The pathophysiological process of ischemic stroke (IS) is highly complex. Current clinical treatments are limited by a narrow therapeutic time window and are inadequate for improving residual neurological dysfunction. Therefore, animal models have become essential tools for exploring the pathological mechanisms of this disease from both traditional Chinese medicine (TCM) and Western medicine perspectives,as well as for evaluating innovative therapeutic strategies. This review systematically outlines existing IS modeling methods and cutting-edge advances. It comparatively integrates the multi-layered pathogeneses in Western medicine, including excitotoxicity, oxidative stress, inflammatory responses, blood-brain barrier injury, ferroptosis, and PANoptosis, with the core TCM pathogenesis characterized by disorders of Qi and blood and functional imbalance caused by "wind, fire/heat, phlegm, blood stasis, and deficiency." Furthermore, this paper categorizes and compares the specific modeling techniques, evaluation indicators, and respective advantages and limitations of focal cerebral ischemia models, global cerebral ischemia models, and TCM disease-syndrome combined models, such as the Qi deficiency and blood stasis syndrome. Literature review suggests that, by exploring emerging cell death mechanisms like PANoptosis and introducing environmental stress or dietary interventions on the basis of ischemic modeling, specific TCM syndromes associated with IS can be preliminarily screened out and replicated. It provides a feasible approach for objectively elucidating the biological basis of TCM interventions involving multiple targets and pathways. Given that traditional single-disease models fail to fully capture the complexity and individual heterogeneity of the cerebral network microenvironment in clinical patients, future research on IS animal models should focus on the deep integration of TCM and Western medicine in pathogenesis. By leveraging multidisciplinary technologies, such as gene editing, high-resolution in vivo imaging, artificial intelligence-driven multi-omics analysis, and brain organoids, researchers can construct high-biomimetic, multi-dimensional models that closely mirror clinical scenarios, thereby effectively improving the success rate of translating innovative IS therapies from basic research to clinical application.

The mental health management of laboratory animals is a critical factor in ensuring the reliability of scientific research data. However, due to the subtle nature of mental state alterations and the limitations of current assessment methods, the mental health of laboratory animals is often overlooked by researchers. Therefore, there is an urgent need to explore a new, objective, simple, and practical method for evaluating mental health. Stress, as a primary factor inducing alterations in the mental state of animals, can influence experimental results across multiple research fields through the neuroendocrine-immune network. This paper first elucidates the necessity of mental health management in laboratory animals from three perspectives: factors contributing to stress, neural mechanisms of stress, and research areas affected by stress. It highlights that excluding animals with abnormal mental states before experiments can enhance the efficiency and reproducibility of biomedical studies. Second, this paper briefly summarizes existing methods for assessing the health of laboratory animals, pointing out that approaches such as behavioral tests and metabolomics have many limitations in evaluating stress responses. Existing methods struggle to meet the demand for simple, objective, and non-invasive assessment methods in animal management. Therefore, this paper focuses on hair, a biological sample with the advantages of cumulative information and non-invasive collection, and systematically describes the theoretical basis and technological advances in using hair characteristics as indicators of stress responses from three perspectives: hair traits, the levels of substances in hair, and artificial intelligence (AI). It proposes and supports an innovative technical pathway that combines hair traits with AI-based image analysis, with the aim of offering an improved solution for non-invasive and objective stress assessment, while providing theoretical support for improving the health management system of laboratory animals.

ObjectiveThis study aimed to investigate the mechanism by which Luoshi Neiyi prescription treats endometriosis （EMs） through regulating ferroptosis， and to screen key metabolites and analyze their association with ferroptosis. MethodsClinical samples of normal endometrium from patients without EMs and eutopic and ectopic endometrium from EMs patients （10 cases each） were collected and divided into control group， eutopic group， and EMs group. Hematoxylin-eosin （HE） staining was performed to observe ectopic lesions of EMs. Immunohistochemistry was used to detect the expression of solute carrier family 7 member 11 （SLC7A11） and glutathione peroxidase 4 （GPX4）. Enzyme-linked immunosorbent assay （ELISA） was adopted to determine the levels of malondialdehyde （MDA）， ferrous ion （Fe²⁺）， GPX4 and glutathione （GSH） in endometrial tissues， as well as serum levels of Fe²⁺， GPX4 and GSH. Real-time quantitative polymerase chain reaction （Real-time PCR） was used to detect the mRNA expression of SLC7A11， GPX4， transferrin receptor （TFR） and ferritin heavy chain 1 （FTH1）. In the in vitro experiment， primary stromal cells were isolated from ectopic lesions of EMs patients. Cell counting kit-8 （CCK-8） was used to determine the optimal concentration of drug-containing serum for intervention. The level of reactive oxygen species （ROS） was measured， and Real-time PCR was applied to detect ferroptosis-related indicators. In the animal experiments， an EM rat model was established， and the rats were randomly assigned to the sham operation group， EMs group， low-dose Luoshi Neiyi Formula group （7.87 g·kg^-1）， high-dose Luoshi Neiyi prescription group （15.74 g·kg^-1）， and danazol group （42 mg·kg^-1）. Untargeted metabolomics detection and pathway enrichment analysis were conducted on serum samples from patients and rats. Spearman correlation analysis was performed to assess the relationship between differential metabolites and ferroptosis indicators. The correlations between differential metabolites in patient endometrium and serum and key ferroptosis indicators （GPX4， Fe²⁺， MDA， GSH） as well as ferroptosis-related mRNAs （GPX4， SLC7A11， FTH1） were analyzed， and correlation heatmaps were generated accordingly. ResultsCompared with normal eutopic endometrium， ectopic lesions in EMs patients showed glandular disorganization and stromal fibrosis. In ectopic endometrium， the contents of MDA， ROS， and Fe²⁺ decreased， while GPX4 level increased， and the mRNA expression of SLC7A11 and GPX4 was upregulated （P<0.05， P<0.01）. In serum， the levels of GPX4 and Fe²⁺ were elevated， whereas the GSH level declined， suggesting abnormalities in ferroptosis-related pathways in ectopic lesions （P<0.05， P<0.01）. After intervention with Luoshi Neiyi prescription-containing serum， the intracellular ROS level in ectopic endometrial stromal cells was elevated， the mRNA expression of SLC7A11 and GPX4 was downregulated， and TFR mRNA expression was upregulated （P<0.05， P<0.01）. Metabolomics analysis revealed 1104 and 198 differential metabolites in EMs patients and EMs rats， respectively， compared with their corresponding control groups， and both low-dose and high-dose Luoshi Neiyi prescription were found to regulate this metabolic disturbance， with the core regulatory pathways mainly involving arginine and proline metabolism. Correlation analysis showed that the glycerophospholipids including PI（16∶0/17∶0） and PI［18∶2（9Z，12Z）］ were negatively correlated with GPX4 and positively correlated with MDA， while 17α-hydroxyprogesterone was positively correlated with GPX4， SLC7A11， and FTH1 q<0.05）. ConclusionLuoshi Neiyi prescription may systematically ameliorate disease-associated metabolic dysregulation via modulation of the serum arginine and proline metabolism pathway， and may regulate ferroptosis in ectopic lesions through a mechanism potentially linked to the serum glycerophospholipid and steroid metabolism pathways. Collectively， these findings provide experimental evidence for the clinical application of Luoshi Neiyi prescription.

ObjectiveThis study aimed to investigate the mechanism by which Luoshi Neiyi prescription treats endometriosis （EMs） through regulating ferroptosis， and to screen key metabolites and analyze their association with ferroptosis. MethodsClinical samples of normal endometrium from patients without EMs and eutopic and ectopic endometrium from EMs patients （10 cases each） were collected and divided into control group， eutopic group， and EMs group. Hematoxylin-eosin （HE） staining was performed to observe ectopic lesions of EMs. Immunohistochemistry was used to detect the expression of solute carrier family 7 member 11 （SLC7A11） and glutathione peroxidase 4 （GPX4）. Enzyme-linked immunosorbent assay （ELISA） was adopted to determine the levels of malondialdehyde （MDA）， ferrous ion （Fe²⁺）， GPX4 and glutathione （GSH） in endometrial tissues， as well as serum levels of Fe²⁺， GPX4 and GSH. Real-time quantitative polymerase chain reaction （Real-time PCR） was used to detect the mRNA expression of SLC7A11， GPX4， transferrin receptor （TFR） and ferritin heavy chain 1 （FTH1）. In the in vitro experiment， primary stromal cells were isolated from ectopic lesions of EMs patients. Cell counting kit-8 （CCK-8） was used to determine the optimal concentration of drug-containing serum for intervention. The level of reactive oxygen species （ROS） was measured， and Real-time PCR was applied to detect ferroptosis-related indicators. In the animal experiments， an EM rat model was established， and the rats were randomly assigned to the sham operation group， EMs group， low-dose Luoshi Neiyi Formula group （7.87 g·kg^-1）， high-dose Luoshi Neiyi prescription group （15.74 g·kg^-1）， and danazol group （42 mg·kg^-1）. Untargeted metabolomics detection and pathway enrichment analysis were conducted on serum samples from patients and rats. Spearman correlation analysis was performed to assess the relationship between differential metabolites and ferroptosis indicators. The correlations between differential metabolites in patient endometrium and serum and key ferroptosis indicators （GPX4， Fe²⁺， MDA， GSH） as well as ferroptosis-related mRNAs （GPX4， SLC7A11， FTH1） were analyzed， and correlation heatmaps were generated accordingly. ResultsCompared with normal eutopic endometrium， ectopic lesions in EMs patients showed glandular disorganization and stromal fibrosis. In ectopic endometrium， the contents of MDA， ROS， and Fe²⁺ decreased， while GPX4 level increased， and the mRNA expression of SLC7A11 and GPX4 was upregulated （P<0.05， P<0.01）. In serum， the levels of GPX4 and Fe²⁺ were elevated， whereas the GSH level declined， suggesting abnormalities in ferroptosis-related pathways in ectopic lesions （P<0.05， P<0.01）. After intervention with Luoshi Neiyi prescription-containing serum， the intracellular ROS level in ectopic endometrial stromal cells was elevated， the mRNA expression of SLC7A11 and GPX4 was downregulated， and TFR mRNA expression was upregulated （P<0.05， P<0.01）. Metabolomics analysis revealed 1104 and 198 differential metabolites in EMs patients and EMs rats， respectively， compared with their corresponding control groups， and both low-dose and high-dose Luoshi Neiyi prescription were found to regulate this metabolic disturbance， with the core regulatory pathways mainly involving arginine and proline metabolism. Correlation analysis showed that the glycerophospholipids including PI（16∶0/17∶0） and PI［18∶2（9Z，12Z）］ were negatively correlated with GPX4 and positively correlated with MDA， while 17α-hydroxyprogesterone was positively correlated with GPX4， SLC7A11， and FTH1 q<0.05）. ConclusionLuoshi Neiyi prescription may systematically ameliorate disease-associated metabolic dysregulation via modulation of the serum arginine and proline metabolism pathway， and may regulate ferroptosis in ectopic lesions through a mechanism potentially linked to the serum glycerophospholipid and steroid metabolism pathways. Collectively， these findings provide experimental evidence for the clinical application of Luoshi Neiyi prescription.

ObjectiveTo explore the current situation of forensic ethics practice and education by designing a questionnaire on forensic ethics， with a view to exploring the path of forensic ethics education construction. MethodsA total of 667 valid questionnaires were collected using the online survey method， basically covering various regions across the country and all sub-specialties of forensic medicine. Descriptive analysis was used to analyze the relevant data. ResultsMost practitioners had relevant ethical reflections in the process of forensic practice. 69.12% of the respondents indicated that they had studied the relevant rules， but approximately half stated that there were no corresponding ethical norms or standard operating manuals. The specific behaviors violating ethics in different units were diverse. 23.04% of the respondents reported that they had encountered unethical behaviors， but only 4.9% of them reported such violations. In terms of forensic ethics education， 87.75% of the respondents believed that there were issues with the current model of forensic ethics education. Meanwhile， the respondents showed a high degree of recognition for receiving forensic ethics education， with 84.15% of respondents expressing willingness to participate in relevant courses. More than half of respondents were willing to participate in forensic ethics education during undergraduate studies， new employee training， and regular post-employment training. ConclusionCurrently， there is a problem of ethical neglect in forensic work in China. Combining ethics courses with professional courses at the practitioner training stage and providing regular training at the practice stage are effective measures to popularize forensic ethics knowledge， enhance ethical awareness， and improve the quality of practice.

[Objective] : To explore the clinical characteristics and methods for syndrome differentiation prediction, as well as to construct a predictive model for Qi deficiency and blood stasis syndrome in patients with acute ischemic stroke (AIS). [Methods] : This study employed a retrospective case-control design to analyze patients with AIS who received inpatient treatment at the Neurology Department of The First Hospital of Hunan University of Chinese Medicine from January 1, 2013 to December 31, 2022. AIS patients meeting the diagnostic criteria for Qi deficiency and blood stasis syndrome were stratified into case group, while those without Qi deficiency and blood stasis syndrome were stratified into control group. The demographic characteristics (age and gender), clinical parameters [time from onset to admission, National Institutes of Health Stroke Scale (NIHSS) score, and blood pressure], past medical history, traditional Chinese medicine (TCM) diagnostic characteristics (tongue and pulse), neurological symptoms and signs, imaging findings [magnetic resonance imaging-diffusion weighted imaging (MRI-DWI)], and biochemical indicators of the two groups were collected and compared. The indicators with statistical difference (P < 0.05) in univariate analysis were included in multivariate logistic regression analysis to evaluate their predictive value for the diagnosis of Qi deficiency and blood stasis syndrome, and the predictive model was constructed by receiver operating characteristic (ROC) curve analysis. [Results] : The study included 1 035 AIS patients, with 404 cases in case group and 631 cases in control group. Compared with control group, patients in case group were significantly older, had extended onset-to-admission time, lower diastolic blood pressure, and lower NIHSS scores (P < 0.05). Case group showed lower incidence of hypertension history (P < 0.05). Regarding tongue and pulse characteristics, pale and dark tongue colors, white tongue coating, fine pulse, astringent pulse, and sinking pulse were more common in case group. Imaging examinations demonstrated higher proportions of centrum semiovale infarction, cerebral atrophy, and vertebral artery stenosis in case group (P < 0.05). Among biochemical indicators, case group showed higher proportions of elevated fasting blood glucose and glycated hemoglobin (HbA1c), while lower proportions of elevated white blood cell count, reduced hemoglobin, and reduced high-density lipoprotein cholesterol (HDL-C) (P < 0.05). Multivariate logistic regression analysis identified significant predictors for Qi deficiency and blood stasis syndrome including: fine pulse [odds ratio (OR) = 4.38], astringent pulse (OR = 3.67), superficial sensory abnormalities (OR = 1.86), centrum semiovale infarction (OR = 1.57), cerebral atrophy (OR = 1.55), vertebral artery stenosis (OR = 1.62), and elevated HbA1c (OR = 3.52). The ROC curve analysis of the comprehensive prediction model yielded an area under the curve (AUC) of 0.878 [95% confidence interval (CI) = 0.855 – 0.900]. [Conclusion] This study finds out that Qi deficiency and blood stasis syndrome represents one of the primary types of AIS. Fine pulse, astringent pulse, superficial sensory abnormalities, centrum semiovale infarction, cerebral atrophy, vertebral artery stenosis, elevated blood glucose, elevated HbA1c, pale and dark tongue colors, and white tongue coating are key objective diagnostic indicators for the syndrome differentiation of AIS with Qi deficiency and blood stasis syndrome. Based on these indicators, a syndrome differentiation prediction model has been developed, offering a more objective basis for clinical diagnosis, and help to rapidly identify this syndrome in clinical practice and reduce misdiagnosis and missed diagnosis.

ObjectiveTo observe the clinical efficacy and safety of Tangning Tongluo tablets in the treatment of nonproliferative diabetic retinopathy （DR）. MethodsFourteen research centers participated in this study， which spanned a time interval from September 2021 to May 2023. A total of 240 patients with nonproliferative DR were included and randomly assigned into an observation group （120 cases） and a control group （120 cases）. The observation group was treated with Tangning Tongluo tablets， and the control group with calcium dobesilate capsules. Both groups were treated for 24 consecutive weeks. The vision， DR progression rate， retinal microhemangioma， hemorrhage area， exudation area， glycosylated hemoglobin （HbA1c） level， and TCM syndrome score were assessed before and after treatment， and the safety was observed. ResultsThe vision changed in both groups after treatment （P<0.05）， and the observation group showed higher best corrected visual acuity （BCVA） than the control group （P<0.05）. The DR progression was slow with similar rates in the two groups. The fundus hemorrhage area and exudation area did not change significantly after treatment in both groups， while the observation group outperformed the control group in reducing the fundus hemorrhage area and exudation area. There was no significant difference in the number of microhemangiomas between the two groups before treatment. After treatment， the number of microhemangiomas decreased in both the observation group （Z=-1.437， P<0.05） and the control group （Z=-2.238， P<0.05）， and it showed no significant difference between the two groups. As the treatment time prolonged， the number of microhemangiomas gradually decreased in both groups. There was no significant difference in the HbA1c level between the two groups before treatment. After treatment， the decline in the HbA1c level showed no significant difference between the two groups. The TCM syndrome score did not have a statistically significant difference between the two groups before treatment. After treatment， neither the TCM syndrome score nor the response rate had significant difference between the two groups. With the extension of the treatment time， both groups showed amelioration of TCM syndrome compared with the baseline. ConclusionTangning Tongluo tablets are safe and effective in the treatment of nonproliferative DR， being capable of improving vision and reducing hemorrhage and exudation in the fundus.

ObjectiveBased on ultra performance liquid chromatography-quadrupole-electrostatic field orbital trap high-resolution mass spectrometry（UPLC-Q-Orbitrap-MS）， to identify the in vivo and in vitro chemical components of total phenolic acids in Gei Herba（TPAGH）， and to clarify the pharmacological effects and potential mechanisms of the effective part in promoting acute wound healing and inhibiting scar formation. MethodsUPLC-Q-Orbitrap-MS was used to identify the chemical components of TPAGH and ingredients absorbed in vivo after topical administration. A total of 120 ICR mice were randomly divided into the model group， recombinant human epidermal growth factor（rhEGF） group（4 mg·kg^-1）， and low， medium， and high dose groups of TPAGH（3.5， 7， 14 mg·kg^-1）， with 24 mice in each group. A full-thickness skin excision model was constructed， and each administration group was coated with the drug at the wound site， and the model group was treated with an equal volume of normal saline， the treatment was continued for 30 days， during which 8 mice from each group were sacrificed on days 6， 12， and 30. The healing of the wounds in the mice was observed， and histopathological changes in the skin tissues were dynamically observed by hematoxylin-eosin（HE）， Masson， and Sirius red staining， and enzyme-linked immunosorbent assay（ELISA） was used to dynamically measure the contents of interleukin-6（IL-6）， tumor necrosis factor-α（TNF-α）， vascular endothelial growth factor A（VEGFA）， matrix metalloproteinase（MMP）-3 and MMP-9 in skin tissues. Network pharmacology was used to predict the targets related to the promotion of acute wound healing and the inhibition of scar formation by TPAGH， and molecular docking of key components and targets was performed. Gene Ontology（GO） biological process analysis and Kyoto Encyclopedia of Genes and Genomes（KEGG） pathway enrichment analysis were carried out for the related targets， so as to construct a network diagram of herbal material-compound-target-pathway-pharmacological effect-disease for further exploring its potential mechanisms. ResultsA total of 146 compounds were identified in TPAGH， including 28 phenylpropanoids， 31 tannins， 23 triterpenes， 49 flavonoids， and 15 others， and 16 prototype components were found in the serum of mice. Pharmacodynamic results showed that， compared with the model group， the TPAGH groups showed a significant increase in relative wound healing rate and relative scar inhibition rate（P<0.05）， and the number of new capillaries， number of fibroblasts， number of new skin appendages， epidermal regeneration rate， collagen deposition ratio， and Ⅲ/Ⅰ collagen ratio in the tissue were significantly improved（P<0.05， 0.01）， the levels of IL-6， TNF-α， MMP-3 and MMP-9 in the skin tissues were reduced to different degrees， while the level of VEGFA was increased. Network pharmacology analysis screened 10 core targets， including tumor protein 53（TP53）， sarcoma receptor coactivator（SRC）， protein kinase B（Akt）1， signal transducer and activator of transcription 3（STAT3）， epidermal growth factor receptor（EGFR） and so on， participating in 75 signaling pathways such as advanced glycation end-products（AGE）-receptor for AGE（AGE/RAGE） signaling pathway， phosphatidylinositol 3-kinase（PI3K）/Akt signaling pathway， mitogen-activated protein kinase（MAPK） signaling pathway. Molecular docking confirmed that the key components genistein， geraniin， and casuariin had good binding ability to TP53， SRC， Akt1， STAT3 and EGFR. ConclusionThis study comprehensively reflects the chemical composition of TPAGH and the absorbed components after topical administration through UPLC-Q-Orbitrap-MS. TPAGH significantly regulates key indicators of skin healing and tissue reconstruction， thereby clarifying its role in promoting acute wound healing and inhibiting scar formation. By combining in vitro and in vivo component identification with network pharmacology， the study explores how key components may bind to targets such as TP53， Akt1 and EGFR， exerting therapeutic effects through related pathways such as immune inflammation and vascular regeneration.

[Objective] To investigate the molecular prevalence and genotype of human parvovirus B19(B19) among blood donors in Lanzhou, and provide data support for monitoring the positive rate of B19 DNA in local blood donors. [Methods] A total of 7 644 blood donor samples collected from January to September 2022 were randomly screened using real-time fluorescent PCR, resulting in 23 samples testing positive for B19 DNA. The characteristics of the B19 DNA reactive donors including gender, age, blood donation recruitment and promotion mode, and donation frequency were analyzed using SPSS 22.0. Additionally, the VP1 gene fragment of B19 DNA reactive samples was sequenced and an evolutionary tree was constructed by the N-J method. [Results] The results showed that the positive rate of B19 DNA in Lanzhou was 0.30%, and the positive population mainly consisted of female individuals aged 18-30 years old who were first-time blood donors; furthermore, genotype 1a was identified as predominant. [Conclusion] The positive rate of B19 DNA is low among blood donors in Lanzhou, with genotype 1a being predominant. It is recommended to periodically monitor the B19 prevalence in blood donors and enhance prevention and control measures, thus improving blood quality and safety.

Artificial intelligence (AI) researchers and cheminformatics specialists strive to identify effective drug precursors while optimizing costs and accelerating development processes. Digital molecular representation plays a crucial role in achieving this objective by making molecules machine-readable, thereby enhancing the accuracy of molecular prediction tasks and facilitating evidence-based decision making. This study presents a comprehensive review of small molecular representations and AI-driven drug discovery downstream tasks utilizing these representations. The research methodology begins with the compilation of small molecule databases, followed by an analysis of fundamental molecular representations and the models that learn these representations from initial forms, capturing patterns and salient features across extensive chemical spaces. The study then examines various drug discovery downstream tasks, including drug-target interaction (DTI) prediction, drug-target affinity (DTA) prediction, drug property (DP) prediction, and drug generation, all based on learned representations. The analysis concludes by highlighting challenges and opportunities associated with machine learning (ML) methods for molecular representation and improving downstream task performance. Additionally, the representation of small molecules and AI-based downstream tasks demonstrates significant potential in identifying traditional Chinese medicine (TCM) medicinal substances and facilitating TCM target discovery.
Artificial Intelligence ; Drug Discovery/methods* ; Humans ; Machine Learning ; Medicine, Chinese Traditional ; Small Molecule Libraries/chemistry*