Objective To explore the adverse event signals of children using macrolide drugs （azithromycin, clarithromycin, and erythromycin）, and provide reference for rational medicine use in clinical practice. Methods Data from children under 12 years old were extracted from the US FAERS database spanning from the first quarter of 2004 to the second quarter of 2023. The adverse drug reaction （ADR） signal mining for three macrolide antibiotics was conducted using the Reporting Odds Ratio （ROR） and Bayesian Confidence Propagation Neural Network （BCPNN） methods. Special emphasis was placed on analyzing and contrasting the differences in adverse events among the three drugs. Results A total of 1 615 reports for children under 12 years old were retrieved from the FAERS database, including 1 024 reports of azithromycin, 460 reports of clarithromycin, and 131 reports of erythromycin. Among azithromycin and erythromycin, there were more reports from boys than girls, while for clarithromycin, there were more reports from girls than boys. Oral administration was the most common route of administration for all three drugs. Regarding the outcome of adverse events reported, azithromycin and clarithromycin were primarily associated with other serious adverse events, whereas erythromycin was mainly associated with hospitalization and other serious adverse events. The number of adverse events reported decreased with increasing age, with a higher number of reports in the 0-3 age group. Using the ROR and BCPNN methods for signal detection, 86 signals were identified for azithromycin, 91 for clarithromycin, and 34 for erythromycin. These signals involved 22 System Organ Classes （SOCs）, with azithromycin mainly concentrated in skin and subcutaneous tissue disorders （n=21）, clarithromycin in gastrointestinal disorders （n=15）, and erythromycin in gastrointestinal disorders （n=8）. Twenty-four signals of moderate to high risk were detected, with 13 for azithromycin, 9 for clarithromycin, and 2 for erythromycin. Conclusion The adverse events induced by the three drugs with different risks in different systems. When clinically treating Mycoplasma pneumoniae pneumonia in children, the risk profiles of drugs in different systems should be considered, and personalized dosing should be implemented.

Background Lead is a typical persistent environmental pollutant that can accumulate in bones for decades. During pregnancy, alterations in calcium metabolism promote the mobilization of bone lead, resulting in secondary exposure; however, the mechanisms by which pregnancy-associated bone lead mobilization affects maternal renal function remain unclear. Objective To investigate the role of mitochondrial dysfunction in pregnancy-related bone lead mobilization-induced renal injury. Methods Newly weaned female Wistar rats were randomly assigned to a control or a lead-exposed group administered either 0.05% sodium acetate or 0.05% lead acetate in drinking water. Following a 4-week lead exposure and a 4-week washout period, the females were co-housed with healthy age-matched males for mating. Rats were sacrificed at early (gestational day 3) and late (gestational day 17) pregnancystages, respectively. Renal histopathology was assessed using hematoxylin and eosin staining staining. Mitochondria-related indicators, including oxidative stress, inflammatory responses, and energy metabolism, were measured. Differential metabolites were identified using serum metabolomics. Results Renal injury in the lead-exposed pregnant rats progressed in a time-dependent manner, characterized by degeneration of proximal tubular epithelial cells, glomerular hyaline changes, and interstitial inflammatory cell infiltration. Repeated measures ANOVA indicated a significant interaction between the treatment factor (lead exposure) and the temporal factor (gestational stage) on renal injury (P<0.001). Further analysis of mitochondrial function-related indicators in late-pregnancy renal tissue revealed that the lead exposure group exhibited significantly increased levels of malondialdehyde (MDA) and reactive oxygen species (ROS) (P<0.05), accompanied by a reduction in superoxide dismutase (SOD) and reduced glutathione (GSH) activities (P<0.05); regarding inflammatory markers, levels of interleukin-18 (IL-18) and interleukin-1β (IL-1β) were elevated (P<0.01), whereas interleukin-33 (IL-33) was decreased in the lead-exposed group (P<0.05); energy metabolism-related indicators, including adenosine triphosphate (ATP) level, Na⁺-K⁺-ATPase and Ca²⁺-Mg²⁺-ATPase activities, and mitochondrial respiratory chain complexes I, III, and V activities, were significantly reduced (P<0.05) in the lead-exposed gorup. The typical differential metabolite N-methylisoleucine, identified through serum metabolomics analysis, was negatively correlated with blood lead levels, kidney injury scores, and IL-1β, while positively correlated with catalase (CAT) activity and Ca²⁺-Mg²⁺-ATPase. Conclusions Mitochondrial dysfunction may play a critical role in renal injury induced by bone lead mobilization during late gestation.

ObjectiveTo evaluate the antitumor activity of Periplaneta americana extract（PAE） against human-derived lung adenocarcinoma organoids（LUAD-PDOs） and to elucidate its potential mechanism based on transcriptomics. MethodsFresh tumor and adjacent normal tissues from patients with LUAD were collected to construct LUAD-PDOs and normal lung organoid（Nor-PDOs） models using 3D organoid culture technology. The effective intervention concentration of PAE was determined using the cell counting kit-8（CCK-8） assay. Experimental groups included the model group（LUAD-PDOs）， normal group， model administration group（LUAD-PDOs+PAE）， and normal administration group（Nor-PDOs+PAE）. Hematoxylin-eosin（HE） staining was used to observe the pathological structures of PDOs， immunohistochemistry（IHC） was performed to detect the expressions of the proliferation marker Ki-67 and lung adenocarcinoma differentiation markers cytokeratin-7（CK-7） and Napsin A， TUNEL staining was applied to detect cell apoptosis. RNA sequencing（RNA-Seq） was conducted to identify differentially expressed genes（DEGs）， followed by Gene Ontology（GO）， Kyoto Encyclopedia of Genes and Genomes（KEGG）， and Gene Set Enrichment Analysis（GSEA）， alongside protein-protein interaction（PPI） network analysis to screen core mechanisms. Finally， key targets were validated by integrating external database analysis with immunofluorescence（IF）. ResultsNor-PDOs and LUAD-PDOs that highly recapitulated the pathological characteristics of the primary tissues were successfully established. The CCK-8 assay determined that the effective intervention concentration of PAE was 16 g·L^-1. Morphological observation showed that Nor-PDOs exhibited lumen-forming structures， whereas LUAD-PDOs displayed dense， solid structures. CCK-8 and TUNEL assays revealed that， compared with the model group， PAE intervention inhibited the proliferation of LUAD-PDOs and promoted apoptosis in LUAD cells， while showing no significant effect on the viability of Nor-PDOs. Transcriptomic analysis identified 719 DEGs that were significantly reversed after PAE intervention（347 up-regulated and 372 down-regulated）（P<0.05）. GO enrichment analysis indicated that DEGs in the model administration group were significantly enriched in biological processes related to cell cycle regulation compared to the model group. KEGG pathway analysis revealed that PAE affected pathways related to proliferation and metabolism， including pathways in cancer and the p53 signaling pathway. GSEA further confirmed that PAE significantly enhanced the activity of the p53 signaling pathway（P<0.05）. PPI network analysis indicated that breast cancer type 1 susceptibility protein（BRCA1） and checkpoint kinase 1（CHEK1） were the core down-regulated targets in the p53 pathway. IF verified the high expression of BRCA1 and CHEK1 in LUAD-PDOs and their significant downregulation after PAE intervention（P<0.05）. Furthermore， survival analysis based on The Cancer Genome Atlas（TCGA） database indicated that low expression of BRCA1 and CHEK1 was significantly associated with prolonged overall survival in patients with LUAD（P<0.05）. ConclusionPAE effectively inhibits proliferation of LUAD-PDOs and promotes their apoptosis， its anti-tumor mechanism is potentially associated with the activation of the p53 signaling pathway， with BRCA1 and CHEK1 genes likely serving as key downstream targets for the effects of PAE.

Polypoidal choroidal vasculopathy(PCV)is one of the important subtypes of neovascular age-related macular degeneration(nARMD), which causes severe vision loss. It is necessary to distinguish PCV from other nARMD subtypes to guide the clinical treatment plans and predict disease outcomes. In recent years, artificial intelligence(AI)has been widely used in the diagnosis and research of ophthalmic diseases. By utilizing machine learning or deep learning combined with examination images in disease classification, lesion segmentation, and quantitative assessment, etc. This article reviews the recent applications of AI in the differential diagnosis of PCV through various examination images, the segmentation and quantification of biomarkers, as well as the prediction of genotype, response to anti-vascular endothelial growth factor(VEGF)therapy, and the short-term risk of vitreous hemorrhage. It summarizes the difficulties and challenges in clinical practice of AI and looks forward to the advantages and development trends of AI in PCV applications in the future. The article aims to provide more information for further research and application, thereby improving the diagnostic rate of PCV, optimizing treatment plans, and improving patients' visual prognosis.

Polypoidal choroidal vasculopathy(PCV)is one of the important subtypes of neovascular age-related macular degeneration(nARMD), which causes severe vision loss. It is necessary to distinguish PCV from other nARMD subtypes to guide the clinical treatment plans and predict disease outcomes. In recent years, artificial intelligence(AI)has been widely used in the diagnosis and research of ophthalmic diseases. By utilizing machine learning or deep learning combined with examination images in disease classification, lesion segmentation, and quantitative assessment, etc. This article reviews the recent applications of AI in the differential diagnosis of PCV through various examination images, the segmentation and quantification of biomarkers, as well as the prediction of genotype, response to anti-vascular endothelial growth factor(VEGF)therapy, and the short-term risk of vitreous hemorrhage. It summarizes the difficulties and challenges in clinical practice of AI and looks forward to the advantages and development trends of AI in PCV applications in the future. The article aims to provide more information for further research and application, thereby improving the diagnostic rate of PCV, optimizing treatment plans, and improving patients' visual prognosis.

Objective To explore the efficacy of DSA-guided intrathecal drug delivery system combined with Zi Wu Liu Zhu Acupoint Therapy for management of cancer pain and provide reference for its standardized clinical application.Methods and Results Recommendations were formulated based on literature review and expert group discussion,and consensus was reached following expert consultation.The consensus recommendations are comprehensive,covering the entire treatment procedures from preoperative assessment and preparation,surgical operation process,postoperative management and traditional Chinese medicine treatment to individualized treatment planning.The study results showed that the treatment plans combining traditional Chinese with Western medicine effectively alleviated cancer pain,reduced the use of opioid drugs,and significantly improved the quality of life and enhanced immune function of the patients.Postoperative follow-up suggested good treatment tolerance among the patients without serious complications.Conclusion The formulated consensus is comprehensive and can provide reference for clinicians to use DSA-guided intrathecal drug delivery system combined with Zi Wu Liu Zhu Acupoint Therapy.The combined treatment has a high clinical value with a good safety profile for management of cancer pain.

Objective To investigate the influencing factors for frailty in elderly patients with mild ischemic stroke(MIS),construct a risk prediction model based on random forest algorithm and evaluate its application performance.Methods A total of 322 elderly MIS patients subjected by cluster sampling in the Neurodiagnosis and Treatment Center of our hospital during January and June 2022 were enrolled and divided into non-frailty group(n=261)and frailty group(n=61)according to the results of frailty screening scale.The general clinical data,and the scores of Daily Living Ability Scale,Simplified Geriatric Depression Scale,Social Support Rating Scale,36-Item Concise Health Questionnaire,and Simplified Intelligent State Examination Scale were compared between two groups.Random forest algorithm was used to construct a risk prediction model for frailty in the elderly MIS patients,and ROC curve was plotted to analyze the predictive value of the model.Results The incidence of frailty in elderly MIS patients was 18.94％.There were sta-tistical differences in age,marital status,monthly income,medical expense payment,sleep condi-tion and comorbidities in the frail group(P＜0.01).The frail group had significantly lower scores of support utilization,concise health status,physiological function,body pain,general health,social function,and emotional function,and higher scores of Activities of Daily Living Scale and the Simplified Geriatric Depression Scale than the non-frail group(P＜0.05).The random forest model obtained an accuracy of 88.28％,a sensitivity of 88.24％,a specificity of 88.89％,an F1 score of 0.933,and an AUC value of 0.816.Random forest algorithm ranked the important varia-bles influencing frailty in elderly MIS patients through variable importance scores,and the top five predictors were types of basic diseases(≥2 types),sleep condition,quality of life score,self-care ability score,and personal monthly income(＜2000 Yuan).Conclusion A risk prediction model for frailty in elderly MIS patients is constructed by using random forest algorithm.The model is helpful to identify key factors of frailty as early as possible,provide empirical evidence for clinical medical staff to implement early intervention,improve the health and quality of elderly MIS patients,and prevent or delay the occurrence of frailty.

Objective: To evaluate the effect of exercise prescription intervention among patients with type 2 diabetes mellitus (T2DM), so as to provide the evidence for guiding appropriate physical activity and glycemic control in this population. Methods: In July 2023, T2DM patients managed by two community health service centers in Qingjiangpu District, Huai'an City, Jiangsu Province, were selected as the study participants and randomly assigned divided into a control group and an intervention group. The control group received routine chronic disease management under the basic public health services, while the intervention group, in addition to receiving the same routine chronic disease management, was provided with exercise prescription to guide their physical activity at baseline (T0), after 3 months of intervention (T1), and after 6 months of intervention (T2). Data on weight-related indicators, glycated hemoglobin (HbA1c), and blood lipid were collected through physical examinations and laboratory tests at T0 and after 12 months of intervention (T3). The differences in indicators between the two groups before and after the intervention were analyzed using generalized estimating equations. Results: The intervention group consisted of 197 patients, including 99 males, accounting for 50.25%. The median disease duration was 7.10 (interquartile range, 7.80) years, and 113 patients had suboptimal HbA1c levels, accounting for 57.36%. The control group included 196 patients, including 99 females, accounting for 50.51%. The median disease duration was 6.10 (interquartile range, 7.00) years, and 100 patients had suboptimal HbA1c levels, accounting for 51.02%. Before the intervention, no statistically significant differences were observed between the two groups in gender, educational level, disease duration, pharmacological treatment, smoking, alcohol consumption, and HbA1c levels (all P>0.05). In the intervention group, the proportion of participants engaging in aerobic exercise and strength training increased from 78.17% and 8.12% at T0 to 85.79% and 16.24% at T3, respectively (both P<0.05). The results of the generalized estimating equations revealed significant interactions between group and time for waist-to-hip ratio, total cholesterol (TC), and low-density lipoprotein cholesterol (LDL-C) following the intervention (all P<0.05). A statistically significant difference in waist-to-hip ratio was found between the two groups (P<0.05), with a greater reduction observed in the intervention group compared to the control group. Significant differences in TC and LDL-C levels were noted across different intervention time points (both P<0.05). Specifically, the intervention group demonstrated reductions of 0.35 mmol/L in TC and 0.42 mmol/L in LDL-C from baseline to follow-up (both P<0.05). Conclusion The 12-month exercise prescription intervention can effectively enhance exercise participation and reduce waist-to-hip ratio, TC, and LDL-C levels among patients with T2DM.

Objective:To investigate the current status of insomnia symptoms and executive function (EF) impairments among adolescents from regions with different economic development levels, and to analyze their relationship with depressive symptoms, so as to provide clues for improved depressive symptoms screening practices.Methods:This population-based cross-sectional study employed a multistage, stratified cluster random sampling method. During November 2017 to January 2018 and December 2018 to January 2019, a total of 2 495 adolescents aged 11 to 18 years were selected from Shanghai, representing a highly developed economic region, and 2 704 adolescents aged 11 to 18 years were selected from Shangrao city, Jiangxi province, representing a less developed economic region. The depressive symptoms were assessed using the short version of the 21-item depression, anxiety, and stress scale, based on which participants were categorized into groups with or without depressive symptoms. Insomnia symptoms and EF impairments were measured using a self-designed insomnia scale and the behavior rating inventory of executive function, respectively. Participants were further classified into 4 subgroups: neither insomnia nor EF impairment, EF impairment only, insomnia only, and comorbid insomnia and EF impairment. Chi-square test was used to compare the differences in basic information of adolescents from different regions. Multivariate Logistic regression models were applied to examine the associations between insomnia, EF impairment, and their combination with depressive symptoms as well as the differences in gender and school-stage among each subgroup.Results:A total of 2 305 adolescents were recruited from Shanghai (1 192 boys and 1 113 girls, 1 266 junior high school students and 1 039 senior high school students) and 2 250 adolescents from Shangrao (1 126 boys and 1 124 girls, 1 146 junior high school students and 1 104 senior high school students). The numbers of adolescents with depressive symptoms, insomnia symptoms and EF impairment in Shanghai were 460 adolescents (20.0%), 907 adolescents (39.3%), and 411 adolescents (17.8%), respectively, all of which were fewer than those in Shangrao, which were 616 adolescents (27.4%), 1 251 adolescents (55.6%), and 524 adolescents (23.3%), respectively (all P<0.001). In Shanghai, the numbers of adolescents with EF impairment only, insomnia only, and comorbid insomnia and EF impairment were 219 adolescents (9.5%), 670 adolescents (29.1%), and 237 adolescents (10.3%), respectively. And in Shangrao, the corresponding numbers were 193 adolescents (8.6%), 865 adolescents (38.4%), and 386 adolescents (17.2%), respectively. Compared to adolescents in Shanghai with neither EF impairment nor insomnia, the risk of depressive symptoms was all higher in adolescents with EF impairment only, insomnia only, and comorbid EF impairment-insomnia ( OR=2.86, 6.48, 20.10; 95% CI 1.57-5.22, 5.09-8.26, 13.66-29.58; all P<0.01). Similar results were observed in adolescents in Shangrao ( OR=3.22, 4.82, 10.91; 95% CI 1.66-6.28, 3.09-7.51, 7.26-16.40; all P<0.01). The analysis of gender and educational stage differences showed that, compared to the group neither EF impairment nor insomnia, the risk of depressive symptoms all higher in the groups with EF impairment only, insomnia only (all P<0.05), and comorbid EF impairment-insomnia, and the risk in comorbid EF impairment-insomnia group was the highest (all P<0.05). Conclusions:Compared with adolescents in regions with underdeveloped economies, those in economically developed regions had lower rates of insomnia, EF impairment, and depression. Both insomnia and EF impairment significantly increase the risk of depressive symptoms. Their coexistence confers the highest risk and therefore warrants particular attention for prevention and intervention efforts.

Objective:To explore the effects of IFN-γ on IL-8 secretion by human liver cancer cells and the impact on their malignant biological functions in vitro. Methods:HuH7 and Hep3B cells were treated with different concentrations of IFN-γ for 24 or 48 h. Changes in the cellular activity, IL-8 secretion, and the proportion of CD133 + liver cancer stem cells were evaluated using CCK8 kit and flow cytometry. Western blot was used to detect the effects of IFN-γ on the expression of several molecules such as phosphorylated protein kinase B (p-Akt), phosphorylated c-Jun N-terminal kinase (p-JNK), vimentin, and E-cadherin in the liver cancer cells. Effects of IFN-γ with or without IL-8 on the migration of liver cancer cells were detected by transwell assay. Additionally, effects of IFN-γ combined with IL-8 or IL-8 receptor inhibitor repertaxin on the differentiation of liver cancer stem cells were detected by flow cytometry. One-way analysis of variance and Tukey-Kramer test were used for statistical analysis. Results:HuH7 and Hep3B cells secreted significantly higher levels of IL-8 than normal hepatocytes LO2 ( P<0.01) and high expression level of IL-8 gene ( CXCL8) was closely correlated with the expression levels of vimentin gene ( VIMENTIN), CD133 gene ( PRCM1), PD-L1 gene ( CD274), PD-1 gene ( PDCD1), and CD163 gene ( CD163), as well as the poor prognosis of liver cancer patients ( P<0.01). IFN-γ (1-100 ng/ml) had no significant effect on the proliferative activity of HuH7 and Hep3B cells ( P>0.05), but could significantly inhibit IL-8 secretion, cell migration, CD133 + liver cancer stem cell differentiation and suspension tumor sphere formation through the Akt and JNK pathways ( P<0.01). IFN-γ combined with IL-8 could significantly reversed the inhibitory effects of IFN-γ on liver cancer cell migration, stem cell differentiation, and suspension tumor sphere formation ( P<0.01). IFN-γ in combination with repertaxin could synergistically inhibited the differentiation of CD133 + liver cancer stem cells ( P<0.01). Conclusion:IFN-γ inhibits the differentiation and migration of human liver cancer cells through the Akt/JNK-IL-8 signaling pathway, providing a new strategy for future clinical immunotherapy of liver cancer.