Objective: To explore the developmental trajectories of depression in children and adolescents and their association with family types, and to analyze the role of being an only child in the context, so as to provide a basis for early identification of mental health issues in children and adolescents. Methods: The study was a secondary analysis based on the existing database of the Jiangsu Provincial Student Common Diseases and Health Influencing Factors Monitoring and Intervention Project. A total of 11 502 students who had completed at least two measurements using the Chinese version of the Center for Epidemiologic Studies Depression Scale (CES-D) between 2022 and 2024, and had complete information on family type, gender, and age, were selected as the study subjects. Latent class trajectory modeling was used to identify depression developmental trajectories. Multinomial Logistic regression was applied to analyze the association between family type and depression developmental trajectories, and the interaction effect of family type and being an only child was tested. Results: Three types of depression developmental trajectories were identified among children and adolescents: low stable type (91.3%, 10 504 students), moderate rising type (4.3%, 500 students), and high declining type (4.3%, 498 students). Significant differences were observed among the different trajectory groups in terms of gender, age, parental education level, family type, baseline CES-D score, and baseline school type ( χ 2/H=17.48, 139.97, 19.72 , 30.77, 1 081.35, 220.81, all P <0.05). Multinomial Logistic regression analysis showed that, using the low stable type as the reference trajectory group and the nuclear family as the reference family type, after adjusting for confounding factors such as gender, age, and parental education level, single parent families ( OR=1.87, 95%CI= 1.16-3.03) and grandparent headed families ( OR=1.83, 95%CI =1.04-3.21) were significantly associated with the high declining type trajectory (both P <0.05). No significant association was found between family type and the moderate rising type trajectory (all P >0.05). The interaction effect between family type and being an only child was not statistically significant ( LRT=7.71, df=8, P =0.46). Conclusions Depressive symptoms in children and adolescents show heterogeneous developmental patterns during school age. Children and adolescents from single parent and intergenerational families are more likely to follow the high decreasing trajectory.

Objective This study reports on the obligatory parasitism of water mites Arrenurus sp. on Anopheles messeae at the Manzhouli Port, Inner Mongolia, China. Methods Duing July 2024, a survey on the mosquito diversity was conducted at the Manzhouli Port. Captured mosquitoes and their ectoparasites were identified to species level. Results A total of 1840 adult mosquitoes were collected, representing species from three genera: Culex(Cx. modestus, Cx. pipiens pallens), Aedes(Ae. dorsalis, Ae. flavidorsalis, Ae. flavescens), and Anopheles (An. messeae). Among all the mosqutioes specimens,3 out of 150 captured An. messeae were found to carry ectoparasitic mites, with number of 2,4,27 mites separately. Morphological and molecular identification reached the same result as water mites(Hydrachnidiae, Hydracrina). COI gene sequence showed 94% similarity with the closest species Arrenurus truncatellus. Conlusions Literature review suggests water mites are host-specific parasitism of mosquito species and herein with the first record of Arrenurus sp. parasiting on An. Messeae in the most high-latitude region globally.

Objective To investigate the effect and mechanism of miglitol on regulating the energy metabolism of brown adipocytes by activating UCP1 and preventing cold injury in mice after cold exposure. Methods Primary brown adipocytes were induced into mature adipocytes, the effect of miglitol on the viability of brown adipocytes was investigated by MTT method, the lipid droplet consumption level of cells after drug administration was investigated by Oil Red O staining technology, and the level of UCP1, a key protein of thermogenesis in brown adipocytes, was detected by Western blotting. The activity of anti-frostbite was investigated in cold exposure at 4 ℃ and −20 ℃. KM mice, which were randomly divided into control group, cold exposure group, miglitol group and all-trans retinoic acid group, and after 7 days of repeated administration, the body surface temperature of mice was detected by infrared thermal imaging system, the anal temperature change was detected by anal thermometer, and the expression levels of UCP1 and PGC1-α in adipose tissue were detected by immunoblotting. Results Compared with the control group, the lipid droplet consumption and UCP1 expression levels in brown adipocytes in the miglitol group were significantly increased. The levels of body surface temperature and rectal temperature increased significantly after cold exposure, and the levels of UCP1 and PGC1α in the brown adipose tissue of mice increased significantly, which indicated that the miglitol could activate the critical proteins UCP1 and PGC1α of the thermogenesis pathway, increase the thermogenesis of mice after cold exposure, and thus improve the effect of cold injury for toe swelling. Conclusion Miglitol could play a role in improving cold injury and body temperature in mice by increasing the level of UCP1 and PGC1α, which are key targets of the thermogenesis pathway to promote the thermogenesis of brown fat.

Objective To explore the networked association among the dimensions of self-efficacy in patients with rheumatoid arthritis(RA)and to identify core efficacy and bridge efficacy,and provide a basis for formulating precise nursing intervention strategies.Methods A total of 652 RA patients admitted in our hospital from September 2024 to January 2025 were enrolled with convenience sampling.The general information questionnaire and Rheumatoid Arthritis Self-Efficacy Scale(RASE)were used for assessment.Exploratory factor analysis was used to extract efficacy symptom clusters.With aid of R project,network analysis was employed to construct an association network among efficacy dimensions to calculate centrality indicators(strength,closeness,betweenness)to identify core efficacy and bridge efficacy.Results Exploratory factor analysis extracted 7 efficacy symptom clusters,with a cumulative variance contribution rate of 64.539%(P<0.001).Network analysis showed that the network density was 0.143,suggesting that there were moderate correlations among the self-efficacy dimensions."Relaxation efficacy 1(r1)"and"pain efficacy 1(a1)"had the strongest correlation(r=0.73).Interpersonal efficacy 2(i2)had the highest intensity centrality(6.88),and relaxation efficacy 3(r3)had the highest tightness(0.0125),and medication efficacy 1(m1)had the highest mediation(116),which were the core efficacy and bridge efficacy in this network group.Conclusion There are complex network-like correlations among the various dimensions of self-efficacy in RA patients.Interpersonal efficacy is the core driving factor,while relaxation and medication efficacies play the bridging role,jointly influencing the overall level of patients'self-management ability.

Creutzfeldt-Jakob disease(CJD)is a rapidly progressive and fatal neurodegenerative disorder caused by prions,with certain infectivity and iatrogenic transmission risks.With the rapid progress and application of new dia-gnostic biomarkers and detection methods,as well as the construction and improvement of surveillance and reporting systems,the detection of CJD in patients domestically and internationally has shown an increasing trend year by year.Due to its long incubation period and heterogeneity of early symptoms,early identification and diagnosis of the disease is difficult,increasing the risk of transmission within medical institutions.Currently,there is a lack of con-sensus on the infection prevention and control of CJD.In order to timely identify and diagnose CJD as well as effec-tively block its transmission in medical institutions,this consensus summarizes 15 clinical concerns and formulates 24 specific recommendations based on the latest domestic and international research findings and clinical evidence,as well as combines with clinical practice,aiming to standardize healthcare-associated infection prevention and control measures for CJD and reduce its transmission risk in medical institutions.

Objective:To evaluate the clinical efficacy of Tianma Xionglin Zhixuan Tablets in treating hypertension patients with liver yang hyperactivity or comorbid phlegm-stasis syndrome and explore its therapeutic mechanisms through plasma metabolomics.Methods:Thirty-six hypertension patients(4 dropouts)diagnosed with liver yang hyperactivity or phlegm-stasis syndrome were enrolled as the treatment group from June 2022 to September 2023 at the First Affiliated Hospital of Hunan University of Chinese Medicine,while 30 healthy volunteers with balanced constitutions were recruited as the blank group.Plasma samples were collected from patients pre-and post-treatment and from healthy volunteers.Clinical outcomes,including syndrome scores,office blood pressure(BP),and 24-hour ambulatory BP,were recorded.Plasma metabolomic profiling was performed using liquid chromatography-mass spectrometry(LC-MS).Results:Compared with baseline,Tianma Xionglin Zhixuan Tablets significantly reduced traditional Chinese medicine syndrome scores(P＜0.01),office systolic/diastolic BP(P＜0.01),and 24-hour ambulatory BP parameters(24-hour mean BP,daytime/nighttime mean BP;all P＜0.01).Metabolomic analysis identified 45 differential metabolites between the blank group and pretreatment patients,and 64 metabolites altered post-treatment(VIP＞1,P＜0.05).Enrichment analysis of 16 overlapping endogenous metabolites revealed that Tianma Xionglin Zhixuan Tablets primarily modulated arachidonic acid metabolism and sphingolipid metabolism pathways.Conclusion:Tianma Xionglin Zhixuan Tablets demonstrates significant clinical efficacy in hypertension patients with liver yang hyperactivity or phlegm-stasis syndrome,potentially mediated through regulation of arachidonic acid and sphingolipid metabolism.

Objective:To evaluate the value of ultrasound radiomics combined with machine learning for early diagnosis of seronegative Hashimoto’s thyroiditis (SN-HT) .Methods:This retrospective study included 164 patients from Liaoning Provincial People’s Hospital , Lixin County People’s Hospital, Linghai Dalinghe Hospital, Fengcheng Phoenix Hospital, who underwent thyroidectomy for solitary nodules with normal thyroid function between Nov. 2016 and Jan. 2024. Postoperative pathology confirmed Hashimoto’s thyroiditis (HT) in some cases, who were further categorized into antibody-positive and antibody-negative groups based on serum antibody status. Patients without Hashimoto’s thyroiditis served as the control group. A total of 298 ultrasound images were analyzed. Radiomics features were extracted from hypoechoic non-nodular areas within 0.5 cm surrounding the tumor. Two senior pathologists and two senior ultrasound physicians independently assessed lymphocytic infiltration, eosinophilic changes of follicular epithelium, and the proportion of hypoechoic areas in pathology and ultrasound images, respectively. A machine learning model, CCH-NET, was developed using linear regression and t-distributed stochastic neighbor embedding (t-SNE) techniques. The dataset was divided into a training set (80%) and a validation set (20%) to compare the diagnostic accuracy of CCH-NET with that of senior ultrasound physicians. Results:In internal validation, CCH-NET achieved a diagnostic accuracy of 88.89% for both antibody-positive and antibody-negative groups, significantly higher than the 66.67% accuracy of senior ultrasound physicians ( P<0.01). In external validation, CCH-NET achieved 75.00% and 66.67% accuracy for the two groups, compared to 50.00% by senior ultrasound physicians. For the control group, both methods achieved 93.33% accuracy. The AUC of CCH-NET was 0.848, outperforming senior ultrasound physicians (0.681) ,demonstrating superior diagnostic performance. Conclusion:The radiomics-based CCH-NET model, using non-nodular hypoechoic areas as a specific indicator, can accurately identify early SN-HT in euthyroid patients. It significantly outperforms senior ultrasound physicians, improving diagnostic accuracy and reducing missed diagnoses.

Objective:To explore the trend of influenza positive rate in Beijing by using classic autoregressive integrated moving average (ARIMA) model, autoregressive integrated moving average model with exogenous variables (ARIMAX) and vector autoregression model (VAR) to compare the performance of three models in influenza prediction and select the most suitable one for Beijing.Methods:The weekly positive rate of influenza virus nucleic acid test and meteorological data in Beijing from week 1 of 2013 to week 40 of 2024 were collected. The data were divided into four groups with expanding training sets and corresponding testing sets. The training set of the first group was from week 1 of 2013 to week 40 of 2016, and the testing set was from week 41 of 2016 to week 40 of 2017. Subsequent groups extended the training set by one year each time. Data from 2020 to 2023 were excluded due to COVID-19 pandemic. The fourth group used data from the week 1 of 2013 to week 40 of 2023 for training and from the week 41 of 2023 to week 40 of 2024 for testing.Results:The incidence of influenza had seasonality in Beijing with higher incidence in winter and spring. The positive rate of influenza virus was positively correlated with the weekly average atmospheric pressure ( r=0.482, P<0.001) and weekly average wind speed ( r=0.003, P=0.034), and negatively correlated with the weekly average temperature ( r=-0.541, P<0.001). The ARIMAX model incorporating meteorological factors had the best prediction performance, with test set's root mean square error ( RMSE) of 0.115 3 and mean absolute error ( MAE) of 0.076 7 (the RMSE and MAE values for ARIMA and VAR models were 0.117 1 and 0.163 8, and 0.078 6 and 0.122 3, respectively). The prediction results of the optimal model showed that the positive rate of influenza virus would continue to rise in Beijing after October 2024 and reach peak in the second week of 2025, but the peak positive rate would be lower than that of previous influenza season. Conclusions:Compared with the ARIMA model and the VAR model,the ARIMAX model which used meteorological parameters is more suitable for prediction of long-term influenza trend in Beijing. The influenza trend peak was predicted to occur in the second week of 2025, but lower than that in previous influenza season.

Objective:To analyze the colonization rate and molecular types of Staphylococcus aureus (SA) on the tracheotomy wounds of neonates at early postoperative stage in neonatal intensive care unit (NICU). Methods:This was a case series study. Patients who were admitted and underwent tracheotomy in NICU of Beijing Children′s Hospital, Capital Medical University from January 1 st 2020 to December 31 st 2023 were enrolled. Swabs on the skin around the incision or on the nasal mucosa were collected and cultured at 24, 72 and 168 h after operation. Coagulase test and Staphytect Plus kits were used for SA identification. The nuc gene amplification and molecular types of SA were assessed by PCR. The patients were divided into SA colonization group and non-colonization group based on the presence or absence of SA colonization, and into infection group and non-infection group based on the presence or absence of infection. Demographic data, hospitalization information, colonization and infection status of SA were collected from the digital medical record system of the hospital. Differences between groups were analyzed using the independent sample t test or Fisher exact test. Results:Totally 19 patients were enrolled, among whom 13 were male. The gestation age was 39.0 (38.1, 40.0) weeks, and the birth weight was 3 150 (2 600, 3 400) g. Tracheotomy was done at 8.2 (4.1, 19.6) days after diagnosis and indication confirmed. Corrected gestational age of patients on the operation day was 43.6 (42.2, 45.4) weeks. The NICU stay time was (34.0±3.1) days. SA colonization was confirmed around the incision of 8 patients. Out of the 18 strains of colonized bacteria, 10 were methicillin-resistant Staphylococcus aureus (MRSA). The most common molecular type of MRSA was ST59-SCCmec Ⅳ-t437 strain (8 strains). A total of 10 patients presented typical clinical manifestations of bacterial infection at the lungs, 3 patients in the blood stream and 2 patients in the central nervous system. Among 10 patients with bacterial infection, 3 patients were MRSA positive by boby fluid culture and affected by the ST59-SCCmec Ⅳ-t437 strain. The infection rate was different between patients with or without SA colonization on the tracheotomy incision (7/8 vs. 3/11, P=0.020). Conclusions:The colonization rate and infection rate are high on the tracheotomy incision in neonates. The major type is MRSA, and the most common molecular strain is ST59-SCCmec Ⅳ-t437 .

Objective:To evaluate the value of ultrasound radiomics combined with machine learning for early diagnosis of seronegative Hashimoto’s thyroiditis (SN-HT) .Methods:This retrospective study included 164 patients from Liaoning Provincial People’s Hospital , Lixin County People’s Hospital, Linghai Dalinghe Hospital, Fengcheng Phoenix Hospital, who underwent thyroidectomy for solitary nodules with normal thyroid function between Nov. 2016 and Jan. 2024. Postoperative pathology confirmed Hashimoto’s thyroiditis (HT) in some cases, who were further categorized into antibody-positive and antibody-negative groups based on serum antibody status. Patients without Hashimoto’s thyroiditis served as the control group. A total of 298 ultrasound images were analyzed. Radiomics features were extracted from hypoechoic non-nodular areas within 0.5 cm surrounding the tumor. Two senior pathologists and two senior ultrasound physicians independently assessed lymphocytic infiltration, eosinophilic changes of follicular epithelium, and the proportion of hypoechoic areas in pathology and ultrasound images, respectively. A machine learning model, CCH-NET, was developed using linear regression and t-distributed stochastic neighbor embedding (t-SNE) techniques. The dataset was divided into a training set (80%) and a validation set (20%) to compare the diagnostic accuracy of CCH-NET with that of senior ultrasound physicians. Results:In internal validation, CCH-NET achieved a diagnostic accuracy of 88.89% for both antibody-positive and antibody-negative groups, significantly higher than the 66.67% accuracy of senior ultrasound physicians ( P<0.01). In external validation, CCH-NET achieved 75.00% and 66.67% accuracy for the two groups, compared to 50.00% by senior ultrasound physicians. For the control group, both methods achieved 93.33% accuracy. The AUC of CCH-NET was 0.848, outperforming senior ultrasound physicians (0.681) ,demonstrating superior diagnostic performance. Conclusion:The radiomics-based CCH-NET model, using non-nodular hypoechoic areas as a specific indicator, can accurately identify early SN-HT in euthyroid patients. It significantly outperforms senior ultrasound physicians, improving diagnostic accuracy and reducing missed diagnoses.