Objective: To describe the association of different sleep characteristics and cardiometabolic risk among college students, so as to provide reference for health promotion of college students. Methods: By random cluster sampling method, a questionnaire survey and physical examination including blood pressure, waist circumference and blood lipid indicators, which were conducted in April and May of 2019 among a total of 1 179 college students from the first grade in two universities in Hefei City of Anhui Province and Shangrao City of Jiangxi Province. A total of 729 college students with valid questionnaires were included into analysis. The Pittsburgh Sleep Quality Index (PSQI) and Insomnia Severity Index (ISI) were used to investigate sleep behavior, and the Morning And Evening Questionnaire-5 (MEQ-5) was used to investigate sleep characteristics. The cardiometabolic risk score was derived using the sum of the standardized sex specific Z scores of waist circumference, mean arterial pressure, HDL cholesterol (multiplied by -1), triglycerides, and insulin resistance index. The rank sum tests were used to compare differences in cardiometabolic risk scores across demographic characteristics. Generalized linear models were used to compare the association of different sleep characteristics with cardiometabolic risk scores among college students. Results: The average cardiovascular metabolic risk score of college students was -0.32(-2.03, 1.58). There were statistically significant differences in cardiovascular metabolic risk scores among college students in variables such as smoking, health status, and physical activity levels ( t/F=-3.41, 12.88, 51.07, P <0.01). The results of the generalized linear model showed that nighttime preference ( B=1.89, 95%CI =1.02-3.49), insomnia symptoms ( B=3.25, 95%CI =1.79-5.90), and short or long sleep duration ( B=1.92, 95%CI =1.21-3.05) were positively correlated with the cardiovascular metabolic risk score of college students ( P <0.05). Conclusions Poor sleep patterns among college students are positively correlated with the risk of cardiovascular metabolism. The sleep behavior of college students should be actively changed to reduce the risk of cardiovascular disease.

Objective: To explore the longitudinal correlation between smartphone multitasking and depressive symptoms, so as to provide an evidence based basis for promoting the mental health of college students. Methods: A total of 967 college students were recruited from one university in Taiyuan, Chongqing, and Shenzhen cities, China, by using multi stage randomized cluster sampling from October to December 2021 at baseline, and a follow up survey was conducted in May 2022. Smartphone multitasking behaviors were assessed by means of the Assessment of Smartphone Multitasking for Adolescents (ASMA), and depressive symptoms were assessed using the Patient Health Questionnaire-9 (PHQ-9) among college students. Chi square tests were performed to compare the differences in depressive symptoms between different groups of demographic characteristics, and binary Logistic regression models were employed to analyze the associations between smartphone multitasking and depressive symptoms among college students. Results: The rates of depressive symptoms among college students at baseline and follow up were 35.2% and 42.3%, respectively. Compared to the low level smartphone multitasking index group at baseline, the moderate and high level groups were more likely to experience depressive symptoms at baseline (moderate level group: OR=1.74, 95%CI =1.22-2.50, high level group: OR=2.77, 95%CI =1.94-3.95) and followup (moderate level group: OR=1.41, 95%CI =1.01-1.95, high level group: OR=1.64, 95%CI =1.17-2.29) ( P <0.05). In addition, compared to the persistently low smartphone multitasking index, increased risk of depressive symptoms was associated with maintaining a moderate to high ( OR=2.94, 95%CI =1.83-4.71), and a higher ( OR=2.07, 95%CI =1.31-3.27) or lower smartphone multitasking index ( OR=2.02, 95%CI =1.27-3.19) ( P <0.05). Moreover, higher smartphone multitasking index scores were positively associated with the risk of new-onset depressive symptoms at follow up ( OR=1.87, 95%CI=1.07-3.27, P <0.05). Conclusions Smartphone multitasking behaviors are find to be associated with an increased risk of depressive symptoms in college students. There is a need to reduce smartphone multitasking in order to decrease depressive symptoms and promote students mental health.

Objective: To describe the prevalence and the association of sleep quality trajectory, social jetlag and comorbid symptoms of anxiety and depression among college students, in order to provide a theoretical basis for improving the comorbid symptoms of anxiety and depression in college students. Methods: A questionnaire survey was conducted among 1 135 college students from two universities in Shangrao, Jiangxi Province and Hefei, Anhui Province from April to May 2019, and were followed up once every one year for a total of three times, with a valid sample size of 1 034 individuals after matching with the baseline survey. A selfassessment questionnaire was used to investigate the social jetlag of college students, the Generalized Anxiety Disorder-7 (GAD-7) and Patient Health Questionnaire 9 (PHQ-9) were used to evaluate anxiety and depression symptoms, respectively, while the Pittsburgh Sleep Quality Index (PSQI) was used to assess sleep quality. College students with GAD-7 score ≥5 and PHQ-9 score ≥5 were defined as having comorbid anxiety and depression symptoms. Latent class growth model (LCGM) was employed to analyze the sleep quality trajectory of college students, and binary Logistic regression was used to analyze the relationship between social jetlag, sleep quality trajectory and comorbid symptoms of anxiety and depression. Results: The detection rate of comorbid symptoms of anxiety and depression among college students was 16.9%, and the detection rate of social jetlag ≥2 h was 13.8%. The sleep quality showed an overall improvement trend, and the two trajectories were good sleep quality (81.6%) and poor sleep quality (18.4%). Binary Logistic regression model showed that poor sleep quality and social jetlag ≥2 h were positively correlated with comorbid symptoms of anxiety and depression (OR=5.94, 1.84, P<0.05). Conclusions Poor sleep quality and social jetlag ≥2 h in college students increase the risk of comorbid symptoms of anxiety and depression. Early screening and intervention of sleep quality and reduction of social jetlag are crucial for enhancing the mental health of college students.

Background Mercury, as a global heavy metal pollutant, poses a serious threat to human health. The toxicity of mercury depends on its chemical form. Distinguishing the forms of mercury in the environment is of great significance for mercury management and reducing human mercury exposure risks. Objective To establish a non-targeted metallomics method based on synchrotron radiation X-ray fluorescence (SRXRF) spectroscopy combined with machine learning to screen inorganic mercury (IHg) or methylmercury (MeHg) exposed rice plants. Methods Rice seeds were exposed to ultra-pure water (control group), 0.1 mg·L⁻¹ IHg (IHg group) or MeHg (MeHg group) solutions, respectively. After germination, the seedlings were cultured for 21 d, and rice leaves were collected, dried, weighed, and pressed. The content of metallome in rice leaves was determined by SRXRF. Machine learning models including soft independent modeling cluster analysis (SIMCA), partial least squares discriminant analysis (PLS-DA), and logistic regression (LR) were used to classify the SRXRF full spectra of different groups and find the best model to distinguish rice exposed to IHg or MeHg. Besides, characteristic elements were selected as input parameters to optimize the model by improving computing speed and reducing model calculation. Results The SRXRF spectral intensities of the control group, IHg group, and MeHg group were different, indicating that exposure to IHg and MeHg can interfere the homeostasis of metallome in rice leaves. The results of principal component analysis (PCA) of SRXRF spectra showed that the control group could be well distinguished from the mercury exposed groups, but the IHg group and the MeHg group were mostly overlapped. The accuracy rates of the three models (PLS-DA, SIMCA, and LR) were higher than 98% for the training set, higher than 95% for the validation set, and higher than 94% for the cross-validation set. Besides, the accuracy of the LR model was higher than that of the PLS-DA model and the SIMCA model. Furthermore, the accuracy was 92.05% when using characteristic elements K, Ca, Mn, Fe, and Zn selected by LR to distinguish the IHg group and the MeHg group. Compared with the full spectra model, although the prediction accuracy of the characteristic spectral model decreased, the input parameters of the model decreased by 99.51%, and precision, recall, and F1 score were above 84.48%, indicating that the model could distinguish rice exposed to different mercury forms. Conclusion Non-targeted metallomics method based on SRXRF and machine learning can be applied for high-throughput screening of rice exposed to different forms of mercury and thus decrease the risks of people being exposed to mercury.

Objective:To investigate the genotype and epidemiological characteristics of human metapneumovirus (HMPV) among hospitalized cases with acute respiratory infections (ARI) in children in Changchun City, Jilin Province, China.Methods:From June 2019 to June 2023, throat swabs of ARI inpatients in Changchun Children′s Hospital were collected, and their epidemiological and clinical information were also collected. Quantitative reverse transcription-PCR was used to identify HMPV-positive cases, followed by the amplification of the G gene and genetic analysis in the HMPV-positive cases.Results:A total of 3 311 children hospitalized with ARI were included in this study. Their age ranged from 0 to 17 years old, and the M ( Q1, Q3) of age was 2 (1, 3) years. About 1 811 (54.70%) cases were males. A total of 167 HMPV-positive cases were detected with a positive rate of 5.04%, of which 92.81% (155/167) were children under 5 years old. The positive rate of HMPV in 2019 was 6.37% (30/471), which dropped to the lowest in 2020 (2.31%, 10/432). The HMPV-positive rate was then rebounded in 2021 (4.70%, 60/1 277) and 2022 (4.56%, 21/461), which increased to 6.87% (46/670) in 2023. The difference in HMPV-positive rate among each year was statistically significant ( P<0.05). The prevalence peak of HMPV varied in different years, showing either a unimodal or bimodal distribution in one year. A total of 79 HMPV G gene sequences were obtained, of which subtype A and subtype B accounted for 48.10% and 51.90%, respectively. All of the subtype A sequences were clarified as A2c duplicated variants, and subtype B was mainly B2 genotype. Besides, subtypes A and B were prevalent alone or co-circulated in different years, and there was a subtype replacement pattern in HMPV. Conclusion:The positive rate of HMPV in hospitalized ARI cases in children is significantly different from 2019 to 2023 in Changchun City. Notably, there are certain switch patterns of HMPV subtypes A and B in different years.

Objective:To understand the epidemiological characteristics of human respiratory syncytial virus (HRSV) among acute respiratory infection (ARI) cases in 16 provinces of China from 2009 to 2023.Methods:The data of this study were collected from the ARI surveillance data from 16 provinces in China from 2009 to 2023, with a total of 28 278 ARI cases included in the study. The clinical specimens from ARI cases were screened for HRSV nucleic acid from 2009 to 2023, and differences in virus detection rates among cases of different age groups, regions, and months were analyzed.Results:A total of 28 278 ARI cases were enrolled from January 2009 to September 2023. The age of the cases ranged from<1 month to 112 years, and the age M ( Q1, Q3) was 3 years (1 year, 9 years). Among them, 3 062 cases were positive for HRSV nucleic acid, with a total detection rate of 10.83%. From 2009 to 2019, the detection rate of HRSV was 9.33%, and the virus was mainly prevalent in winter and spring. During the Corona Virus Disease 2019 (COVID-19) pandemic, the detection rate of HRSV fluctuated between 6.32% and 18.67%. There was no traditional winter epidemic peak of HRSV from the end of 2022 to the beginning of 2023, and an anti-seasonal epidemic of HRSV occurred from April to May 2023. About 87.95% (2 693/3 062) of positive cases were children under 5 years old, and the difference in the detection rate of HRSV among different age groups was statistically significant ( P<0.001), showing a decreasing trend of HRSV detection rate with the increase of age ( P<0.001). Among them, the HRSV detection rate (25.69%) was highest in children under 6 months. Compared with 2009-2019, the ranking of HRSV detection rates in different age groups changed from high to low between 2020 and 2023, with the age M (Q1, Q3) of HRSV positive cases increasing from 1 year (6 months, 3 years) to 2 years (11 months, 3 years). Conclusion:Through 15 years of continuous HRSV surveillance analysis, children under 5 years old, especially infants under 6 months old, are the main high-risk population for HRSV infection. During the COVID-19 pandemic, the prevalence and patterns of HRSV in China have changed.

Objective:To investigate the genotype and epidemiological characteristics of human metapneumovirus (HMPV) among hospitalized cases with acute respiratory infections (ARI) in children in Changchun City, Jilin Province, China.Methods:From June 2019 to June 2023, throat swabs of ARI inpatients in Changchun Children′s Hospital were collected, and their epidemiological and clinical information were also collected. Quantitative reverse transcription-PCR was used to identify HMPV-positive cases, followed by the amplification of the G gene and genetic analysis in the HMPV-positive cases.Results:A total of 3 311 children hospitalized with ARI were included in this study. Their age ranged from 0 to 17 years old, and the M ( Q1, Q3) of age was 2 (1, 3) years. About 1 811 (54.70%) cases were males. A total of 167 HMPV-positive cases were detected with a positive rate of 5.04%, of which 92.81% (155/167) were children under 5 years old. The positive rate of HMPV in 2019 was 6.37% (30/471), which dropped to the lowest in 2020 (2.31%, 10/432). The HMPV-positive rate was then rebounded in 2021 (4.70%, 60/1 277) and 2022 (4.56%, 21/461), which increased to 6.87% (46/670) in 2023. The difference in HMPV-positive rate among each year was statistically significant ( P<0.05). The prevalence peak of HMPV varied in different years, showing either a unimodal or bimodal distribution in one year. A total of 79 HMPV G gene sequences were obtained, of which subtype A and subtype B accounted for 48.10% and 51.90%, respectively. All of the subtype A sequences were clarified as A2c duplicated variants, and subtype B was mainly B2 genotype. Besides, subtypes A and B were prevalent alone or co-circulated in different years, and there was a subtype replacement pattern in HMPV. Conclusion:The positive rate of HMPV in hospitalized ARI cases in children is significantly different from 2019 to 2023 in Changchun City. Notably, there are certain switch patterns of HMPV subtypes A and B in different years.

Objective:To understand the epidemiological characteristics of human respiratory syncytial virus (HRSV) among acute respiratory infection (ARI) cases in 16 provinces of China from 2009 to 2023.Methods:The data of this study were collected from the ARI surveillance data from 16 provinces in China from 2009 to 2023, with a total of 28 278 ARI cases included in the study. The clinical specimens from ARI cases were screened for HRSV nucleic acid from 2009 to 2023, and differences in virus detection rates among cases of different age groups, regions, and months were analyzed.Results:A total of 28 278 ARI cases were enrolled from January 2009 to September 2023. The age of the cases ranged from<1 month to 112 years, and the age M ( Q1, Q3) was 3 years (1 year, 9 years). Among them, 3 062 cases were positive for HRSV nucleic acid, with a total detection rate of 10.83%. From 2009 to 2019, the detection rate of HRSV was 9.33%, and the virus was mainly prevalent in winter and spring. During the Corona Virus Disease 2019 (COVID-19) pandemic, the detection rate of HRSV fluctuated between 6.32% and 18.67%. There was no traditional winter epidemic peak of HRSV from the end of 2022 to the beginning of 2023, and an anti-seasonal epidemic of HRSV occurred from April to May 2023. About 87.95% (2 693/3 062) of positive cases were children under 5 years old, and the difference in the detection rate of HRSV among different age groups was statistically significant ( P<0.001), showing a decreasing trend of HRSV detection rate with the increase of age ( P<0.001). Among them, the HRSV detection rate (25.69%) was highest in children under 6 months. Compared with 2009-2019, the ranking of HRSV detection rates in different age groups changed from high to low between 2020 and 2023, with the age M (Q1, Q3) of HRSV positive cases increasing from 1 year (6 months, 3 years) to 2 years (11 months, 3 years). Conclusion:Through 15 years of continuous HRSV surveillance analysis, children under 5 years old, especially infants under 6 months old, are the main high-risk population for HRSV infection. During the COVID-19 pandemic, the prevalence and patterns of HRSV in China have changed.

Objective:To evaluate the effect of patient-controlled intravenous analgesia (PCIA) with esketamine mixed with hydromorphone on the postoperative sleep quality in pediatric patients.Methods:This was a prospective randomised controlled study. One hundred pediatric patients of both sexes, aged 4-12 yr, with a body mass index of 13-26 kg/m 2, of American Society of Anesthesiologists Physical Status classification Ⅰ or Ⅱ, undergoing elective abdominal surgery with general anesthesia, who agreed to use postoperative patient-controlled intravenous analgesia in our hospital from January to November 2023, were divided into esktamine mixed with hydromorphone group (EH group) and hydromorphone group (H group), with 50 patients in each group. PCIA solution contained esketamine 1 mg/kg and hydromorphon 0.1 mg/kg in 100 ml of 0.9% sodium chloride in EH group and hydromorphone 0.2 mg/kg in 100 ml of 0.9% sodium chloride in H group. The Pittsburgh Sleep Quality Index was used to evaluate the preoperative sleep quality by asking pediatric patients themselves or their guardians. On the morning of 1-3 days after surgery, the numeric rating scale (NRS) was used to evaluate the sleep quality of the first 3 nights after surgery. At 24 and 48 h after surgery, the FLACC pain scale was used to evaluate the intensity of pain. The consumption of hydromorphone within 48 h after surgery and the incidence of postoperative adverse reactions such as nausea, vomiting, itching and delirium were recorded. Results:Compared with group H, the NRS score was significantly increased on the 1st postoperative night, the ratio of poor sleep quality was decreased ( P<0.05), and no significant change was found in the NRS score on the 2nd or 3rd postoperative night and ratio of poor sleep quality ( P>0.05), and the FLACC pain scale score at 24 and 48 h after surgery and consumption of hydromorphone within 48 h after surgery were decreased in group EH ( P<0.05). There was no significant difference in the incidence of postoperative adverse reactions between the two groups ( P>0.05). Conclusions:PCIA with esketamine mixed with hydromorphone can improve the postoperative sleep quality in pediatric patients.

To investigate the therapeutic effect and mechanism of Qingwen Baiduyin on acute lung injury （ALI） in mice induced by lipopolysaccharide （LPS）. MethodA total of 144 C57BL/6 mice were randomly divided into the following groups： a normal group， a model group （LPS， 5 mg·kg^-1）， a dexamethasone group （5 mg·kg^-1）， and low-， medium-， and high-dose Qingwen Baiduyin groups （14.105， 28.21， 56.42 g·kg^-1）. The mice were treated once daily for 5 days. One hour after the final administration， the ALI model was established by intratracheal instillation of LPS， and samples were collected at 6 h and 24 h after modeling. The arterial blood gas index of mice was analyzed. The total protein content， total cell count， Evans blue dye （EBD） content， and lung tissue wet-to-dry weight ratio （W/D） of bronchoalveolar lavage fluid （BALF） were measured. Hematoxylin-eosin （HE） staining was performed to assess the pathological changes in mouse lung tissue. Western blot was used to detect the expression levels of key proteins in the Janus kinase 1/signal transducer and activator of transcription 1/interferon regulatory factor 1 （JAK1/STAT1/IRF1） signaling pathway in lung tissue. ResultCompared with the normal group， the model group showed reduced arterial oxygen pressure （pO₂）， oxygen saturation （SO₂）， and lung tissue W/D （P<0.05， P<0.01）， increased carbon dioxide pressure （pCO₂）， total protein content， total cell count， EBD content， interferon-γ （IFN-γ）， tumor necrosis factor-α （TNF-α）， interleukin-1β （IL-1β）， chemokine CXC ligand 1 （CXCL1）， chemokine CXC ligand 2 （CXCL2）， chemokine CXC ligand 9 （CXCL9）， and chemokine CXC ligand 10 （CXCL10） content （P<0.05， P<0.01）， thickening of the alveolar walls， fusion of alveolar cavities， and infiltration of inflammatory cells in lung tissue， increased proportion of M1 macrophage polarization and lung cell apoptosis （P<0.05）， and increased protein expression levels of JAK1， phosphorylated JAK1 （p-JAK1）， inducible nitric oxide synthase （iNOS）， STAT1， phosphorylated STAT1 （p-STAT1）， IRF1， gasdermin D （GSDMD）， and mixed lineage kinase domain-like protein （MLKL） （P<0.05， P<0.01）. Compared with the model group， Qingwen Baiduyin significantly increased pO₂， SO₂， and lung tissue W/D （P<0.05， P<0.01）， improved the pathological changes in lung tissue， and reduced pCO₂， total protein content， total cell count， EBD content， IFN-γ， TNF-α， IL-1β， CXCL1， CXCL2， CXCL9， and CXCL10 content， proportion of M1 macrophage polarization， and protein expression levels of JAK1， p-JAK1， iNOS， STAT1， p-STAT1， IRF1， GSDMD， and MLKL （P<0.05， P<0.01）. ConclusionQingwen Baiduyin can improve the lung inflammatory response and reduce lung cell apoptosis in mice with ALI by inhibiting the JAK1/STAT1/IRF1 signaling pathway， thereby exerting a lung-protective effect.