Objective To explore the prevalence of depressive symptoms in postoperative patients with ovarian cancer and to analyze its influencing factors from multiple dimensions, including clinical characteristics, psychological factors, and laboratory indicators. Methods A cross-sectional study was conducted, which enrolled 235 postoperative patients with ovarian cancer. Depressive status was assessed using the patient health questionnaire, and the demographic, pathological, and medical record data of the patients were collected using the generalized anxiety disorder scale, Pittsburgh sleep quality index, European organization for research and treatment of cancer quality of life questionnaire core 30, and ECOG performance status score. Peripheral blood tumor marker (CA125), routine blood test, lymphocyte subsets, and serum cytokine levels were measured. Univariate and multivariate binary logistic regression analysis were used for statistical analysis. Results The prevalence of depression in postoperative patients with ovarian cancer was 39.15% (92/235). Univariate analysis showed that ECOG score ≥ 2 points, pain, anxiety, poor sleep quality, low quality of life, low life satisfaction, tumor recurrence, six or more cycles of chemotherapy, as well as higher levels of CA125, NLR, and NAR, and lower hemoglobin levels were significantly associated with depression (all P<0.05). Multivariate binary Logistic regression analysis showed that anxiety (OR=1.975, 95%CI: 1.231-3.170), sleep efficiency (OR=4.181, 95%CI: 1.211-14.43), sleep latency (OR=34.806, 95%CI: 4.258-284.542), ECOG performance status score, cognitive function (OR=0.918, 95%CI: 0.868-0.97), and life satisfaction were independent risk factors for depression (all P<0.05). Laboratory indicators were not independent influencing factors in the multivariate Logistic regression model. Conclusion Depression in postoperative patients with ovarian cancer is influenced by physiological, psychological, and social factors. Clinical management should focus on patients with anxiety, sleep disorders, poor physical condition, and low life satisfaction, and a comprehensive prevention and treatment strategy centered on psychological intervention and taking into account symptom management and social support should be implemented.

ObjectiveTo evaluate the effectiveness and safety of Sufei Pingchuan Formula （肃肺平喘方） in the treatment of bronchiectasis with airflow limitation， phlegm-heat obstructing the lung， and lung-spleen qi deficiency syndrome. MethodsA randomized， double-blind， placebo-controlled trial was conducted. A total of 72 patients with stable bronchiectasis with airflow limitation of phlegm-heat obstructing the lung and lung-spleen qi deficiency syndrome were randomly divided into treatment group and control group， with 36 cases in each group. On the basis of regular inhalation of tiotropium bromide inhalation spray， the treatment group was given Sufei Pingchuan Formula granules， and the control group was given Sufei Pingchuan Formula granule simulant. The course of treatment in both groups was 12 weeks. The pulmonary function of both groups before and after treatment was observed， specifically focusing on forced expiratory volume in one second （FEV1）； the modified British Medical Research Council （mMRC） dyspnea scale， 24-hour sputum volume， COPD assessment test （CAT）， and traditional Chinese medicine （TCM） syndrome scores were assessed before treatment and after 4， 8， and 12 weeks of treatment； acute exacerbations were recorded at weeks 4， 8， and 12； additionally， changes in routine blood tests， urinalysis， liver and kidney function， and adverse events were monitored before and after treatment. ResultsAfter treatment， 4 patients in the treatment group and 6 in the control group dropped out. After 12 weeks of treatment， FEV1 increased in both groups compared to pre-treatment levels （P＜0.05）， but the difference between groups was not statistically significant （P＞0.05）. Compared to before treatment， the treatment group showed a reduction in mMRC scores after 12 weeks （P＜0.05） and a decrease in 24-hour sputum volume， CAT scores， and TCM syndrome scores at weeks 4， 8， and 12 （P＜0.05）. In the control group， 24-hour sputum volume decreased after 12 weeks （P＜0.05）， and TCM syndrome scores decreased at weeks 8 and 12 （P＜0.05）. Compared to the control group， the treatment group showed a greater reduction in mMRC scores at week 12 （P＜0.05）， a decrease in 24-hour sputum volume and TCM syndrome scores at weeks 4， 8， and 12 （P＜0.05）， and lower CAT scores at weeks 8 and 12 （P＜0.05）. The frequency and number of acute exacerbations in the treatment group were significantly lower than those in the control group at week 12 （P＜0.05）. No severe adverse events occurred in either group. ConclusionSufei Pingchuan Formula can improve the pulmonary function FEV1， the severity of dyspnea， reduce 24-hour sputum volume and frequent acute exacerbations， and improve the quality of life in patients with bronchiectasis and airflow limitation， with good safety.

INTRODUCTION: Adverse childhood experiences (ACEs) are associated with significant long-term impacts, yet few interventions specifically target ACE exposure, especially in Asian populations. Anchor, Singapore's first home visitation programme, addresses maltreat-ment among preschool children. This study evaluated Anchor's impact on children's developmental and behavioural outcomes. METHOD: We conducted a prospective evaluation of children under 4 years assessed for maltreatment from November 2019 to July 2023. Developmental and behavioural progress was measured every 6 months using the Ages and Stages Questionnaires (ASQ-3) and ASQ:Social-Emotional (ASQ:SE-2), and annually using the Child Behaviour Checklist (CBCL). RESULTS: The results of 125 children (mean age 20.0 months, 48% female) were analysed. The mean length of stay in programme was 21.2 (7.3) months. At baseline, 92 (73.6%) children were at risk of develop-mental delay and 25 (31.7%) children aged ≥18 months had behavioural concerns. The programme was associated with significant improvements in gross motor (P=0.002) and fine motor (P=0.001) domains of the ASQ-3 and internalising problem scale (P=0.001) of the CBCL. CONCLUSION Anchor effectively enhances develop-mental and behavioural outcomes for children exposed to maltreatment. Targeted early intervention through such programmes can mitigate adverse impacts, optimising developmental trajectories and potentially reducing the long-term clinical and economic burdens associated with ACEs.
Humans ; Female ; Male ; Child Abuse/therapy* ; Child, Preschool ; Singapore ; House Calls ; Infant ; Prospective Studies ; Child Development ; Developmental Disabilities/epidemiology* ; Program Evaluation ; Child Behavior Disorders ; Child Behavior

This study aims to explore the mechanism of Huanglian Jiedu Decoction(HJD) in treating acute liver injury(ALI) in the mouse model of sepsis induced by lipopolysaccharide(LPS). Fifty-four male C57BL/6 mice were randomized into six groups: blank group, model group, low-, medium-, and high-dose group HJD, and dexamethasone group. The mouse model of sepsis was established by intraperitoneal injection of LPS after 7 days of gavage with HJD, and dexamethasone(0.2 mL) was injected intraperitoneally 1.5 h after modeling. The murine sepsis score(MSS) was recorded 12 h after modeling. The levels of alanine aminotransferase(ALT) and aspartate aminotransferase(AST) in the liver tissue and tumor necrosis factor-α(TNF-α) and interleukin-6(IL-6) in the serum were measured by ELISA. Hematoxylin-eosin(HE) staining was used to observe the pathological changes of the mouse liver. The content of light chain 3 of microtubule-associated protein 1(LC3) was detected by immunofluorescence, and that of sirtuin 1(SIRT1) was detected by immunohistochemistry. The mRNA levels of adenosine 5'-monophosphate-activated protein kinase(AMPK), LC3, and P62 were detected by RT-PCR. Western blot was employed to determine the protein levels of AMPK, p-AMPK, and SIRT1 in the liver tissue. The results showed that compared with model group, drug interventions decreased the MSS and liver injury indicators, lowered the levels of inflammatory cytokines, improved the liver tissue structure, upregulated the protein levels of of p-AMPK/AMPK and SIRT1 and the mRNA levels of AMPK and LC3, and downregulated the mRNA level of P62. To sum up, HJD can regulate the autophagy level and reduce inflammation to ameliorate acute liver injury in septic mice by activating the AMPK/SIRT1 autophagy pathway.
Animals ; Drugs, Chinese Herbal/administration & dosage* ; Sirtuin 1/genetics* ; Male ; Mice ; Sepsis/metabolism* ; Mice, Inbred C57BL ; Autophagy/drug effects* ; AMP-Activated Protein Kinases/genetics* ; Liver/metabolism* ; Humans ; Signal Transduction/drug effects* ; Disease Models, Animal ; Tumor Necrosis Factor-alpha/genetics*

Objective:To discuss the influencing factors of angina pectoris in the patients with diabetes mellitus(DM),to construct a Bayesian network model to explore the network relationships among the influencing factors,and to predict the risk of angina pectoris in the patients with DM.Methods:Based on the UK Biobank(UKB)database,the Logistic regression aralysis model was used to screen the influencing factors of angina pectoris in the patients with DM.The taboo search algorithm was used for structure learning,and the Bayesian parameter estimation method was used for parameter learning to construct the Bayesian network model.Results:A total of 22 712 DM patients were included.The influencing factors of angina pectoris in the patients with DM included 14 variables:gender,age,body mass index(BMI),triglycerides(TG),total cholesterol(TC),glycated hemoglobin(HbA1c),hypertension,maternal smoking around delivery,smoking status,alcohol consumption,regular exercise,insomnia,sleep duration,and childhood relative body size(P<0.05).A Bayesian network model was constructed with 15 nodes and 22 directed edges.Among them,age,HbA1c,hypertension,regular exercise,BMI,and sleep duration were directly associated with the occurrence of angina pectoris in the patients with DM,while gender,smoking status,alcohol consumption,TC,TG,insomnia,childhood relative body size,and maternal smoking around delivery were indirectly associated with the occurrence of angina pectoris in the patients with DM.Conclusion:Age,HbA1c,hypertension,regular exercise,BMI,and sleep duration are direct influencing factors of angina pectoris in the patients with DM.Controlling HbA1c,blood pressure,and BMI levels,engaging in regular exercise,and maintaining appropriate sleep duration are beneficial for reducing the risk of angina pectoris in the patients with DM.

Objective:To screen the Alzheimer's disease(AD)-related genes and construct its diagnostic model using bioinformatics technology and machine learning(ML)algorithms,to discuss the immunological characteristics of AD patients,and to provide novel biomarkers for AD diagnosis.Methods:The AD-related gene expression dataset GSE125583 was downloaded from the Gene Expression Omnibus(GEO)database.Differentially expressed genes(DEGs)were identified through differential analysis.Gene Ontology(GO)functional enrichment and Kyoto Encyclopedia of Genes and Genomes(KEGG)signaling pathway enrichment analyses were performed to explore the biological functions and signaling pathways of DEGs.A protein-protein interaction(PPI)network was constructed,and hub genes were screened using Cytoscape software combined with three ML algorithms:Least Absolute Shrinkage and Selection Operator(LASSO),eXtreme Gradient Boosting(XGBoost),and Random Forest(RF).The screened hub genes were utilized to build an AD diagnostic model via RF,followed by feature importance ranking.The model's efficacy and key genes were evaluated using a test set.Single-sample gene set enrichment analysis(ssGSEA)was used for immune cell infiltration analysis between AD group and control group.Results:Differential analysis identified 1 287 DEGs.The GO functional enrichment analysis results revealed that DEGs were primarily involved in biological functions related to neural signaling,synapses,and vesicles.KEGG signaling pathway enrichment analysis indicated significant enrichment of DEGs in ion transport,neurotransmitter,and ligand-gated channel pathways.Nine overlapping hub genes were screened by the three ML algorithms.In the AD diagnostic model,the top four key genes with highest diagnostic performance were adenylate cyclase-activating polypeptide 1(ADCYAP1),brain-derived neurotrophic factor(BDNF),platelet-derived growth factor receptor β(PDGFRB),and C-X-C motif chemokine receptor 4(CXCR4),with corresponding area under the curve(AUC)values of 0.852,0.795,0.820,and 0.756,respectively.The model achieved an AUC of 0.828,accuracy of 81.25%,sensitivity of 84.40%,and specificity of 71.43%.The immune cell infiltration analysis results demonstrated higher infiltration of macrophages,monocytes,natural killer(NK)cells,and lymphocytes in AD tissue.Among these,NK/natural killer T(NKT)cells and plasmacytoid dendritic cells showed significant correlations with the four key genes(P<0.05).Conclusion:The feature genes screened based on bioinformatics and ML exhibit diagnostic potential for AD.Genes such as ADCYAP1 may serve as potential biomarkers for AD diagnosis,offering significant implications for early prevention and treatment.

Poly(lactic-co-glycolide)(PLGA)is a key excipient in long-acting sustained-release preparations,and its degradation properties directly affect the drug release behavior.In this study,PLGA microspheres were prepared by microfluidic techniques,and the morphology changes of the microspheres were observed by scanning electron microscopy(SEM).In alkaline environment,due to the accelerated hydrolysis of ester bonds,the surface of the microspheres was rapidly dissolved and eroded,and the degradation rate was significantly higher than that in acidic environment.High temperature accelerated the degradation of PLGA microspheres.Under neutral and alkaline conditions,the microspheres showed aggregation and adhesion.Under acidic conditions,the microspheres gradually decomposed into irregular fragments.The high ionic strength further promoted the surface corrosion of the microspheres,especially under extreme pH conditions.Simultaneously,PLGA microspheres encapsulating coumarin were prepared to simulate the microsphere formulation.The release rate of coumarin after degradation of the microspheres under different conditions was observed by measuring the absorbance with ultraviolet-visible spectrophotometry.The results were consistent with those of the blank microspheres.This study revealed that the degradation of PLGA microspheres was significantly pH-dependent,temperature sensitive and ion strength responsive.These findings not only helped to understand and optimize the long-term stability and controlled release performance of drug-carrying microspheres,but also provided a theoretical basis for further improvement of PLGA-based drug carrier design.

The development of traditional Chinese medicine (TCM) diagnosis and treatment has undergone multiple paradigms, evolving from sporadic experiential practices to systematic approaches in syndrome differentiation and treatment and further integration of disease and syndrome frameworks. TCM is a vital component of the medical system, valued alongside Western medicine. Treatment based on syndrome differentiation embodies both personalized treatment and holistic approaches; however, the inconsistency and lack of stability in syndrome differentiation limit clinical efficacy. The existing integration of diseases and syndromes primarily relies on patchwork and embedded systems, where the full advantages of synergy between Chinese and Western medicine are not fully realized. Recently, driven by the development of diagnosis and treatment concepts and advances in analytical technology, Western medicine has been rapidly transforming from a traditional biological model to a precision medicine model. TCM faces a similar need to progress beyond traditional syndrome differentiation and disease-syndrome integration toward a more precise diagnosis and treatment paradigm. Unlike the micro-level precision trend of Western medicine, precision diagnosis and treatment in TCM is primarily reflected in data-driven applications that incorporate information at various levels, including precise syndrome differentiation, medication, disease management, and efficacy evaluation. The current priority is to accelerate the development of TCM precision diagnosis and treatment technology platforms and advance discipline construction in this area.

Traditional Chinese medicine （TCM） therapy has unique clinical advantages in the treatment of atrial fibrillation， mainly reflected in five aspects， improving quality of life， enabling early diagnosis and treatment， promoting cardiac rehabilitation， making up for the limitations of Western medicine， and improving the success rate of catheter ablation. However， there is insufficient evidence in current clinical research. Based on the current status of TCM research in the treatment of atrial fibrillation， it is suggested that future studies should focus on standardized research on syndrome differentiation and classification. This can be achieved through clinical epidemiological surveys， expert consensus， and other methods to establish a unified syndrome differentiation and classification standard for atrial fibrillation. Clinical efficacy evaluation indicators should be standardized， and core outcome measures for clinical research on TCM treatment of atrial fibrillation should be developed through systematic reviews， patient interviews， and other methods. Additionally， clinical research design， implementation， and data management should be improved. By leveraging modern information technologies such as artificial intelligence， the scientific and standardized nature of TCM intervention research on atrial fibrillation can be enhanced， ultimately improving the quality of research.