Objective: To investigate the correlation between social jetlag and psychological behavior in upper primary school students,so as to provide reference for sleep health promotion in primary school students. Methods: From April to June 2024, a survey was conducted among 4 341 fourth and fifth grade students from 9 public primary schools in a district in Beijing. Sleep patterns were assessed using a self designed questionnaire, while psychological behavior was evaluated using the Strengths and Difficulties Questionnaire (SDQ)(parent version). A generalized estimating equation (GEE) model was used to examine the association between different levels of social jetlag and psychological behavior problem scores in primary school students. Results: The proportions of students with social jetlag of <1.0, 1.0-<2.0, and ≥2.0 h were 57.6%, 30.6%, and 11.8%, respectively. The GEE model analysis found that after adjusting for covariates, compared with primary school students with social jetlag of <1.0 h, those with 1.0 -<2.0 and ≥2.0 h had higher scores for internalizing behavior problems [ β (95% CI ) =0.23(0.05-0.41)，0.28(0.02-0.54), P < 0.01]. Primary school students with ≥2.0 h of social jetlag had higher scores for externalizing behavior problems [ β (95% CI )=0.42 (0.13-0.71)， P <0.01]. Among boys and primary school students with an average nighttime sleep duration of ≥9 h, comparied with social jetlag of <1.0 h,those with sucial jetlag 1.0-<2.0 h had higher scores on internalizing and externalizing behavior problems[ β (95% CI )=0.32(0.07-0.56),0.51 (0.11-0.90), 0.26 (0.06-0.46)，0.58 (0.25-0.91), P <0.05]. Conclusions Greater social jetlag may be a risk factor for internalizing and externalizing behavior problems in upper primary school students. Reducing social jetlag may help decrease the occurrence of psychological behavior problems in primary school students.

Background: The genetic basis for hyperglycaemia in pregnancy remain unclear. This study aimed to uncover the genetic determinants of gestational diabetes mellitus (GDM) and investigate their applications. Methods: We performed a meta-analysis of genome-wide association studies (GWAS) for GDM in Chinese women (464 cases and 1,217 controls), followed by de novo replications in an independent Chinese cohort (564 cases and 572 controls) and in silico replication in European (12,332 cases and 131,109 controls) and multi-ethnic populations (5,485 cases and 347,856 controls). A polygenic risk score (PRS) was derived based on the identified variants. Results: Using the genome-wide scan and candidate gene approaches, we identified four susceptibility loci for GDM. These included three previously reported loci for GDM and type 2 diabetes mellitus (T2DM) at MTNR1B (rs7945617, odds ratio [OR], 1.64; 95% confidence interval [CI],1.38 to 1.96]), CDKAL1 (rs7754840, OR, 1.33; 95% CI, 1.13 to 1.58), and INS-IGF2-KCNQ1 (rs2237897, OR, 1.48; 95% CI, 1.23 to 1.79), as well as a novel genome-wide significant locus near TBR1-SLC4A10 (rs117781972, OR, 2.05; 95% CI, 1.61 to 2.62; Pmeta=7.6×10-9), which has not been previously reported in GWAS for T2DM or glycaemic traits. Moreover, we found that women with a high PRS (top quintile) had over threefold (95% CI, 2.30 to 4.09; Pmeta=3.1×10-14) and 71% (95% CI, 1.08 to 2.71; P=0.0220) higher risk for GDM and abnormal glucose tolerance post-pregnancy, respectively, compared to other individuals. Conclusion Our results indicate that the genetic architecture of glucose metabolism exhibits both similarities and differences between the pregnant and non-pregnant states. Integrating genetic information can facilitate identification of pregnant women at a higher risk of developing GDM or later diabetes.

ObjectiveTo investigate the relationship between the non-fasting triglyceride and glucose （TyG） index and hyperglycemia in pregnancy during the third trimester in high altitudes. MethodsThis study selected clinical and laboratory data of 774 Tibetan singleton pregnant women who delivered at Chaya People's Hospital of Qamdo city in Xizang autonomous region， from January 2023 to April 2025. The non-fasting TyG index was calculated from non-fasting triglyceride （TG） and random plasma glucose （PG）. Based on the tertiles of the non-fasting TyG index values， the individuals were split into three groups （corresponding to non-fasting TyG index of 8.89 and 9.21， respectively）. The baseline clinical characteristics， lipid levels and the occurrence of developing hyperglycemia in pregnancy were compared among the three groups. Statistical analyses were performed using ANOVA， Kruskal-Wallis H test， Chi-square test， or Fisher exact test and the relationship between the non-fasting TyG index and hyperglycemia in pregnancy were examined using multivariate logistic regression models and curve fitting. ResultsA total of 774 Tibetan singleton pregnant women were included， with a average age of 27.3 ± 6.1 years， a pre-delivery body mass index （Pre-BMI） of （25.2±2.3）kg/m² ， a proportion of 26.7% （207/774） primigravid women， the mean non-fasting TyG index was 9.1 ± 0.4。Thirty pregnant women were diagnosed with hyperglycemia in pregnancy， with a detection rate of 3.9% （30/774）. Statistically significant differences in serum total cholesterol （TC）， TG， low-density lipoprotein cholesterol （LDL-C） and high-density lipoprotein cholesterol （HDL-C） levels were identified when comparing different non-fasting TyG groups （all P values <0.05）. Subsequent trend test analysis indicated that the levels of TC， TG， LDL-C， and PG gradually increased with elevated the non-fasting TyG index （ F_{trend TC}=95.61， P<0.001； F_{trend TG}=1 051.91， P<0.001； F_{trend LDL-C} = 97.20， P < 0.001； F_{trend TG}=195.20； P<0.001）. After adjustment for maternal age， pre-delivery BMI， altitude， TC， LDL-C， and HDL-C， multivariate Logistic regression models revealed independent positive associations between non-fasting TyG index and hyperglycemia in pregnancy （Model 1： OR=2.72， 95% CI： 1.13-6.53， P=0.026； Model 2： OR=2.56， 95% CI： 1.01-6.50， P=0.048； Model 3： OR=2.72， 95% CI： 1.06-6.97， P=0.037； Model 4： OR=4.02， 95% CI： 1.42-11.40， P=0.009） and the incident of hyperglycemia in pregnancy showed an increasing tendency as increasing with the non-fasting TyG index， however， this association did not statistical significance （P _trend >0.05）. Curve fitting by restricted cubic splines （RCS） were used to assess linearity between non-fasting TyG and hyperglycemia in pregnancy， and there was a linear dose-response relationship between non-fasting TyG and hyperglycemia in pregnancy （P _{for non-linear} = 0.515）. ConclusionNon-fasting TyG index in the third trimester is a risk factor for hyperglycemia in pregnancy among the Tibetan singleton pregnant women at high altitudes and there was a possible linear dose-response relationship between the non-fasting TyG index and hyperglycemia in pregnancy.

Background: The genetic basis for hyperglycaemia in pregnancy remain unclear. This study aimed to uncover the genetic determinants of gestational diabetes mellitus (GDM) and investigate their applications. Methods: We performed a meta-analysis of genome-wide association studies (GWAS) for GDM in Chinese women (464 cases and 1,217 controls), followed by de novo replications in an independent Chinese cohort (564 cases and 572 controls) and in silico replication in European (12,332 cases and 131,109 controls) and multi-ethnic populations (5,485 cases and 347,856 controls). A polygenic risk score (PRS) was derived based on the identified variants. Results: Using the genome-wide scan and candidate gene approaches, we identified four susceptibility loci for GDM. These included three previously reported loci for GDM and type 2 diabetes mellitus (T2DM) at MTNR1B (rs7945617, odds ratio [OR], 1.64; 95% confidence interval [CI],1.38 to 1.96]), CDKAL1 (rs7754840, OR, 1.33; 95% CI, 1.13 to 1.58), and INS-IGF2-KCNQ1 (rs2237897, OR, 1.48; 95% CI, 1.23 to 1.79), as well as a novel genome-wide significant locus near TBR1-SLC4A10 (rs117781972, OR, 2.05; 95% CI, 1.61 to 2.62; Pmeta=7.6×10-9), which has not been previously reported in GWAS for T2DM or glycaemic traits. Moreover, we found that women with a high PRS (top quintile) had over threefold (95% CI, 2.30 to 4.09; Pmeta=3.1×10-14) and 71% (95% CI, 1.08 to 2.71; P=0.0220) higher risk for GDM and abnormal glucose tolerance post-pregnancy, respectively, compared to other individuals. Conclusion Our results indicate that the genetic architecture of glucose metabolism exhibits both similarities and differences between the pregnant and non-pregnant states. Integrating genetic information can facilitate identification of pregnant women at a higher risk of developing GDM or later diabetes.

Background: The genetic basis for hyperglycaemia in pregnancy remain unclear. This study aimed to uncover the genetic determinants of gestational diabetes mellitus (GDM) and investigate their applications. Methods: We performed a meta-analysis of genome-wide association studies (GWAS) for GDM in Chinese women (464 cases and 1,217 controls), followed by de novo replications in an independent Chinese cohort (564 cases and 572 controls) and in silico replication in European (12,332 cases and 131,109 controls) and multi-ethnic populations (5,485 cases and 347,856 controls). A polygenic risk score (PRS) was derived based on the identified variants. Results: Using the genome-wide scan and candidate gene approaches, we identified four susceptibility loci for GDM. These included three previously reported loci for GDM and type 2 diabetes mellitus (T2DM) at MTNR1B (rs7945617, odds ratio [OR], 1.64; 95% confidence interval [CI],1.38 to 1.96]), CDKAL1 (rs7754840, OR, 1.33; 95% CI, 1.13 to 1.58), and INS-IGF2-KCNQ1 (rs2237897, OR, 1.48; 95% CI, 1.23 to 1.79), as well as a novel genome-wide significant locus near TBR1-SLC4A10 (rs117781972, OR, 2.05; 95% CI, 1.61 to 2.62; Pmeta=7.6×10-9), which has not been previously reported in GWAS for T2DM or glycaemic traits. Moreover, we found that women with a high PRS (top quintile) had over threefold (95% CI, 2.30 to 4.09; Pmeta=3.1×10-14) and 71% (95% CI, 1.08 to 2.71; P=0.0220) higher risk for GDM and abnormal glucose tolerance post-pregnancy, respectively, compared to other individuals. Conclusion Our results indicate that the genetic architecture of glucose metabolism exhibits both similarities and differences between the pregnant and non-pregnant states. Integrating genetic information can facilitate identification of pregnant women at a higher risk of developing GDM or later diabetes.

Background: The genetic basis for hyperglycaemia in pregnancy remain unclear. This study aimed to uncover the genetic determinants of gestational diabetes mellitus (GDM) and investigate their applications. Methods: We performed a meta-analysis of genome-wide association studies (GWAS) for GDM in Chinese women (464 cases and 1,217 controls), followed by de novo replications in an independent Chinese cohort (564 cases and 572 controls) and in silico replication in European (12,332 cases and 131,109 controls) and multi-ethnic populations (5,485 cases and 347,856 controls). A polygenic risk score (PRS) was derived based on the identified variants. Results: Using the genome-wide scan and candidate gene approaches, we identified four susceptibility loci for GDM. These included three previously reported loci for GDM and type 2 diabetes mellitus (T2DM) at MTNR1B (rs7945617, odds ratio [OR], 1.64; 95% confidence interval [CI],1.38 to 1.96]), CDKAL1 (rs7754840, OR, 1.33; 95% CI, 1.13 to 1.58), and INS-IGF2-KCNQ1 (rs2237897, OR, 1.48; 95% CI, 1.23 to 1.79), as well as a novel genome-wide significant locus near TBR1-SLC4A10 (rs117781972, OR, 2.05; 95% CI, 1.61 to 2.62; Pmeta=7.6×10-9), which has not been previously reported in GWAS for T2DM or glycaemic traits. Moreover, we found that women with a high PRS (top quintile) had over threefold (95% CI, 2.30 to 4.09; Pmeta=3.1×10-14) and 71% (95% CI, 1.08 to 2.71; P=0.0220) higher risk for GDM and abnormal glucose tolerance post-pregnancy, respectively, compared to other individuals. Conclusion Our results indicate that the genetic architecture of glucose metabolism exhibits both similarities and differences between the pregnant and non-pregnant states. Integrating genetic information can facilitate identification of pregnant women at a higher risk of developing GDM or later diabetes.

Objective: To explore the association of screening myopia and sitting posture habits as well as screen viewing distance among primary school students, providing a scientific basis for myopia prevention and intervention among primary school students. Methods: From April to June 2024, a convenient sampling method was used to enroll 1 394 fourth grade students from four primary schools in a district of Beijing for vision examinations and questionnaire surveys. Logistic regression models were employed to analyze the relationship of screening myopia detection and sitting posture habits as well as viewing distance. Results: The screening myopia prevalence among primary school students was 63.8%. About 13.1% of students self reported poor sitting posture, and 47.1% selfreported a viewing distance of ≤20 cm. After adjusting for covariates including age, gender, school, sleep quality, parental myopia status, physical fitness level, daily high intensity physical activity, weekend outdoor activity time and types of after school services, Logistic regression analysis showed that students with poor sitting posture were more likely to have screening myopia than those with normal sitting posture ( OR =1.73,95% CI =1.03-2.92); students with a viewing distance of ≤20 cm were more likely to have screening myopia than those with a viewing distance of >20 cm( OR =1.32, 95% CI =1.02-1.71)( P <0.05). The association between sitting posture and screening myopia was more significant among boys( OR =2.00, 95% CI =1.03-3.88, P < 0.05 ). A multiplicative interaction was observed between sitting posture and viewing distance. Compared to primary school students with normal posture and a viewing distance of >20 cm, those with poor posture and a viewing distance of >20 cm were more likely to have screening myopia ( OR =1.82, 95% CI =1.12-2.96， P <0.05). Conclusions Both sitting posture habits and screen viewing distance are related to screening myopia in primary school students. Poor sitting posture poses a higher risk than screen distance, and the two factors exhibit an interactive effect on myopia risk.

Given the increasing concern regarding antibacterial resistance, the antimicrobial properties of naphthoquinones have recently attracted significant attention. While 1,4-naphthoquinone and its derivatives have been extensively studied, the antibacterial properties of 5,8-dihydroxy-1,4-naphthoquinone derivatives remain relatively unexplored. This study presents a comprehensive in vitro and in vivo analysis of the antibacterial activity of 35 naturally sourced and chemically synthesized derivatives of 5,8-dihydroxy-1,4-naphthoquinone. Kirby-Bauer antibiotic testing identified three compounds with activity against methicillin-resistant Staphylococcus aureus (MRSA), with one compound (PNP-02) demonstrating activity comparable to vancomycin in minimum inhibitory concentration, minimum bactericidal concentration (MBC), and time-kill assays. Microscopic and biochemical analyses revealed that PNP-02 adversely affects the cell wall and cell membrane of MRSA. Mechanistic investigations, including proteomic sequencing analyses, Western blotting, and RT-qPCR assays, indicated that PNP-02 compromises cell membrane integrity by inhibiting arginine biosynthesis and pyrimidine metabolism pathways, thereby increasing membrane permeability and inducing bacterial death. In an in vivo mouse model of skin wound healing, PNP-02 exhibited antibacterial efficacy similar to vancomycin. The compound demonstrated low toxicity to cultured human cells and in hemolysis assays and remained stable during serum incubation. These findings suggest that PNP-02 possesses promising bioactivity against MRSA and represents a potential novel antibacterial agent.
Methicillin-Resistant Staphylococcus aureus/genetics* ; Anti-Bacterial Agents/chemistry* ; Naphthoquinones/administration & dosage* ; Animals ; Microbial Sensitivity Tests ; Mice ; Humans ; Staphylococcal Infections/microbiology* ; Molecular Structure

Background The residues of pharmaceutical and personal care products (PPCPs) in aquatic environments have become an increasingly prominent urban pollution issue, attracting widespread attention. The analysis of PPCPs pollution in water environments holds profound implications in Zhengzhou, a strategically important city in central China. Objective To analyze the pollution characteristics of PPCPs, such as antidepressants and antibiotics, in rivers of Zhengzhou and assess associated ecological risk. Methods Water samples were collected from three rivers of Zhengzhou, and 13 PPCPs (5 antibiotics and 8 antidepressants) were analyzed quantitatively by high performance liquid chromatography-triple quadrupole mass spectrometry (HPLC-MS/MS) after automatic solid phase extraction. Risk quotient (RQ) was applied to assess ecological risk of PPCPs with high concentration. Results The primary antibiotics pollutants were norfloxacin and ofloxacin, both with a detection rate of 100%. Among antidepressants, venlafaxine and citalopram showed the highest detection rates at 92.3% and 88.5%, respectively. The detected antibiotics with the highest average concentrations included ofloxacin and sulfamethoxazole with concentrations of 99.8 ng·L⁻¹and 96.2 ng·L⁻¹, respectively, while antidepressants venlafaxine and citalopram were detected with the highest average concentrations of 15.2 ng·L⁻¹and 1.35 ng·L⁻¹, respectively. The inter-river comparisons revealed statistically significant differences in contaminant loads (P<0.05). The sums of average PPCP concentrations at sampling points in the Jialu River and Suoxu River were 83.4 ng·L⁻¹ and 100.4 ng·L⁻¹, respectively. The Xiaoqing River exhibited higher pollution levels than both the Jialu and Suoxu Rivers, with a total average concentration of 478.4 ng·L⁻¹, where ofloxacin and sulfamethoxazole were identified as the predominant pollutants. The results of ecological risk assessment indicated the RQ contributed by sulfamethoxazole ranged between 0.50−0.95 in the Xiaoqing River, suggesting a controllable risk but requiring prioritized mitigation strategies. The RQ values of norfloxacin were distributed within the range of 0.10-0.30, indicating a moderate ecological risk. The RQ values for ofloxacin and venlafaxine remained below 0.10, indicating a lower risk level. Conclusion PPCPs contamination is positive in the rivers of Zhengzhou, and sulfamethoxazole and ofloxacin are the primary cantaminants. The Xiaoqing River exhibits the highest pollution levels. The initial risk assessment show that sulfamethoxazole and norfloxacin pose potential ecological risks, requiring prioritized contamination management.

Objective: To evaluate the influence of electronic sports games on children s acquisition of basic motor skills, so as to provide assistance for childrens acquisition of basic motor skills in the context of digital society. Methods: Computer searches were conducted on CNKI, Web of Science, Cochrane Library and PubMed databases from March 2012 to March 2022. Methodological quality of included studies was evaluated using the Cochrane bias risk assessment tool RoB 2 and the extension tools RoB 2 Cluster and ROBINS-I. Publication bias assessment, heterogeneity test, subgroup analysis and Meta analysis were performed using RevMan 5.3. Results: A total of 12 studies included 897 participants, 7 randomized controlled trials, 2 cohort randomized controlled trials and 3 non randomized trials. Among them, 2 items had a low risk of bias, 8 items had certain risks and 2 items had a high risk of bias. Measures of basic motor skills in children from 12 studies included object control skills, motor skills, coordination, agility and balance. The results of Meta analysis showed that electronic sports games had a positive effect on children s acquisition of basic motor skills ( SMD=0.81, 95%CI=0.46-1.17, P <0.05). Conclusion Children can generate positive interactive communication behavior through physical activity and digital screen, and then promote the development of basic motor skills.