ObjectiveTo construct and evaluate a mouse model that simulates the pathological progression of immune checkpoint inhibitor-associated pneumonitis (CIP), in order to address the critical issue of the lack of standardized animal models in this research field. MethodsThirty-five SPF-grade 6-week-old male C57BL/6J mice were randomly assigned to a control group (n=5), a bleomycin (BLM) group (n=15), and a BLM+programmed death-1 (PD-1) monoclonal antibody (BLM+PD-1) group (n=15). Corresponding drugs were administered via intraperitoneal injection for intervention. The general condition, body weight changes, survival rate, and pulmonary histopathological alterations were systematically monitored. ResultsCompared with the BLM group, the BLM+PD-1 group exhibited significantly more severe pulmonary fibrosis, characterized by progressive body weight loss and more severe deterioration of general conditions. Histopathological examination showed that pulmonary inflammation was alleviated 4 weeks post-modeling in the BLM group. In contrast, pulmonary lesions continued to worsen in the BLM+PD-1 group, with no evidence of resolution of inflammation 28 days post-modeling. Quantitative immunohistochemical analysis revealed that the positive expression rate of interleukin-17A (IL-17A) in lung tissues reached 34.28% in the BLM+PD-1 group 14 days post-modeling, which was markedly higher than that in the BLM group (24.02%, P < 0.000 1). The positive expression rate of α-smooth muscle actin (α-SMA) was 12.40% in the BLM+PD-1 group 14 days post-modeling, nearly twice the level in the BLM group (5.87%). 28 days post-modeling, the positive expression rate of α-SMA remained at 7.72% in the BLM+PD-1 group, while it declined to 3.38% in the BLM group. ConclusionThe addition of a PD-1 inhibitor to bleomycin treatment accelerates the progression of pulmonary interstitial fibrosis and effectively recapitulates the pathological process of lung injury and fibrosis driven by aberrant immune activation during clinical immunotherapy. Accordingly, this study successfully establishes a dynamic CIP animal model recapitulating the progression from early inflammatory response to pulmonary fibrosis. This model addresses the critical shortage of animal models for this condition and offers an experimental platform for further mechanistic studies and the development of therapeutic strategies.

Background Patients with pneumoconiosis often have limited disease-related knowledge, insufficient access to health education, and substantial health management needs. Health education may help improve rehabilitation outcomes and quality of life in this population. Objective To evaluate the effects of health education based on the Listen-Establish-Adopt-Reinforce-Name-Strength (LEARNS) model on rehabilitation outcomes, health-related behaviors, and quality of life among pneumoconiosis patients, and provide effective intervention strategies for the rehabilitation management of patients with pneumoconiosis. Methods A randomized controlled trial was conducted. A total of 120 pneumoconiosis patients treated in the Department of Occupational Diseases, Beijing Emergency General Hospital, from November 2024 to February 2025 were enrolled. Participants were randomly assigned to a control group or an intervention group using a random number table method, with 60 patients in each group. The control group received routine pharmacotherapy, whereas the intervention group received a 12-week LEARNS model-based health-education intervention in addition to routine treatment. The 6-Minute Walk Test (6MWT) was used to assess exercise tolerance, and the modified Medical Research Council dyspnoea scale (mMRC) was used to evaluate dyspnoea. The Self-Rating Anxiety Scale (SAS) and Self-Rating Depression Scale (SDS) were applied for psychological status assessment. Pulmonary function, including forced expiratory volume in one second (FEV₁) and forced vital capacity (FVC), was measured using spirometry. A self-designed scale was used to evaluate eight health-related behaviors targeted by the health education program. The 36-Item Short-Form Health Survey (SF-36) and Chronic Obstructive Pulmonary Disease (COPD) Assessment Test (CAT) were used to assess quality of life, and the Pittsburgh Sleep Quality Index (PSQI) was adopted to evaluate sleep quality. Results After the 12-week intervention, the control group showed no statistically significant changes from baseline in the measured outcomes(P＞0.05). In the intervention group, exercise tolerance improved significantly, with the 6-minute walking distance increasing from (382.55±19.52) m to (426.84±33.59) m (P＜0.001). Dyspnoea was also alleviated, with the mMRC score decreasing from 1.37±0.66 to 0.96±0.54 (P＜0.001). The CAT score decreased from 18.95±7.03 to 10.67±3.64 (P＜0.001). Significant improvements were observed in anxiety and depression symptoms (P＜0.001), with the SAS score decreasing from 38.85±6.24 to 34.27±2.27, and the SDS score decreasing from 49.01±3.25 to 45.49±3.44. Sleep quality improved significantly, with the PSQI score dropping from 7.89±4.35 to 4.05±2.31 (P＜0.001). All eight health-related behaviors in the intervention group improved significantly after the intervention (P＜0.001), including acquisition of disease-related knowledge (1.87±0.34 vs. 3.13±0.45), participation in health education activities (1.89±0.52 vs. 3.61±0.38), and regular physical exercise (2.37±0.41 vs. 4.17±0.33). All SF-36 domain scores increased significantly (P＜0.05), with the most prominent improvements observed in physical functioning, general health, and vitality. At week 12, all SF-36 domain scores were significantly higher in the intervention group than in the control group (P＜0.05). No statistically significant between-group differences were detected in pulmonary function parameters (P＞0.05). Conclusion LEARNS model-based health education could improve exercise tolerance, dyspnea, psychological status, sleep quality, health-related behaviors, and quality of life among patients with pneumoconiosis, and therefore may be a useful adjunctive strategy for rehabilitation management in patients with pneumoconiosis.

Metformin is a common oral hypoglycemic drug, which has an important role in improving insulin resistance and regulating the level of glucolipid metabolism.With the widespread use of metformin in recent years, new evidence suggests that it also regulates multiple biological processes such as autophagy, inflammation, angiogenesis, and fibrosis, which may provide the theoretical basis for the use of metformin in ocular disease.Current studies have implicated that metformin has great potential in ocular therapy in preclinical and clinical applications, especially for patients with diabetic retinopathy, where metformin has an important role in delaying disease progression by inhibiting hyperglycemia-induced retinal inflammation, oxidative injury, and vascular endothelial growth factor signaling pathway.For nondiabetic ocular disease, metformin ameliorated the disease course by modulating cellular metabolism, improving oxidative stress and autophagy, and downregulating pro-inflammatory cytokines.Considering the multifaceted roles beyond glucose-lowering effects, as the advantage of safety profile and low cost, metformin has the potential as a novel therapeutic strategy for the treatment of ocular disease.This article reviews the research progress on the application of metformin in ocular diseases.

Rapid developments in biotechnology have led researchers to seek new method to improve the efficiency and accuracy of biomedical research and drug development,promoting interdisciplinary integration.Recent advancements in artificial intelligence(AI)technologies have brought unprecedented opportunities to this field.The integration of various AI models allows researchers to better utilize multi-omics data,identify disease phenotypes,interpret animal behavior,assess treatment effects,improve experimental designs,reduce the use of experimental animals,enhance animal facility management,and improve animal welfare.This article reviews the advancements in AI biomedical research over the past decade and discusses its contributions to disease phenotype identification,the selection and design of experimental animal models,animal behavior analysis,and animal facility management.It also points out the challenges related to data standardization,AI model selection and interpretability,the extrapolation process from AI models to animal experiments and clinical practice,as well as ethical considerations in using AI in sensitive areas involving human genetics and personalized medicine.This review aims to help researchers and practitioners in relevant fields understand the current state and opportunities of AI development,thus providing support for its broader application.

Metformin is a common oral hypoglycemic drug, which has an important role in improving insulin resistance and regulating the level of glucolipid metabolism.With the widespread use of metformin in recent years, new evidence suggests that it also regulates multiple biological processes such as autophagy, inflammation, angiogenesis, and fibrosis, which may provide the theoretical basis for the use of metformin in ocular disease.Current studies have implicated that metformin has great potential in ocular therapy in preclinical and clinical applications, especially for patients with diabetic retinopathy, where metformin has an important role in delaying disease progression by inhibiting hyperglycemia-induced retinal inflammation, oxidative injury, and vascular endothelial growth factor signaling pathway.For nondiabetic ocular disease, metformin ameliorated the disease course by modulating cellular metabolism, improving oxidative stress and autophagy, and downregulating pro-inflammatory cytokines.Considering the multifaceted roles beyond glucose-lowering effects, as the advantage of safety profile and low cost, metformin has the potential as a novel therapeutic strategy for the treatment of ocular disease.This article reviews the research progress on the application of metformin in ocular diseases.

Rapid developments in biotechnology have led researchers to seek new method to improve the efficiency and accuracy of biomedical research and drug development,promoting interdisciplinary integration.Recent advancements in artificial intelligence(AI)technologies have brought unprecedented opportunities to this field.The integration of various AI models allows researchers to better utilize multi-omics data,identify disease phenotypes,interpret animal behavior,assess treatment effects,improve experimental designs,reduce the use of experimental animals,enhance animal facility management,and improve animal welfare.This article reviews the advancements in AI biomedical research over the past decade and discusses its contributions to disease phenotype identification,the selection and design of experimental animal models,animal behavior analysis,and animal facility management.It also points out the challenges related to data standardization,AI model selection and interpretability,the extrapolation process from AI models to animal experiments and clinical practice,as well as ethical considerations in using AI in sensitive areas involving human genetics and personalized medicine.This review aims to help researchers and practitioners in relevant fields understand the current state and opportunities of AI development,thus providing support for its broader application.

Objective:To investigate the acute gastrointestinal injury (AGI) in patients with extracorporeal membrane oxygenation (ECMO) at the early stage of operation and its influencing factors.Methods:A total of 70 patients with ECMO who were hospitalized in the Emergency Care Unit of Guangxi Zhuang Autonomous Region People's Hospital from September 2020 to December 2021 were retrospectively analyzed, and a total of 70 patients with ECMO who were hospitalized in the emergency care unit of Guangxi Zhuang Autonomous Region People's Hospital from September 2020 to December 2021 were retrospectively analyzed. According to the 2012 guidelines of the European Society of Intensive Care Medicine on the classification of acute gastrointestinal injury in critically ill patients, the patients were divided into AGI group and non-AGI group. The incidence of acute gastrointestinal injury in the early stage was statistically analyzed, and the results of blood gas analysis during ECMO loading and ECMO parameters, hemodynamic indexes and biochemical indexes after ECMO transfer were statistically analyzed. To explore the influencing factors and independent risk factors of AGI in the early stage. In addition, 70 patients were divided into successful group and non-successful group according to whether they were successfully withdrawn. The occurrence of acute gastrointestinal injury between the two groups was compared, and the effect of acute gastrointestinal injury on ECMO patients was analyzed.Results:Among the 70 ECMO patients, the incidence of early AGI was 71.43% (50 cases), and the components of AGI Ⅰ, Ⅱ, Ⅲ and Ⅳ were 18.57% (13 cases), 41.43% (29 cases), 11.43% (8 cases) and 0% (0 cases), respectively. ① Univariate analysis showed that systolic blood pressure, diastolic blood pressure, mean arterial pressure (MAP), vasoactive drug index (VIS), pH, lactic acid and BMI were significantly different between AGI group and non-AGI group when ECMO was used ( P < 0.05). Logistic binary regression analysis showed that BMI was an independent risk factor for early AGI in ECMO patients (ROC area 0.657, 95% confidence interval 0.522-0.791 ( P < 0.05), and Yoden index 0.15). (3) The AGI composition ratio of the unsuccessful group was higher than that of the unsuccessful group ( P < 0.05). Conclusions:Patients with ECMO have a high incidence of AGI in the early stage, mainly occurring in grade I and Ⅱ. Systolic blood pressure, diastolic blood pressure, MAP, VIS, pH, lactic acid and BMI when ECMO is put on are influential factors for the early development of AGI in ECMO patients, among which BMI is an independent risk factor for the early development of AGI in ECMO patients. The occurrence of AGI reduces the probability of successful withdrawal in ECMO patients.

OBJECTIVE: To explore the influences of andrographolide (Andro) on bladder cancer cell lines and a tumor xenograft mouse model bearing 5637 cells. METHODS: For in vitro experiments, T24 cells were stimulated with Andro (0-40 µmol/L) and 5637 cells were stimulated with Andro (0 to 80 µmol/L). Cell growth, migration, and infiltration were assessed using cell counting kit-8, colony formation, wound healing, and transwell assays. Apoptosis rate was examined using flow cytometry. In in vivo study, the antitumor effect of Andro (10 mg/kg) was evaluated by 5637 tumor-bearing mice, and levels of nuclear factor κ B (NF- κ B) and phosphoinositide 3-kinase/AKT related-proteins were determined by immunoblotting. RESULTS: Andro suppressed growth, migration, and infiltraion of bladder cancer cells (P⩽0.05 or P⩽0.01). Additionally, Andro induced intrinsic mitochondria-dependent apoptosis in bladder cancer cell lines. Furthermore, Andro inhibited bladder cancer growth in mice (P⩽0.01). The expression of p65, p-AKT were suppressed by Andro treatment in vitro and in vivo (P⩽0.05 or P⩽0.01). CONCLUSIONS Andrographolide inhibits proliferation and promotes apoptosis in bladder cancer cells by interfering with NF- κ B and PI3K/AKT signaling in vitro and in vivo.
Animals ; Apoptosis ; Cell Line, Tumor ; Cell Proliferation ; Diterpenes/therapeutic use* ; Humans ; Mice ; NF-kappa B/metabolism* ; Phosphatidylinositol 3-Kinases/metabolism* ; Proto-Oncogene Proteins c-akt/metabolism* ; Urinary Bladder Neoplasms/drug therapy*

Objective:To examine the correlations of C-reactive protein (CRP)/albumin ratio (CAR) with the postoperative complications of patients with colorectal cancer.Methods:The clinic data of 312 patients undergoing elective surgery for colorectal cancer in Hainan Hospital of People′s Liberation Army General Hospital between January 2013 and July 2018 was analyzed retrospectively. There were 188 males and 124 females, aged (61.0±12.9) years (range: 21 to 86 years). Logistic analysis was used to identify relative factors for postoperative complications. Receiver operating characteristic curves were developed to examine the cutoff values and compare diagnostic accuracy of the CAR and CRP levels.Results:Postoperative complications occured in 28.5% (89/312) cases. Hemoglobin on postoperative day(POD) 3 ( OR=0.977, 95% CI: 0.957 to 0.998, P=0.034), preoperative CRP ( OR=1.209, 95% CI: 1.055 to 1.386, P=0.006) and CAR on POD 3 ( OR=0.033, 95% CI: 0.016 to 0.067, P<0.01) were found to be significant independent relative factors for postoperative complications. The cutoff point of CAR on POD 3 was 0.325, patients with CAR≥0.325 were found to have more postoperative complications than those with CAR<0.325. The area under the curve of CAR on POD 3 and preoperative CRP were 0.872, 0.626, respectively. The positive predictive value of CAR on POD 3 was higher than that of preoperative CRP (79.9% vs. 55.1%). Conclusions:CAR is closely related to the occurrence of postoperative complications in colorectal surgery. Patients with CAR≥0.325 on POD 3 has higher incidence of postoperative complications.

Objective:To examine the correlations of C-reactive protein (CRP)/albumin ratio (CAR) with the postoperative complications of patients with colorectal cancer.Methods:The clinic data of 312 patients undergoing elective surgery for colorectal cancer in Hainan Hospital of People′s Liberation Army General Hospital between January 2013 and July 2018 was analyzed retrospectively. There were 188 males and 124 females, aged (61.0±12.9) years (range: 21 to 86 years). Logistic analysis was used to identify relative factors for postoperative complications. Receiver operating characteristic curves were developed to examine the cutoff values and compare diagnostic accuracy of the CAR and CRP levels.Results:Postoperative complications occured in 28.5% (89/312) cases. Hemoglobin on postoperative day(POD) 3 ( OR=0.977, 95% CI: 0.957 to 0.998, P=0.034), preoperative CRP ( OR=1.209, 95% CI: 1.055 to 1.386, P=0.006) and CAR on POD 3 ( OR=0.033, 95% CI: 0.016 to 0.067, P<0.01) were found to be significant independent relative factors for postoperative complications. The cutoff point of CAR on POD 3 was 0.325, patients with CAR≥0.325 were found to have more postoperative complications than those with CAR<0.325. The area under the curve of CAR on POD 3 and preoperative CRP were 0.872, 0.626, respectively. The positive predictive value of CAR on POD 3 was higher than that of preoperative CRP (79.9% vs. 55.1%). Conclusions:CAR is closely related to the occurrence of postoperative complications in colorectal surgery. Patients with CAR≥0.325 on POD 3 has higher incidence of postoperative complications.