ObjectiveTo address the challenges of unstructured classical Chinese expressions， nested entity relationships， and limited annotated data in famous traditional Chinese medicine（TCM） case records， this study proposes a joint relation extraction framework that integrates data augmentation and entity mapping， aiming to support the construction of TCM diagnostic knowledge graphs and clinical pattern mining. MethodsWe developed an annotation structure for entities and their relationships in TCM case texts and applied a data augmentation strategy by incorporating multiple ancient texts to expand the relation extraction dataset. A cascade binary tagging framework for relation triple extraction（CasRel） model for TCM semantics was designed， integrating a pre-trained bidirectional encoder representations from transformers（BERT） layer for classical TCM texts to enhance semantic representation， and using a head entity-relation-tail entity mapping mechanism to address entity nesting and relation overlapping issues. ResultsExperimental results showed that the CasRel model， combining data augmentation and entity mapping， outperformed the pipeline-based Bert-Radical-Lexicon（BRL）-bidirectional long short-term memory（BiLSTM）-Attention model. The overall precision， recall， and F₁-score across 12 relation types reached 65.73%， 64.03%， and 64.87%， which represent improvements of 14.26%， 7.98%， and 11.21% compared to the BRL-BiLSTM-Attention model， respectively. Notably， the F₁-score for tongue syndrome relations increased by 22.68%（69.32%）， and the prescription-syndrome relations performed the best with the F₁-score of 70.10%. ConclusionThe proposed framework significantly improves the semantic representation and complex dependencies in TCM texts， offering a reusable technical framework for structured mining of TCM case records. The constructed knowledge graph can support clinical syndrome differentiation， prescription optimization， and drug compatibility， providing a methodological reference for TCM artificial intelligence research.

The implementation of the Good Pharmacovigilance Practice(GVP)in 2021 has laid a solid foundation for improving China's pharmacovigilance system,a matter of paramount importance currently emphasized by Marketing Authorization Holders(MAHs).Given the unique organizational structures of corporate groups,establishing a centralized pharmacovigilance system can optimize resource utilization.This paper analyzes the challenges faced by corporate groups in developing such central-ized systems and proposes an organizational framework with defined operational divisions.The findings aim to provide actionable insights for vaccine manufacturers in establishing and refining life cycle pharmacovigilance systems.

The implementation of the Good Pharmacovigilance Practice(GVP)in 2021 has laid a solid foundation for improving China's pharmacovigilance system,a matter of paramount importance currently emphasized by Marketing Authorization Holders(MAHs).Given the unique organizational structures of corporate groups,establishing a centralized pharmacovigilance system can optimize resource utilization.This paper analyzes the challenges faced by corporate groups in developing such central-ized systems and proposes an organizational framework with defined operational divisions.The findings aim to provide actionable insights for vaccine manufacturers in establishing and refining life cycle pharmacovigilance systems.

G protein-coupled receptors (GPCRs) are a large family of membrane protein receptors, and Takeda G protein-coupled receptor 5 (TGR5) is a member of this family. As a membrane receptor, TGR5 is widely distributed in different parts of the human body and plays a vital role in regulating metabolism, including the processes of energy consumption, weight loss and blood glucose homeostasis. Recent studies have shown that TGR5 plays an important role in glucose and lipid metabolism disorders such as fatty liver, obesity and diabetes. With the global obesity situation becoming more and more serious, a comprehensive explanation of the mechanism of TGR5 and filling the gaps in knowledge concerning clinical ligand drugs are urgently needed. In this review, we mainly explain the anti-obesity mechanism of TGR5 to promote the further study of this target, and show the electron microscope structure of TGR5 and review recent studies on TGR5 ligands to illustrate the specific binding between TGR5 receptor binding sites and ligands, which can effectively provide new ideas for ligand research and promote drug research.

ObjectiveTo investigate the identification of kidney Yang deficiency syndrome of patients with osteoporosis（OP）， and to form the clinical syndrome identification rules of traditional Chinese medicine（TCM）. MethodBasic information， etiology， clinical symptoms and other characteristics of 982 OP patients were included， and statistical tests were used to screen the variables associated with kidney Yang deficiency syndrome. Taking the decision tree as the base model， bootstrap aggregation algorithm（Bagging algorithm） was utilized to establish the classification model of kidney Yang deficiency syndrome in OP， generating numerous rules and removing redundancy. Combining least absolute shrinkage and selection operator（LASSO） regression to screen key rules and integrate them to construct an identification model， achieving the identification of kidney Yang deficiency syndrome in OP patients. ResultEighteen key identification rules were screened out， and of these， where 11 rules with regression coefficients>0 correlated positively with the kidney Yang deficiency syndrome， the rule with the highest coefficient was chilliness（present）&feverish sensation over the palm and sole（absent）. The other 7 rules with regression coefficients<0 correlated negatively with the syndrome， the rule with the lowest coefficient was reddish tongue（present）&diarrhea（absent）&deficiency of endowment（absent）. According to the regression coefficients of each key rule， variables with importance>0.2 were ranked as chilliness， reddish tongue， feverish sensation over the palm and sole， cold limbs， clear urine， diarrhea， deficiency of endowment， prolonged illness. The results of the partial dependence analysis of the identification model showed that compared to OP patients without chilliness， those with chilliness（present） had a 0.266 8 higher probability of being identified as having kidney Yang deficiency syndrome， indicating that this variable had the highest impact on identification of the syndrome. Similarly， compared to OP patients without reddish tongue， those with reddish tongue had a 0.141 9 lower probability of being identified as having kidney Yang deficiency syndrome， indicating that this variable had the highest impact on identifying non-kidney Yang deficiency syndrome. The accuracy， sensitivity， specificity and area under receiver operating characteristic curve（AUC） of the established kidney Yang deficiency syndrome identification model in the test set were 0.865 9， 0.853 7， 0.872 0 and 0.931 5， respectively. ConclusionA precise identification model of OP kidney Yang deficiency syndrome is conducted basing on the rule ensemble method of Bagging combining LASSO regression， and the screened key rules can explain the identification process of kidney Yang deficiency syndrome. In this research， according to the regression coefficients of rules， the importance and partial dependence of variables， combined with the thinking of TCM， the influence of patient characteristics on the identification of syndromes is described， so as to reveal the primary and secondary syndromes of identification and assist the clinical identification of kidney Yang deficiency syndrome.