Objective: To explore the impact of sleep quality, experience of childhood maltreatment, and their interaction on depressive symptoms among middle school students, so as to provide the reference for early intervention of depressive symptoms among middle school students. Methods: From September to December 2023, a questionnaire survey was conducted among 1 231 students from two secondary schools in Harbin, Heilongjiang Province by a convenient sampling method. The survey included general demographic information, Childhood Trauma Questionnaire Short Form, Pittsburgh Sleep Quality Index and Short Version of Center for Epidemiological Studies Depression Scale. The Chi square test was used to analyze the differences in depressive symptom, sleep quality and childhood maltreatment among students with different demographic characteristics. Correlation analysis was conducted using Logistic regression, and interaction analysis was performed by both additive and multiplicative interaction models. Results: The detection rate of depressive symptoms among middle school students was 22.7%, and the rate for high school students (35.2%) was significantly higher than that for middle school students (17.0%) ( χ 2=50.35, P <0.01). The detection rates of depressive symptoms among middle school students with a history of childhood maltreatment and poor sleep quality were 45.8% and 44.0%, respectively. Multivariate Logistic regression analysis showed that compared to students without a history of childhood maltreatment, students with a history of childhood maltreatment had a higher risk of depressive symptoms ( OR =4.49，95% CI =3.31~ 6.09 , P <0.01);students with poor sleep quality had a higher risk of depressive symptoms than students with good sleep quality ( OR = 5.99，95% CI =4.37~8.22, P <0.01).The interaction results showed that the presence of childhood maltreatment and poor sleep quality had an additive interaction on the occurrence of depression in middle school students. Compared with students without childhood maltreatment and having good sleep quality, students with childhood maltreatment and poor sleep quality had a 22.49 times higher risk of developing depression ( OR =22.49，95% CI =14.22~35.59, P <0.01). Conclusion Depressive symptoms among middle school students are associated with childhood maltreatment and poor sleep quality, and there is an additive interaction between childhood maltreatment and poor sleep quality on the impact of depressive symptoms.

ObjectivePatients with hepatic glycogen storage disease（GSD）have recurrent episodes of hypoglycemia. This study aimed to investigate and analyze blood glucose and biochemical indicators in pediatric patients with hepatic GSD， thus provide data support for hypoglycemia prevention and its clinical management. MethodsA cross-sectional field study was conducted among patients with hepatic GSD treated in the Department of Pediatrics of Guangdong Provincial People's Hospital on July 14， 2024. We collected the peripheral blood samples of the patients and their healthy family controls on site， then analyzed and compared their blood glucose and biochemical indicators. ResultsOf the 44 patients with hepatic GSD， there were 34 males and 10 females， including GSD Ib（n =14）， GSD Ia（n=15）， GSD Ⅲ（n=2）， GSD Ⅵ（n=7）and GSD Ⅸ（n=6）. The average age was 7.60（5.08-11.98）years. All patients were on uncooked cornstarch（UCCS）therapy. Of the patients， 77.3%（34/44）had hepatomegaly， 61.4%（27/44）had recurrent hypoglycemia， 61.4%（27/44）had blood glucose ≤ 3.9 mmol/L， 18.2%（8/44）had blood glucose ≤ 2.8 mmol/L， and none of the 8 cases was GSD Ib. The lowest blood glucose level was 1.19 mmol/L and no episodes of hypoglycemia occurred. Of the family control subjects， 65.9%（29/44）had blood glucose ≤ 3.9 mmol/L. There was no significant difference in hypoglycemia prevalence between hepatic GSD group and control group（P=0.658）. The hepatic GSD patients had hyperlactacemia， hyperuricemia and hypercholesterolemia prevalence rates of 65.9%， 45.5% and 9.1%， respectively， as compared with 18.2%， 43.2% and 15.9%， respectively， for the family control subjects. No significant difference was found in the prevalence rates of hyperuricemia and hypercholesterolemia between the two groups（P=0.830 and P=0.334， respectively）. ConclusionsAsymptomatic hypoglycemia is common in patients with hepatic GSD， especially in non-GSD-Ib patients. It is necessary to optimize the diet management of UCCS， conduct dynamic blood glucose monitoring and follow a light diet， so as to decrease hyperuricemia and hypercholesterolemia， avoid and reduce the serious adverse reactions and complications caused by severe hypoglycemia.

In this study, we constructed a GLP-2R-HEK293 cell line and established a method for the determination of the in vitro biological activity of teduglutide based on HTRF, after optimizing experimental conditions and methodological verification. We also carried out relative potency detection of teduglutide pharmaceutical products using this method. The result showed that there was a quantitative-efficient relationship between the teduglutide activity and cAMP contents in GLP-2R-HEK293 cells, which conformed to four-parameter model. Method verification results of five concentrations of teduglutide (64%, 80%, 100%, 125% and 156%) met the requirements of the General Rules of Chinese Pharmacopoeia, 2020 edition, Volume IV (9401). We then analyzed the relative potency of three batches of teduglutide drug substances and three batches of drug products. The linearity, regression and parallelism of the obtained curves all fit the system suitability requirements. The relative potency of six batches of teduglutide was from 83% to 105%. In summary, the biological activity detection method established in this study was accurate, precise, simple and time-saving, which can be used for quality control of teduglutide pharmaceutical products.

Objective: Previous studies have discovered a correlation between cigarette smoking and cortical thickness and surface area, but the causal relationship remains unclear. The objective of this investigation is to scrutinize the causal association between them. Methods: To derive summary statistics from a genome-wide association study (GWAS) on cortical thickness, surface area, and four smoking behaviors: 1) age of initiation of regular smoking (AgeSmk); 2) smoking initiation (SmkInit); 3) smoking cessation (SmkCes); 4) cigarettes per day (CigDay). Linkage disequilibrium score regression (LDSC) was employed to examine genetic association analysis. Furthermore, for traits with significant genetic associations, Mendelian randomization (MR) analyses were conducted. Results: The LDSC analysis revealed nominal genetic correlations between AgeSmk and right precentral surface area, left caudal anterior cingulate surface area, left cuneus surface area, left inferior parietal surface area, and right caudal anterior cingulate thickness, as well as between CigDay and left caudal middle frontal surface area, between SmkCes and left entorhinal thickness, and between SmkInit and left rostral anterior cingulate surface area, right rostral anterior cingulate thickness, and right superior frontal thickness (rg=-0.36–0.29, p<0.05). MR analysis showed a unidirectional causal association between left caudal middle frontal surface area and CigDay (βIVW=0.056, pBonferroni=2×10-4). Conclusion Left caudal middle frontal surface area has the potential to serve as a significant predictor of smoking behavior.

Objective: Previous studies have discovered a correlation between cigarette smoking and cortical thickness and surface area, but the causal relationship remains unclear. The objective of this investigation is to scrutinize the causal association between them. Methods: To derive summary statistics from a genome-wide association study (GWAS) on cortical thickness, surface area, and four smoking behaviors: 1) age of initiation of regular smoking (AgeSmk); 2) smoking initiation (SmkInit); 3) smoking cessation (SmkCes); 4) cigarettes per day (CigDay). Linkage disequilibrium score regression (LDSC) was employed to examine genetic association analysis. Furthermore, for traits with significant genetic associations, Mendelian randomization (MR) analyses were conducted. Results: The LDSC analysis revealed nominal genetic correlations between AgeSmk and right precentral surface area, left caudal anterior cingulate surface area, left cuneus surface area, left inferior parietal surface area, and right caudal anterior cingulate thickness, as well as between CigDay and left caudal middle frontal surface area, between SmkCes and left entorhinal thickness, and between SmkInit and left rostral anterior cingulate surface area, right rostral anterior cingulate thickness, and right superior frontal thickness (rg=-0.36–0.29, p<0.05). MR analysis showed a unidirectional causal association between left caudal middle frontal surface area and CigDay (βIVW=0.056, pBonferroni=2×10-4). Conclusion Left caudal middle frontal surface area has the potential to serve as a significant predictor of smoking behavior.

Objective: Previous studies have discovered a correlation between cigarette smoking and cortical thickness and surface area, but the causal relationship remains unclear. The objective of this investigation is to scrutinize the causal association between them. Methods: To derive summary statistics from a genome-wide association study (GWAS) on cortical thickness, surface area, and four smoking behaviors: 1) age of initiation of regular smoking (AgeSmk); 2) smoking initiation (SmkInit); 3) smoking cessation (SmkCes); 4) cigarettes per day (CigDay). Linkage disequilibrium score regression (LDSC) was employed to examine genetic association analysis. Furthermore, for traits with significant genetic associations, Mendelian randomization (MR) analyses were conducted. Results: The LDSC analysis revealed nominal genetic correlations between AgeSmk and right precentral surface area, left caudal anterior cingulate surface area, left cuneus surface area, left inferior parietal surface area, and right caudal anterior cingulate thickness, as well as between CigDay and left caudal middle frontal surface area, between SmkCes and left entorhinal thickness, and between SmkInit and left rostral anterior cingulate surface area, right rostral anterior cingulate thickness, and right superior frontal thickness (rg=-0.36–0.29, p<0.05). MR analysis showed a unidirectional causal association between left caudal middle frontal surface area and CigDay (βIVW=0.056, pBonferroni=2×10-4). Conclusion Left caudal middle frontal surface area has the potential to serve as a significant predictor of smoking behavior.

Objective: Previous studies have discovered a correlation between cigarette smoking and cortical thickness and surface area, but the causal relationship remains unclear. The objective of this investigation is to scrutinize the causal association between them. Methods: To derive summary statistics from a genome-wide association study (GWAS) on cortical thickness, surface area, and four smoking behaviors: 1) age of initiation of regular smoking (AgeSmk); 2) smoking initiation (SmkInit); 3) smoking cessation (SmkCes); 4) cigarettes per day (CigDay). Linkage disequilibrium score regression (LDSC) was employed to examine genetic association analysis. Furthermore, for traits with significant genetic associations, Mendelian randomization (MR) analyses were conducted. Results: The LDSC analysis revealed nominal genetic correlations between AgeSmk and right precentral surface area, left caudal anterior cingulate surface area, left cuneus surface area, left inferior parietal surface area, and right caudal anterior cingulate thickness, as well as between CigDay and left caudal middle frontal surface area, between SmkCes and left entorhinal thickness, and between SmkInit and left rostral anterior cingulate surface area, right rostral anterior cingulate thickness, and right superior frontal thickness (rg=-0.36–0.29, p<0.05). MR analysis showed a unidirectional causal association between left caudal middle frontal surface area and CigDay (βIVW=0.056, pBonferroni=2×10-4). Conclusion Left caudal middle frontal surface area has the potential to serve as a significant predictor of smoking behavior.

ObjectiveTo investigate the contamination status, transmission risk and drug resistance of Klebsiella pneumoniae (KP) on the object surfaces in the surrounding environment of hospitalized patients infected with carbapenem-resistant Klebsiella pneumoniae (CRKP) , so as to provide a scientific guidance for the prevention and control of healthcare-associated infection. MethodsSamples from the surfaces of objects in the surrounding environment of CRKP infected patients living in the intensive care unit (ICU) and hand specimens from healthcare workers were collected for KP isolation and identification, as well as drug susceptible test in a medical institution located in Minhang District, Shanghai from 2021 to 2023. Additionally, both univariate and multivariate logistic regression analyses were used to identify the influencing factors associated with KP contamination in the hospital environment. ResultsA total of 546 surface samples were collected from the surrounding environment objects of 15 patients infected with CRKP, with a KP detection rate of 6.59% (36/546).The KP detection rate in the ICU of general ward (10.22%) was higher than that in the ICU of emergency department (2.94%) (χ²=12.142, P<0.001). Moreover, the KP detection rate on the surfaces of patient-contacted items (15.66%) was higher than that on shared-use items (6.25%), cleaning items (10.00%), and medical supplies (3.30%) (χ²=17.943, P<0.001). Besides, the detection rate of KP in items sent out of hospital for disinfection (15.38%) was higher than that in those self-disinfected (4.20%) (χ²=19.996, P<0.001).The highest detection rate of KP was observed in high-temperature washing (15.13%, 18/119) (χ²=21.219, P<0.001), while the lowest detection rate was observed in antibacterial hand sanitizer with trichlorohydroxydiphenyl ether sanitizing factor (0, 0/60) ( χ²=21.219, P<0.001).The detection rate of KP in samples taken more than 24 hours after the last disinfection (23.08%) was higher than that in those taken at 4 to24 hours (12.90%) and less than 4 hours (4.22%) (χ²=23.398,P<0.001).ICU of general ward (OR=4.045, 95%CI: 2.206‒7.416), patient-contacted items (OR=3.113, 95%CI: 1.191‒8.141), and self-disinfection ( OR=0.241, 95%CI:0.144‒0.402) were influencing factors for KP contamination in environmental surface. From 2021 to 2023, the drug resistance rates of hospital environmental KP isolates showed an upward trend (P<0.001) to antibiotics such as ceftazidime and gentamicin. Furthermore, high drug resistance rates of KP (>90%) were observed to ciprofloxacin, levofloxacin, cefotaxime, ceftriaxone, and cefepime. ConclusionCRKP can be transmitted outward through the surfaces of objects in the patients’ surroundings, and the drug resistance situation is severe. In clinical settings, it is necessary to implement isolation measures for CRKP infection patients, to increase the frequency of disinfection for objects in their surroundings, to strengthen hand hygiene practices, and to use antibiotics appropriately.

Objective: Previous studies have discovered a correlation between cigarette smoking and cortical thickness and surface area, but the causal relationship remains unclear. The objective of this investigation is to scrutinize the causal association between them. Methods: To derive summary statistics from a genome-wide association study (GWAS) on cortical thickness, surface area, and four smoking behaviors: 1) age of initiation of regular smoking (AgeSmk); 2) smoking initiation (SmkInit); 3) smoking cessation (SmkCes); 4) cigarettes per day (CigDay). Linkage disequilibrium score regression (LDSC) was employed to examine genetic association analysis. Furthermore, for traits with significant genetic associations, Mendelian randomization (MR) analyses were conducted. Results: The LDSC analysis revealed nominal genetic correlations between AgeSmk and right precentral surface area, left caudal anterior cingulate surface area, left cuneus surface area, left inferior parietal surface area, and right caudal anterior cingulate thickness, as well as between CigDay and left caudal middle frontal surface area, between SmkCes and left entorhinal thickness, and between SmkInit and left rostral anterior cingulate surface area, right rostral anterior cingulate thickness, and right superior frontal thickness (rg=-0.36–0.29, p<0.05). MR analysis showed a unidirectional causal association between left caudal middle frontal surface area and CigDay (βIVW=0.056, pBonferroni=2×10-4). Conclusion Left caudal middle frontal surface area has the potential to serve as a significant predictor of smoking behavior.

ObjectiveTo analyze the distribution, drug resistance characteristics, and changing trends of Acinetobacter baumannii (AB) isolated from environmental surfaces and healthcare workers’ hands in a grade Ⅱ level A general hospital in Xuhui District of Shanghai from 2018 to 2023, and to provide reference for infection control in the hospital. MethodsEnvironmental samples were collected quarterly from critical surfaces and healthcare workers’ hands in the intensive care unit (ICU), geriatrics, and respiratory departments from 2018 to 2023. Clinical isolates were obtained from all patients with AB infections in ICU, geriatrics, respiratory department, rehabilitation department, infectious diseases department, emergency department, cardiology department, and orthopedics of the hospital from 2018 to 2023. Retrospective analyses were performed on AB detection rates, strain origins, resistance rates to commonly used antimicrobial agents, and resistance gene features, comparing the antimicrobial resistance between clinically isolated strains and environmentally isolated strains. ResultsFrom 2018 to 2023, a total of 1 416 samples were collected from the hospital and a total of 272 strains of AB were detected, with a positive detection rate of 19.21%. The detection rate gradually decreased year-on-year (χ²_trend=45.290, P<0.001). The majority of samples originated from patient-contacted items (34.56%, 94/272), followed by shared items (26.84%, 73/272) and healthcare worker-contacted items (15.07%, 41/272). From 2018 to 2023, the resistance rate of AB on environmental surfaces and healthcare workers’ hands to commonly tested antibiotics in the hospital ranged from 10% to 40%. The resistance rates to cefotaxime (42.52%) and piperacillin (38.58%) were relative high, while the resistance to polymyxin E (1.57%), polymyxin B (2.36%), and doxycycline (3.94%) maintained low. The annual fluctuations in resistance to cefotaxime, piperacillin, ceftriaxone, tobramycin, doxycycline, minocycline and cotrimoxazole were statistically significant (all P<0.05). There were statistically significant differences in the resistance of clinical and environmental isolates to ampicillin/sulbactam, cefepime, ceftazidime, subamphetamine, meropenem, piperacillin, aztreonam, gentamicin, tobramycin, minocycline, ciprofloxacin, levofloxacin, and cotrimoxazole in the hospital from 2018 to 2023 (all P<0.05). The resistance rate of clinical isolates was generally high, especially to β-lactam and quinolone drugs, which were mostly above 80% [such as cefepime (93.86%), cefotaxime (97.37%), imipenem (98.25%), and ciprofloxacin (99.12%)]. The resistance rate of environmental isolated strains to similar antibiotics was relatively lower, mostly concentrated at 10%‒30%. The whole-genome sequencing of 34 carbapenem-resistant Acinetobacter baumannii (CRAB) strains isolated from the hospital environment in 2023 revealed that the main resistance mechanism was overexpression of efflux pumps (51.97%), followed by changes in target sites (32.46%). Among the 34 CRAB strains, carbapenem resistance genes OXA-23 and OXA-51 were detected in 6 strains (17.65%), while genes such as KPC, IMP, VIM, and SIM were not detected. ConclusionFrom 2018 to 2023, AB in the hospital environment exhibited high resistance rates to certain antimicrobial agents and carried multiple resistance genes, indicating a potential transmission risk. It is necessary to further strengthen bacterial resistance monitoring and hospital infection control, and use antibiotics reasonably.