Stroke is one of the leading causes of disability and mortality worldwide. Research into its mechanisms and the development of therapeutic strategies heavily rely on animal models that accurately replicate the pathological features of human disease. An ideal animal model for stroke should not only reproduce the neurological deficits and pathological changes observed in clinical patients but also demonstrate good reproducibility and translational value. This review focuses on the preparation and evaluation methods of ischemic stroke animal models. Firstly, it elaborates on the selection criteria, advantages, and disadvantages of experimental animals, including rodents (rats, mice) and non-rodents (non-human primates, miniature pigs, rabbits, zebrafish). Secondly, it provides a detailed overview of the modeling principles, key procedures, and application scopes for ischemic stroke models and hemorrhagic stroke models. Furthermore, the review summarizes advances in the applications of emerging technologies—including gene editing [e.g., clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated protein 9 (Cas9) gene editing], multimodal imaging (e.g., two-photon microscopy, photoacoustic imaging), artificial intelligence, optogenetics, 3D bioprinting, organoid models, and multi-omics–in model optimization, precise assessment, and mechanistic investigation. Finally, based on a systematic analysis of relevant domestic and international literature from 2019 to 2024, this review discusses model selection strategies based on research objectives, a multidimensional evaluation system encompassing behavioral, imaging, and molecular pathological assessments, and envisions future directions involving technological integration to achieve model precision and individualization. This article aims to provide a comprehensive methodological reference to help researchers select appropriate animal models of stroke according to specific scientific questions.

Objective This study used The Cancer Genome Atlas (TCGA) database to investigate the methylation levels of PCDHGB7 in lung adenocarcinoma tissues and analyze its association with clinical pathological features of lung adenocarcinoma, and its prognostic predictive value. Methods Methylation data of PCDHGB7 from 473 lung adenocarcinoma tissues and 32 normal tissues in the TCGA database were derived and analyzed to assess between-group variance and determine the correlation of methylation levels with clinical pathological features and overall survival. Results PCDHGB7 exhibited significantly higher methylation levels in lung adenocarcinoma tissues than in normal tissues (P<0.001), demonstrating a strong discriminative ability for lung adenocarcinoma (AUC=0.926, P<0.001). The methylation level was strongly associated with gender (P=0.047) and T stage (P=0.013). The critical prognostic sites of PCDHGB7 were identified through univariate Cox regression analysis. We found significant differences in overall survival between patient groups with low or high methylation levels (P=0.0099). Conclusion PCDHGB7 shows significantly elevated methylation in lung adenocarcinoma, which correlates with tumor malignancy and possesses certain prognostic predictive potential.

ObjectiveTo investigate the preventive effect and mechanism of Dendrobium officinale （DO） on non-alcoholic fatty liver disease （NAFLD） by network pharmacology and animal experiments. MethodsDO components in blood after administration were identified and analyzed using ultra-performance liquid chromatography-quadrupole-electrostatic field orbitrap high-resolution mass spectrometry （UPLC-QE-HF-MS/MS）. Network pharmacology and molecular docking methods were employed to obtain active ingredients and potential targets of DO for NAFLD control. High-fat feeds were used to replicate the NAFLD rat model. Biochemical kits were used for detecting the expression levels of blood lipids， hepatic lipids， and liver functions of rats. Hematoxylin-eosin （HE） staining and oil red O staining were employed to observe pathological changes in rat liver， and real-time fluorescence quantitative PCR （Real-time PCR） assay was performed to validate potential targets obtained from the network pharmacology analysis. ResultsA total of 13 DO components were identified in blood， including berberine， dihydrosanguinarine， and oxypeucedanin. A total of 14 potential targets were screened through network pharmacology， including Forkhead box protein O1 （FoxO1）， epidermal growth factor receptor （EGFR）， and insulin-like growth factor 1 （IGF-1R）， involving pathways such as the advanced glycation end product （AGE）/receptor for AGE （RAGE） signaling pathway， blood lipids and atherosclerosis， insulin resistance， and FoxO signaling. The results of animal experiments showed that the NAFLD rat model was successfully replicated. After the preventive treatment with DO for NAFLD rats， the indexes of blood lipids， hepatic lipids， and liver function were normalized； lipid deposition and lesions in the liver were significantly improved； the expression level of FoxO1 mRNA in the liver was significantly reduced （P<0.05）， and the mRNA expression levels of phosphatidylinositide 3-kinases （PI3K）， protein kinase B （Akt）， EGFR， and IGF-1R were significantly increased （P<0.05）. ConclusionDO has a preventive effect on NAFLD rats， and the mechanism of action may be related to the modulation of IGF1R and EGFR targets and activation of the PI3K/Akt/FoxO1 signaling pathway.

ObjectiveTo construct a group-based trajectory model (GBTM) for early medication adherence check-in, and to analyze the relationship between different trajectories and treatment outcomes in tuberculosis patients using data that were generated from smart tools for monitoring their medication adherence and check-in. MethodsFrom October 1, 2022 to September 30, 2023, a total of 163 pulmonary tuberculosis patients diagnosed in Fengxian District were selected as the study subjects. The GBTM was utilized to analyze the weekly active check-in trajectories of the subjects during the first 4 weeks and establish different trajectory groups. The χ² tests were employed to compare the differences between groups and logistic regression analysis was conducted to explore the relationship between different trajectory groups and treatment outcomes. ResultsA total of four groups were generated by GBTM analyses, of which a low level of punch card was maintained in group A, 6% of the drug users increased rapidly from a low level in group B, 17% of drug users increased gradually from a low level in group C, and 18% of drug users maintained a high level of punch card in group D. The trajectory group was divided into two groups according to homogeneity, namely the low level medication punch card group (group A) and the high level medication punch card group (group B, group C, and group D). The results of multivariate logistic regression analyses revealed that low-level medication check-in (OR=3.250, 95%CI: 1.089‒9.696), increasing age (OR=1.030, 95%CI: 1.004‒1.056), and not undergoing sputum examination at the end of the fifth month (OR=2.746, 95%CI: 1.090‒7.009) were significantly associated with poor treatment outcomes. ConclusionThe medication check-in trajectory of pulmonary tuberculosis patients within the first 4 weeks is correlated with adverse outcomes, or namely consistent low-level medication adherence check-ins are associated with poor treatment outcomes, while high-level medication adherence check-ins are associated with a lower incidence of adverse outcomes.

Objective: To explore the efficacy of pelvic floor optimization training of Yun-type with the aid of myoelectric biofeedback in the treatment of mild to moderate female stress urinary incontinence (SUI). Methods: Female SUI patients treated in our hospital during Jan.and Oct.2024 were included as the research subjects.They were randomly divided into the control group (n=47) and observation group (n=48) by random number method.The control group received conventional Yun-type pelvic floor optimization training，while the observation group received Yun-type pelvic floor optimization training assisted with myoelectric biofeedback.The total treatment course lasted for 12 weeks.The clinical efficacy，as well as the changes in international consultation on incontinence questionnaire for symptoms and impact (ICI-Q-SF)，incontinence quality of life (I-QoL)，female sexual function index (FSFI)，and pelvic floor electromyographic values before and after treatment were compared. Results: The total effective rate of the observation group was 93.6%，which was significantly higher than that of the control group (79.2%，P<0.05).After 12 weeks of treatment，the ICI-Q-SF [(6.12±1.11) vs. (6.97±1.24)]，I-QoL [(85.05±4.51) vs. (82.14±4.60)]，and FSFI [(30.01±4.10) vs. (26.32±3.32)] scores of the observation group were significantly better than those of the control group (P<0.05).After 12 weeks of treatment，the myoelectric values of the pelvic floor muscles of the observation group at the pre-rest stage，fast muscle (type Ⅱ muscle) stage，slow muscle (type Ⅰ muscle) stage，endurance test stage，and post-rest stage were significantly improved compared with those before treatment and were greatly enhanced compared with those of the control group (P<0.05).No serious adverse reactions occurred in either groups during treatment and follow-up. Conclusion: The Yun-type pelvic floor optimization training assisted with myoelectric biofeedback can precisely enhance the therapeutic effects of the conventional Yun-type pelvic floor optimization training，and significantly improve the female sexual function index.It is worthy of clinical promotion and application.

Acute myeloid leukemia (AML) is a highly heterogeneous hematological malignancy characterized by an abnormal proliferation of primitive and naive myeloid cells in the bone marrow and peripheral blood. Patients vary enormously in molecular biological features, clinical manifestations and prognosis, leading to therapeutic difficulties. Increasing evidence indicates that the tumor microenvironment plays an important role in the development and progression of AML. Immunometabolism reveals the metabolic network of immune cells, which has important implications in tumor research. This work reviews the research progress on the metabolic alterations of immune cells in the AML microenvironment and the therapeutic strategies targeting immune metabolism in AML to present a part of the blueprint of immune metabolism regulation in the bone marrow microenvironment of AML.