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.

OBJECTIVE To compare the predictive accuracy and clinical applicability of four vancomycin individualized dosing tools （SmartDose， ClinCalc， Gulou， Pharmado） and provide a basis for rational clinical medication use. METHODS A retrospective cohort study was conducted， enrolling 479 adult patients who received vancomycin therapy and underwent steady-state trough concentration monitoring in Zhongshan Hospital， Fudan University （Xiamen Branch） from January 1， 2022， to June 30， 2024. The predictive accuracy of each tool was evaluated using indicators， such as mean error （ME）, mean absolute error （MAE）， mean percentage error （MPE）， mean absolute percentage error （MAPE）， the proportion of patients with an absolute percentage error （APE） of less than 30%， the 95% limits of agreement， and the overall relative percentage difference between predicted and measured values. Using indicators such as accessibility， patient management， and recommendation of multiple treatment options， the clinical panxso@163.com applicability of the tools for all patients was evaluated； using the discrepancy in accuracy between the predicted and actual measured blood drug concentrations as an indicator， the clinical applicability was assessed for patients in different renal function subgroups （hyperfunction， normal， mild impairment， moderate impairment， and severe impairment）. RESULTS In terms of accuracy， SmartDose demonstrated the best overall performance with an MAPE of 46.40% and a proportion of APE ＜30% （46.56%）. Bland-Altman analysis indicated that SmartDose had the smallest overall relative percentage difference （－7.25%）， although the 95% limits of agreement were broad for all tools， with differences between the upper and lower limits exceeding 200%. In terms of applicability， all four dosing tools were freely accessible and demonstrated good availability； SmartDose and Pharmado provided the most comprehensive solutions， offering features such as patient management， multiple regimen recommendations， and drug concentration-time curve plotting. Stratified analysis based on renal function revealed that Pharmado showed optimal prediction for hyperfiltration patients （mean difference： 0.11 mg/L）. SmartDose and ClinCalc showed relatively better performance in normal and mild renal impaiment （mean difference： 0.37， 0.51 mg/L and －1.13， －1.33 mg/L，respectively）. SmartDose performed best in moderate renal impairment （mean difference： －2.60 mg/L）. Pharmado and Gulou had smaller prediction biases in severe renal impairment （mean differences： 1.52 mg/L and －0.23 mg/L， respectively）. CONCLUSIONS The four individualized dosing tools demonstrated limited accuracy in the initial prediction of vancomycin concentrations. Among them， SmartDose demonstrates the highest overall prediction accuracy and possesses comprehensive clinical management features. It is recommended that Pharmado be preferred for patients with renal hyperfiltration； SmartDose or ClinCalc can be used for patients with normal or mildly impaired renal function； SmartDose is recommended for patients with moderately impaired renal function； Pharmado or Gulou may be considered for patients with severely impaired renal function.

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*

Forsythia suspensa is a traditional Chinese medicine and a commonly used landscaping plant. Its dried fruit is used in medicine for its functions of clearing heat, removing toxins, reducing swelling, dissipating masses, and dispersing wind and heat. It possesses extremely high medicinal and economic value. However, the genetic differentiation and diversity of its wild populations remain unclear. In this study, chloroplast genome sequences were obtained from 15 wild individuals of F. suspensa using high-throughput sequencing technology. The sequence characteristics and intraspecific variations were analyzed. The results were as follows:(1) The full length of the F. suspensa chloroplast genome ranged from 156 184 to 156 479 bp, comprising a large single-copy region, a small single-copy region, and two inverted repeat regions. The chloroplast genome encoded a total of 132 genes, including 87 protein-coding genes, 37 tRNA genes, and 8 rRNA genes.(2) A total of 166-174 SSR loci, 792 SNV loci, and 63 InDel loci were identified in the F. suspensa chloroplast genome, indicating considerable genetic variation among individuals.(3) Population structure analysis revealed that F. suspensa could be divided into five or six groups. Both the population structure analysis and phylogenetic reconstruction results indicated significant genetic variation within the wild populations of F. suspensa, with no obvious correlation between intraspecific genetic differentiation and geographical distribution. This study provides new insights into the genetic diversity and differentiation within F. suspensa species and offers additional references for the conservation of species diversity and the utilization of germplasm resources in wild F. suspensa.
Genome, Chloroplast ; Forsythia/classification* ; Phylogeny ; Genetic Variation ; Chloroplasts/genetics* ; Microsatellite Repeats

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

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