Dry eye disease(DED)is a multifactorial disorder with an unclear pathogenesis. Advances in omics technologies have introduced a novel medical research approach, enabling the identification of global response variables from a single-factor perspective. However, multi-omics methods integrate multiple omics datasets to analyze all potential response variables, generating multidimensional and evidence-supported holistic inferences. These insights help elucidate functional impairments of ocular cells and biomolecular processes during disease progression, thereby revealing correlations between biomolecules and complex diseases. This review summarizes the application of multi-omics technologies in clarifying the pathogenesis and intricate molecular mechanisms of dry eye disease. Distinctive features from genomics, transcriptomics, proteomics, metabolomics, and microbiomics are integrated to deepen the understanding of the pathogenesis and complex molecular mechanisms underlying dry eye disease.

Objective: To explore the association of outdoor activity time and sleep duration with screening myopia in primary school students, so as to provide strategies for myopia prevention. Methods: Through a convenience sampling method, a survey was conducted among 4 248 primary school students aged 7-13 years from three primary schools in Xihu District, Nanchang City, Jiangxi Province from May to July, 2023. The average daily outdoor activity time and sleep duration on both weekdays and weekends were investigated in primary school students by using a self designed questionnaire. Uncorrected visual acuity tests and non cycloplegic autorefraction were measured by professional optometrists. Inter group comparisons were conducted using the Chi square test. Logistic regression model was used to analyze the association of outdoor activity time and sleep duration with screening myopia. Results: The detection rate of screening myopia in primary school students was 33.6%, with the rate in boys (32.0%) lower than that in girls (35.3%), and the difference was statistically significant ( χ 2=5.11, P =0.02). The analysis results of Logistic regression showed that after adjusting for factors such as gender, grade and parental education level, both average daily outdoor activity time ＜2 h on both weekdays and weekends ( OR =1.27, 95% CI =1.11-1.46) and sleep duration <10 h ( OR =1.17, 95% CI =1.01- 1.35 ), as well as their combined effect ( OR =1.57, 95% CI =1.25-1.98), were associated with an increased risk of screening myopia in primary school students(all P <0.05). Subgroup analysis results indicated that compared to boys ( OR =1.46, 95% CI = 1.07 -1.99), girls( OR =1.73, 95% CI =1.22-2.44) with insufficient outdoor activity time and sleep duration had a higher risk of screening myopia(both P <0.05). Conclusions There is a negative correlation of outdoor activity time and sleep duration with screening myopia in primary school students. Outdoor activity time and extending sleep duration should be increased to reduce the risk of myopia in primary school students.

Annexin A3（ANXA3）is a member of the membrane associated protein family. It has two subtypes of 36 kDa and 33 kDa. Its gene is located on the fourth chromosome of human. ANXA3, widely expressed in human bone marrow, lung, placenta, prostate and thyroid, is closely related to several biological processes such as exoplasmosis, vascular production, fat cell maturity, and white blood cell migration. Studies have found that ANXA3 is abnormally expressed in various diseases including cancer, cardiovascular disease and inflammation. It can regulate multiple signaling pathways such as JNK, NF-κB, PI3K/AKT, and may become a potential drug target for treatment of related diseases. The structure, functions, the link with diseases and related mechanisms of ANXA3 were summarized in this paper, which could provide reference for ANXA3 related research.

BACKGROUND: G protein-coupled receptor kinase 2 (GRK2) could participate in the regulation of diverse cells via interacting with non-G-protein-coupled receptors. In the present work, we explored how paroxetine, a GRK2 inhibitor, modulates the differentiation and activation of immune cells in rheumatoid arthritis (RA). METHODS: The blood samples of healthy individuals and RA patients were collected between July 2021 and March 2022 from the First Affiliated Hospital of Anhui Medical University. C57BL/6 mice were used to induce the collagen-induced arthritis (CIA) model. Flow cytometry analysis was used to characterize the differentiation and function of dendritic cells (DCs)/T cells. Co-immunoprecipitation was used to explore the specific molecular mechanism. RESULTS: In patients with RA, high expression of GRK2 in peripheral blood lymphocytes, accompanied by the increases of phosphatidylinositol 3 kinase (PI3K), protein kinase B (AKT), and mammalian target of rapamycin (mTOR). In animal model, a decrease in regulatory T cells (T regs ), an increase in the cluster of differentiation 8 positive (CD8 + ) T cells, and maturation of DCs were observed. Paroxetine, when used in vitro and in CIA mice, restrained the maturation of DCs and the differentiation of CD8 + T cells, and induced the proportion of T regs . Paroxetine inhibited the secretion of pro-inflammatory cytokines, the expression of C-C motif chemokine receptor 7 in DCs and T cells. Simultaneously, paroxetine upregulated the expression of programmed death ligand 1, and anti-inflammatory cytokines. Additionally, paroxetine inhibited the PI3K-AKT-mTOR metabolic pathway in both DCs and T cells. This was associated with a reduction in mitochondrial membrane potential and changes in the utilization of glucose and lipids, particularly in DCs. Paroxetine reversed PI3K-AKT pathway activation induced by 740 Y-P (a PI3K agonist) through inhibiting the interaction between GRK2 and PI3K in DCs and T cells. CONCLUSION Paroxetine exerts an immunosuppressive effect by targeting GRK2, which subsequently inhibits the metabolism-related PI3K-AKT-mTOR pathway of DCs and T cells in RA.
G-Protein-Coupled Receptor Kinase 2/metabolism* ; Arthritis, Rheumatoid/immunology* ; Animals ; Dendritic Cells/metabolism* ; Paroxetine/therapeutic use* ; Proto-Oncogene Proteins c-akt/metabolism* ; Mice ; Humans ; Mice, Inbred C57BL ; Signal Transduction/drug effects* ; Male ; Phosphatidylinositol 3-Kinases/metabolism* ; Lymphocyte Activation/drug effects* ; Female ; T-Lymphocytes/metabolism* ; Middle Aged

Natural product-based drug combinations (NPDCs) present distinctive advantages in treating complex diseases. While high-throughput screening (HTS) and conventional computational methods have partially accelerated synergistic drug combination discovery, their applications remain constrained by experimental data fragmentation, high costs, and extensive combinatorial space. Recent developments in artificial intelligence (AI), encompassing traditional machine learning and deep learning algorithms, have been extensively applied in NPDC identification. Through the integration of multi-source heterogeneous data and autonomous feature extraction, prediction accuracy has markedly improved, offering a robust technical approach for novel NPDC discovery. This review comprehensively examines recent advances in AI-driven NPDC prediction, presents relevant data resources and algorithmic frameworks, and evaluates current limitations and future prospects. AI methodologies are anticipated to substantially expedite NPDC discovery and inform experimental validation.
Artificial Intelligence ; Biological Products/chemistry* ; Humans ; Drug Combinations ; Drug Discovery/methods* ; Machine Learning ; Algorithms

OBJECTIVE: To investigate the association between fluid balance trajectories within the first 3 days of intensive care unit (ICU) admission and 28-day mortality as well as the incidence of continuous renal replacement therapy (CRRT) in patients with severe acute pancreatitis (SAP). METHODS: Clinical data of SAP patients were extracted from the Medical Information Mart of Intensive Care-IV (MIMIC-IV). Group-based trajectory modeling (GBTM) was used to analyze the daily fluid balance of patients within 3 days of ICU admission, and grouping them accordingly. Univariate and multivariate Logistic regression analyses were performed to assess the association between fluid balance trajectory and 28-day mortality and ICU CRRT in SAP patients. RESULTS: A total of 251 SAP patients were included, with 33 deaths within 28 days, and a 28-day mortality of 13.15%; 49 patients (19.52%) continued to receive bedside CRRT after 3 days of ICU admission. The fluid balance on the 3rd day, cumulative fluid balance within 3 days of ICU admission, and incidence of CRRT in the death group were significantly higher than those in the survival group. According to GBTM groups, there were 127 cases in the moderate fluid resuscitation with rapid reduction (MF group), 44 cases in the large fluid resuscitation with rapid reduction (LF group), 20 cases in the moderate fluid resuscitation with slow reduction (MS group), and 60 cases in the small fluid resuscitation with slow reduction (SS group). The cumulative fluid balance within 3 days of ICU admission of the MF group, LF group, MS group, and SS group were 8.60% (5.15%, 11.70%), 16.70% (13.00%, 21.02%), 23.40% (19.38%, 25.45%), and 0.65% (-2.35%, 2.20%), respectively, and the incidence of CRRT during ICU hospitalization were 11.02%, 29.55%, 85.00%, and 8.33%, respectively, with statistically significant differences among the groups (both P < 0.05); the 28-day mortality were 11.02%, 18.18%, 20.00%, and 11.67%, respectively, with no statistically significant difference among the groups (P > 0.05). Kaplan-Meier survival curve analysis showed there was no statistically significant difference in 28-day cumulative survival rate among groups with different fluid balance trajectories (Log-rank test: χ ² = 2.31, P = 0.509). Multivariate Logistic regression analysis showed that cumulative fluid balance within 3 days of ICU admission was an independent risk factor for 28-day mortality [odds ratio (OR) = 1.071, 95% confidence interval (95%CI) was 1.005-1.144, P = 0.040] and CRRT requirement (OR = 1.233, 95%CI was 1.125-1.372, P < 0.001); early aggressive fluid resuscitation on day 1 reduced CRRT risk (OR = 0.866, 95%CI was 0.756-0.978, P = 0.030). CONCLUSIONS Dynamic fluid management is essential in SAP patients. While early aggressive fluid resuscitation may reduce CRRT demand, excessive cumulative fluid balance is associated with increased 28-day mortality and CRRT incidence.
Humans ; Male ; Female ; Middle Aged ; Water-Electrolyte Balance ; Continuous Renal Replacement Therapy ; Intensive Care Units ; Aged ; Adult ; Pancreatitis/mortality* ; Logistic Models ; Retrospective Studies ; Renal Replacement Therapy

Abstract In recent years, the prevalence of overweight and obesity among children and adolescents has risen rapidly, posing a serious threat to their physical and mental health. To provide scientific, systematic, and standardized weight management guidance for overweight and obese children and adolescents, the study focuses on the core concept of healthy lifestyle intervention, integrates multidisciplinary expert opinions and research findings,and proposes a comprehensive multidisciplinary intervention framework covering scientific exercise intervention, precise nutrition and diet, optimized sleep management, and standardized psychological support. It calls for the establishment of a multi agent collaborative management mechanism led by the government, implemented by families, fostered by schools, initiated by individuals, optimized by communities, reinforced by healthcare, and coordinated by multiple stakeholders. Emphasizing a child and adolescent centered approach, the consensus advocates for comprehensive, multi level, and personalized guidance strategies to promote the internalization and maintenance of a healthy lifestyle. It serves as a reference and provides recommendations for the effective prevention and control of overweight and obesity, and enhancing the health level of children and adolescents.

Objective To discuss the application of ankle pump exercise with colorful ring counting command in improving the blood hypercoagulable state in patients after hepatic arterial infusion chemotherapy(HAIC).Methods A total of 105 patients,who received HAIC at the Interventional Department of a certain Grade A general hospital in Fujian Province of China from January to December of 2023,were collected.The 53 patients who received treatment from January to June of 2023 were used as the control group,and the other 52 patients who received treatment from July to December of 2023 were used as the study group.The postoperative routine nursing and ankle pump exercise was employed for the patients of the control group,while ankle pump exercise with colorful ring counting command on the basis of postoperative routine nursing was carried out for the patients of the study group.The resting status of popliteal vein,the maximum and average systolic blood flow velocity at the end of exercise,the changes in coagulation index,the incidence of deep vein thrombosis,and the compliance of ankle pump were compared between the two groups.Results There were no statistically significant differences in the resting popliteal vein blood flow velocity and incidence of deep vein thrombosis between the two groups(P＞0.05).The maximum and average popliteal vein blood flow velocity at the end of exercise in the study group were higher than those in the control group.The levels of PT,APTT,FBG,TT and D-dimer(D-D)at 72 hours after HAIC were lower than those in the control group(all P＜0.05),and the compliance of ankle pump exercise in the study group was better than that in the control group(P＜0.05).Conclusion Ankle pump exercise with colorful ring counting command can accelerate lower limb blood flow velocity,improve the blood hypercoagulable state,and improve compliance with ankle pump exercise in patients after receiving HAIC.

Objective To develop and validate risk prediction models utilizing five machine learning algorithms for assessing postoperative pulmonary infection(PPI)risk in lung cancer patients undergoing grade Ⅳ thoracoscopic surgery.Methods A retrospective cohort study included 2,380 lung cancer patients who underwent grade Ⅳ thoracoscopic surgery at a tertiary hospital in Shanghai(January 2022 to June 2024).Patients were stratified into training(n=1,665)and validation(n=715)cohorts.Five machine learning algorithms—Logistic regression(LR),artificial neural network(ANN),support vector machine(S VM),random forest(RF),and extreme gradient boosting(XGB)—were employed to construct predictive models.A nomogram was developed for clinical utility.Results Among 2,380 patients,226(9.5％)developed PPI.The Least Absolute Shrinkage and Se-lection Operator(LASSO)regression identified eight predictive variables:daily cigarette consumption,diabetes history,preoperative diffusing capacity,maximal tumor diameter,24-hour postoperative chest drainage volume,perioperative oral nutritional supplementation(ONS),postoperative urinary cathe-terization,and intraoperative pleural adhesion severity.All models demonstrated robust discrimina-tion,with area under the curve(AUC)values ranging from 0.862 to 0.947.The XGB model a-chieved superior performance(AUC=0.947,95％CI,0.937 to 0.962),followed closely by the LR model(AUC=0.926,95％CI,0.918 to 0.933).Conclusion Machine learning-based algo-rithms models effectively stratify PPI risk in lung cancer patients following grade Ⅳ thoracoscopic surgery.The derived nomogram provides a practical tool for perioperative risk management by healthcare providers.