.001). ROC curve analysis showed that NHHR had a high predictive value for short-term poor outcome in patients with AIS (the area under the curve [AUC] 0.764, 95% CI 0.745-0.784), and it also demonstrated high predictive value in patients with various etiological types such as LAA (AUC=0.755, 95% CI 0.730-0.781), SVO (AUC=0.801, 95% CI 0.777-0.824) and CE (AUC=0.797, 95% CI 0.774-0.820). Conclusion:NHHR is significantly correlated with the severity of stroke and poor short-term outcome in patients with AIS, and has a high predictive value for poor short-term outcome.

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.

Animal experiments are crucial in evaluating the preclinical safety and efficacy of new dental materials, drugs, instruments, and equipment by identifying and eliminating potential health risks to humans. An international team of several dental experts formulated a guideline named Preferred Reporting Items for Animal Studiesin Endodontology (PRIASE) 2021. Consisting of 11 domains, 43 individual items, and a flowchart. PRIASE provides guidance for animal experiments in dentistry and improves the quality of experiment design and reporting. This work introduces the process and basic content of the guideline and interprets the key items of its checklist with specific examples to provide reference for the reporting of animal experiment in dentistry in China.
Animals ; Animal Experimentation/standards* ; Checklist ; China ; Endodontics ; Guidelines as Topic ; Research Design

N⁶-methyladenosine (m⁶A) modification plays a critical role in cell cycle regulation, while the mechanism of m⁶A in regulating mitosis remains underexplored. Here, we found that the total m⁶A modification level in cells increased during mitosis by the liquid chromatography-mass spectrometry/mass spectrometry and m⁶A dot blot assays. Silencing methyltransferase-like 3 (METTL3) or METTL14 results in delayed mitosis, abnormal spindle assembly, and chromosome segregation defects by the immunofluorescence. By analyzing transcriptome-wide m⁶A targets in HeLa cells, we identified polo-like kinase 1 (PLK1) as a key gene modified by m⁶A in regulating mitosis. Specifically, through immunoblotting and RNA pulldown, m⁶A modification inhibits PLK1 translation via YTH N⁶-methyladenosine RNA binding protein 1, thus mediating cell cycle homeostasis. Demethylation of PLK1 mRNA leads to significant mitotic abnormalities. These findings highlight the critical role of m⁶A in regulating mitosis and the potential of m⁶A as a therapeutic target in proliferative diseases such as cancer.
Humans ; Polo-Like Kinase 1 ; Cell Cycle Proteins/metabolism* ; Proto-Oncogene Proteins/metabolism* ; Protein Serine-Threonine Kinases/metabolism* ; Mitosis/physiology* ; HeLa Cells ; Adenosine/genetics* ; Methyltransferases/metabolism* ; RNA, Messenger/metabolism* ; RNA-Binding Proteins/metabolism*