ObjectiveTo investigate the migration and distribution characteristics of chemical constituents in blood and hippocampal tissues before and after vinegar processing of Citri Reticulatae Pericarpium Viride（CRPV）， and to explore the potential material basis and mechanisms underlying their regulatory effects on emotional disorders by comparing the effects of raw and vinegar-processed products of CRPV. MethodsUltra-performance liquid chromatography-quadrupole-time-of-flight mass spectrometry（UPLC-Q-TOF-MS/MS） was employed to characterize and identify the chemical constituents of raw and vinegar-processed products of CRPV extracts， as well as their migrating components in blood and hippocampal tissues after oral administration. Reference standards， databases， and relevant literature were utilized for compound annotation， with data processing performed using PeakView 1.2 software. Seventy male C57BL/6 mice were randomly divided into seven groups， including the blank group， model group， diazepam group（2.5 mg·kg^-1）， raw CRPV low/high dose groups（0.6， 1.2 g·kg^-1）， and vinegar-processed CRPV low/high dose groups（0.6， 1.2 g·kg^-1）， with 10 mice per group. Except for the blank group， all other groups underwent chronic restraint stress（2 h·d^-1） for 20 d. Each drug-treated group received oral administration at the predetermined dose starting 10 d after modeling， with a total treatment duration of 10 d. Following model-based drug administration， mice underwent open-field， forced swimming， and elevated plus maze tests. After anesthesia with isoflurane， whole brains were collected from each group of mice， and hippocampi were dissected. Reactive oxygen species（ROS） level in hippocampal tissues was quantified by enzyme-linked immunosorbent assay（ELISA）. Hematoxylin-eosin（HE） staining was used to observe hippocampal tissue morphology. Immunofluorescence was performed to detect neuronal nuclei（NeuN） and peroxisome proliferator-activated receptor alpha（PPARα） expressions in hippocampal tissue. Then， pharmacodynamic evaluations were conducted to assess the effects of raw and vinegar-processed CRPV on mood disorders， exploring the potential mechanisms. ResultsVinegar processing caused significant changes in the chemical composition of CRPV， with 18 components showing increased relative content and 35 components showing decreased relative content. The primary changes occurred in flavonoid compounds， including 20 flavonoids， 20 flavonoid glycosides， 3 triterpenes， 3 phenolic acids， 1 alkaloid， and 6 other compounds. Twenty-one components were detected in blood（15 methoxyflavones， 4 flavonoid glycosides， and 2 phenolic acids）， with 17 shared between raw and vinegar-processed CRPV. Seven components reached hippocampal tissues（all common to both forms）. In regulating emotional disorders， Vinegar-processed CRPV exhibited superior antidepressant-like effects compared to raw products. HE staining revealed that both treatments improved hippocampal neuronal morphology， particularly in the damaged CA1 and CA3 regions. Immunofluorescence and ELISA analyses demonstrated that both raw and vinegar-processed CRPV significantly modulated NeuN and PPARα expressions in hippocampal tissue while alleviating oxidative stress induced by excessive ROS（P<0.05）. ConclusionThe chemical composition of CRPV undergoes changes after vinegar processing， but the migrating components in blood and hippocampus are primarily methoxyflavonoids. These components may serve as the potential material basis for activating the PPARα pathway， thereby negatively regulating ROS generation in the hippocampus， reducing oxidative stress， and promoting the development of NeuN-positive neurons. These findings provide experimental evidence for enhancing quality standards， pharmacodynamic material research， and active drug development of raw and vinegar-processed CRPV.

Objective To present a named entity recognition method referred to as BioBERT-Att-BiLSTM-CRF for eligibility criteria based on the BioBERT pretrained model.The method can automatically extract relevant information from clinical trials and provide assistance in efficiently formulating eligibility criteria.Methods Based on the UMLS medical semantic network and expert-defined rules,the study established medical entity annotation rules and constructed a named entity recognition corpus to clarify the entity recognition task.BioBERT-Att-BiLSTM-CRF converted the text into BioBERT vectors and inputted them into a bidirectional long short-term memory network to capture contextual semantic features.Meanwhile,attention mechanisms were applied to extract key features,and a conditional random field was used for decoding and outputting the optimal label sequence.Results BioBERT-Att-BiLSTM-CRF outperformed other baseline models on the eligibility criteria named entity recognition dataset.Conclusion BioBERT-Att-BiLSTM-CRF can efficiently extract eligibility criteria-related information from clinical trials,thereby enhancing the scientific validity of clinical trial registration data and providing assistance in the formulation of eligibility criteria for clinical trials.

With the booming development of medical information technology and computer science, the medical services industry is gradually transiting from information technology to intelligence. The medical knowledge graph plays an important role in intelligent medical applications such as knowledge questions and answers and intelligent diagnosis, and is a key technology for promoting wise medical care and the basis for intelligent management of medical information. In order to fully exploit the great potential of knowledge graphs in the medical field, this paper focuses on five aspects: inter-drug relationship discovery, assisted diagnosis, personalized recommendation, decision support and intelligent prediction. The latest research progress on medical knowledge graphs is introduced, and relevant suggestions are made in light of the current challenges and problems faced by medical knowledge graphs to provide reference for promoting the wide application of medical knowledge graphs.
Pattern Recognition, Automated ; Medical Informatics

Objective To discuss the specific role of association rules in the compatibility of herbs and the relationship between herbs and symptoms by analyzing ancient analogous prescriptions Zhizichi Decoction with SQL Server software.Methods The prescriptions which contain Gardenia and Semen Sojae Preparatum were searched in the database of “Ancient Prescriptions for Epidemic Disease”, and they were imported to software with the standardized data of their symptoms and ingredients, then the proper association rules were found. The laws between parameter setting and rule generation were searched through parameter adjustment.Results Many laws of the drug compatibility and relationship between herbs and symptoms were obtained effectively in data mining by adjusting the parameters:The support setting was good for finding common used drug compatibility, and the confidence was good for finding specific drug compatibility and relationship between herbs and symptoms;the item set which had high frequency, sometimes made the rule’s importance low.Conclusion The laws of compatibility of herbs and the relationship between herbs and symptoms for data mining of analogous prescriptions are discovered by analyzing the support, confidence and importance of the association-rules and the clinical magnificence between symptoms and herbs.