Association of different sleep characteristics and cardiometabolic risk in college students / 中国学校卫生

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.

[Association between changes in physical activity and comorbid symptoms of anxiety and depression in college students].

OBJECTIVE: To describe the prevalence of physical activity and comorbid symptoms of anxiety and depression in college students, and to explore the correlation strength between changes in physical activity and comorbid symptoms of anxiety and depression, so as to provide a reference for promoting college students' mental health. METHODS: From April to May 2019, 1179 freshmen majoring in public health, nursing, chemistry and physical education were randomly sampled from one university in Hefei City, Anhui Province, and Shangrao City, Jiangxi Province, respectively. A baseline questionnaire survey was conducted. A follow-up survey was conducted in May 2021, and a total of 1046 subjects were included, including 647 female and 399 male. The International Physical Activity Questionnaire-Short Form was used to evaluate the physical activity level of college students, and the Patient Health Questionnaire and Generalized Anxiety Disorder Scale were used to evaluate the anxiety and depression symptoms of college students during follow-up. Determining the coexistence of anxiety and depression symptoms in college students as anxiety-depression comorbid symptoms. RESULTS: In the follow-up survey, the detection rate of anxiety and depression comorbid symptoms of college students was 16.9%(n=177), and the detection rates of sufficient, decreased, increased, and insufficient physical activity changes were 72.5%(n=758), 13.8%(n=144), 9.2%(n=96), and 4.6%(n=48), respectively. The result of multiple Logistic regression model showed that, after controlling for confounding factors, compared with those with sustained high level of physical activity, i. e. , adequate physical activity, increased physical activity(OR=1.89, 95%CI 1.10-3.25), decreased physical activity(OR =2.80, 95% CI 1.72-4.57), and insufficient physical activity(OR = 3.66, 95% CI 1.85-7.23) increased the risk of anxiety-depression comorbidity symptoms of college students(P<0.05). However, there was no significant increase in the risk of anxiety or depressive symptoms in those who increased, decreased, or insufficient physical activity compared with those who were sufficient physical activity(P>0.05). CONCLUSION: The level of physical activity and its changes are related to mental health of college students. The continuous low level of physical activity is associated with the increased risk of comorbidity of anxiety and depression in college students.

The day-night differences in cognitive and anxiety-like behaviors of mice after chronic sleep restriction.

Animal behavioral tests are often conducted during the day. However, rodents are nocturnal animals and are primarily active at night. The aim of this study was to determine whether there are diurnal changes in cognitive and anxiety-like performance of mice following chronic sleep restriction (SR). We also investigated whether this phenotypic difference is related to the diurnal variation of glymphatic clearance of metabolic wastes. Mice received 9-day SR by the use of the modified rotating rod method, followed by the open field, elevated plus maze, and Y-maze tests conducted during the day and at night, respectively. Brain ß-amyloid (Aß) and tau protein levels, the polarity of aquaporin4 (AQP4), a functional marker of the glymphatic system, and glymphatic transport ability were also analyzed. SR mice exhibited cognitive impairment and anxiety-like behaviors during the day, but not at night. AQP4 polarity and glymphatic transport ability were higher during the day, with lower Aß1-42 , Aß1-40 , and P-Tau levels in the frontal cortex. These day-night differences were totally disrupted after SR. These results reveal the diurnal changes in behavioral performance after chronic SR, which may be related to circadian control of AQP4-mediated glymphatic clearance of toxic macromolecules from the brain.

Smartphone Use and Inflammation at 2-Year Follow-Up in College Students: The Mediating Role of Physical Activity.

Purpose: Smartphone use could lead to being physically inactive and a greater risk for health problems, such as inflammation. However, the associations between smartphone use, physical activity (PA), and systemic low-grade inflammation remained unclear. This study aimed to examine the potential mediating effect of PA on the association between smartphone use and inflammation. Patients and Methods: A two-year follow-up study was conducted between April 2019 and April 2021. Duration of smartphone use, smartphone dependence and PA were assessed by a self-administered questionnaire. Laboratory analysis of blood samples was performed to evaluate the levels of TNF-α, IL-6, IL-1ß, and CRP as biomarkers of systemic inflammation. The correlations between smartphone use, PA, and inflammation were analyzed using Pearson correlation. Structural equation modelling was used to analyze the potential mediating effect of PA on the associations between smartphone use and inflammation. Results: A total of 210 participants were included with a mean (standard deviation) age of 18.7 (1.0) years, 82 (39%) of whom were males. Smartphone dependence was negatively associated with the total PA level (r=-0.18, P<0.01). PA mediated the associations between the duration of smartphone use and smartphone dependence with inflammatory markers. Specifically, as PA decreased, the duration of smartphone use was more negatively associated with TNF-α (ab=-0.027; 95% CI: -0.052, -0.007) and more positively correlated to IL-6 (ab=0.020; 95% CI: 0.001, 0.046) and CRP (ab=0.038; 95% CI: 0.004, 0.086); smartphone dependency was more negatively associated with TNF-α (ab=-0.139; 95% CI: -0.288, -0.017) and more positively related to CRP (ab=0.206; 95% CI: 0.020, 0.421). Conclusion: Our study illustrates that there are no direct associations between smartphone use and systemic low-grade inflammation, however, PA level plays a weak but significant mediating effect on the associations between smartphone use and inflammation among college students.

Poor sleep pattern is associated with metabolic disorder during transition from adolescence to adulthood.

Objective: The purpose of this study was to investigate whether sleep pattern is associated with metabolic disorders among young adults. Methods: We measured sleep patterns using multiple sleep behaviors in an ongoing prospective cohort among college students (n = 1,151). At baseline, 729 college students provided fasting blood samples and human body morphological measurements for quantification of metabolic parameters. Then, 340 participants continued to take metabolic parameters measurements at a 2-year follow-up. Sleep patterns were defined by chronotype, sleep duration, insomnia, snoring, and daytime sleepiness. Metabolic scores were derived for four metabolic parameters including body mass index (BMI), waist circumference (WC), fasting blood sugar (FBG), and insulin. Multivariate linear regression model was applied to analyze the association between sleep pattern types and metabolic parameters and metabolic scores. Results: In the baseline survey, we found that a total of 41 (4.1%) participants had poor sleep patterns. Then, metabolic scores were significantly higher among college students with poor sleep patterns, compared with those who with healthy sleep patterns at baseline (1.00 ± 0.96 vs. 0.78 ± 0.72, p < 0.05) and 2-year follow-up (0.34 ± 0.65 vs. 1.50 ± 1.64, p < 0.05). After covariates were adjusted, poor sleep pattern (ß = 0.22, 95% CI: 0.06~2.53, p = 0.001) was associated with elevated metabolic scores at the 2-year follow-up. Conclusions: The elevated metabolic burden observed in college students with poor sleep patterns highlights the need to identify and address sleep problems in order to minimize the long-term impact on disease vulnerability.

Insomnia trajectories predict chronic inflammation over 2 years at the transition to adulthood.

Insomnia in adolescents is an important public health concern, as its impacts on both their current and future physical and mental health has been discussed. However, few longitudinal studies have examined insomnia and chronic inflammation at the transition from adolescence to adulthood. This study aimed to examine the predictive effects of insomnia and insomnia trajectories on inflammation in college students by using a prospective design. Using data from the College Student Behaviour and Health Cohort Study, which was conducted between April 2019 and April 2021, with an interval of 6 months. We investigated the associations between insomnia trajectories from Year 1 to Year 3 and five inflammatory biomarkers (C-reactive protein [CRP], tumour necrosis factor [TNF]-α, interleukin [IL]-6, IL-1ß, IL-10) at Year 3. The association of insomnia symptoms at baseline, Wave 1 or Wave 2 with inflammatory biomarkers at Wave 4 were also assessed. A total of 312 college students (males: 51.6%) aged 16-26 years (mean [SD] 18.82 [1.22] years) were analysed. We identified two insomnia trajectory classes: increasing insomnia (n = 63 [20.2%]) and decreasing insomnia (n = 249 [79.8%]). Generalised linear model analysis revealed that insomnia symptoms at Wave 1 were associated with significantly elevated CRP and TNF-α levels at Wave 4. Increasing insomnia trajectories predicted consistently higher levels of CRP, TNF-α and IL-10. However, after adjusting for potential confounders, these associations were significantly attenuated. Overall, the findings suggest that insomnia symptoms affect chronic inflammation at the transition to adulthood. Our study needs to be replicated in larger cohorts to further explore how inflammation interacts with insomnia to increase the susceptibility to adverse health conditions.

Association between healthy sleep patterns and depressive trajectories among college students: a prospective cohort study.

BACKGROUND: The purpose of this study was to identify different develpment trajectories of depression symptoms during college period, and prospectively investigate the associations healthy sleep patterns with trajectories of depression symptoms among college students from freshman through junior year. METHODS: A total of 999 participants from the College Student Behavior and Health Cohort Study were included between April 2019 and June 2021. Healthy sleep patterns were defined by chronotype, sleep duration, insomnia, snoring, and daytime sleepiness. Latent growth curve model was used to identify trajectories of depression symptoms. Then binary logistic regression was used to examine association of the healthy sleep patterns with these trajectories. RESULTS: In baseline survey, we found that a total of 100 (10.0%) participants had healthy sleep patterns' score equal to 5. Then, we used 5 surveys' data to identify 2 distinct trajectories of depression symptoms during college (decreasing: 82.5%; increasing: 17.5%). The healthy sleep patterns were associated with these trajectories, the better healthy sleep patterns significantly decrease the risk of increasing trajectories of depression symptoms in males (OR: 0.72, 95%CI: 0.54 ~ 0.97, P = 0.031). Moreover, we found out that the healthy sleep patterns of college students can predict the future depressive symptoms in this study (all P < 0.001). CONCLUSION: Our findings indicate that the better healthy sleep patterns may significantly decrease the risk of increasing trajectory of depression symptoms only in male college students. The results speak to a need for college student with depression symptoms to identify and address sleep problems when present, which could prevent or reduce depression detriments in later life.

Association of chronotype, social jetlag, sleep duration and depressive symptoms in Chinese college students.

OBJECTIVES: To describe the prevalence of depressive symptoms among Chinese college students and examine the relationship between sleep and circadian rhythm disruption (SCRD) indicators (chronotype, social jetlag, sleep duration) and depressive symptoms. METHODS: From April to May 2019, the College Student Behavior and Health Cohort Study was conducted among Chinese college students from 2 universities in Anhui and Jiangxi provinces. The current study used data from the third follow-up study. Questionnaire content includes socio-demographic and lifestyle information. Social jetlag and sleep duration were calculated by answering the question about sleep time. Chronotype was assessed by the Morning and Evening Questionnaire (MEQ-5). Depressive symptoms were evaluated by the Patient Health Questionnaire 9 (PHQ-9). A Chi-square test was used to examine the proportion depressive symptoms. Multinomial logistic regression model were used to explore the associations of circadian rhythm indicators with depressive symptoms. RESULTS: The prevalence of mild depression, moderate and above depression was 18.8 % and 6.9 %. Evening types (E-types) and short sleep duration were significantly associated with depression. Stratified analysis indicated that E-types and social jetlag≥2 h were associated with mild depression (OR = 5.67, 95 % CI: 1.83-17.51), as well as stratified analysis indicated that E-types and sleep duration<8 h were associated with mild depression (OR = 5.10, 95 % CI: 1.88-13.87). CONCLUSIONS: The findings suggest that depressive symptoms are more severe when multiple SCRD indicators are out of whack. The intervention programs of depressive symptoms should consider the context of the multidimensional aspects of Chinese college student sleep.

Bidirectional associations between cellular phone use behaviors and depressive symptoms in college students: a follow up study / 中国学校卫生

Objective@#The study aimed to describe the prevalence of mobile phone use and depressive symptoms and to examine the bidirectional associations between the two among college students, providinb evidence for mental health promotion among college students.@*Methods@#A longitudinal study with follow up at 6 month intervals was conducted in 1 135 students from 2 universities in Hefei, Anhui Province and Shangrao, Jiangxi Province who were selected between April and May 2019. The last follow up was conducted between April and May 2021 based on questionnaire survey, and 999 valid participants were obtained after matching. The self designed questionnaire was used to investigate the duration of cellular phone use and use of cellular phone functions among college students. The Self rating Questionnaire for Adolescent Problematic Mobile Phone Use (SQAPMPU) and the Patient Health Questionnaire-9 (PHQ-9) were used to assess cellular phone dependence and depressive symptoms among college students. Pearson correlation analysis was used to examine the correlation between cellular phone use behavior and depressive symptoms at baseline and 2 years later; linear regression model was used to analyze the linear association between cellular phone use behavior and depressive symptoms scores; autoregressive cross lagged model was used to analyze the bidirectional associations between cellular phone use behaviors and depressive symptoms among college students over time.@*Results@#The prevalence of mobile phone dependence and depressive symptoms among college students at baseline were 24.3% and 42.4%, respectively. The mean duration of mobile phone use among college students at baseline and the 2 year follow up were (2.84±0.90)h/d and (2.02±1.05)h/d, respectively; the mean scores of mobile phone dependence were (23.30±9.00) and (23.29±10.45), respectively; the mean scores of mobile phone function use were (30.12±6.66) and (29.12±7.27), respectively; and the mean scores of depressive symptoms were (4.51±4.76) and (2.61±4.40), respectively. Pearson correlation analysis showed there were significant positive correlations between duration of cellular phone use, cellular phone dependence, use of cellular phone functions at baseline or 2 years later and depressive symptoms 2 years later( r =0.08-0.50, P <0.05). Linear regression models showed a significant positive association between cellular phone dependence at baseline and depressive symptoms ( β=0.26, 95%CI =0.23-0.29) at baseline and 2 years later ( β=0.12, 95%CI =0.09-0.15). Autoregressive cross lagged models showed that cellular phone dependence at baseline positively predicted depressive symptoms 2 years later ( β =0.04) and depressive symptoms at baseline positively predicted cellular phone dependence 2 years later( β =0.23)( P <0.05).@*Conclusion@#There was a bidirectional association between cellular phone dependence and depressive symptoms among college students. Reducing cellular phone dependence is of positive significance for improving college students mental health.

Association between sleep quality and anxiety-depression co-morbid symptoms among nursing students of medical college in Hefei City / 中国学校卫生

Objective@#To describe the prevalence and association of sleep quality and anxiety-depression co-morbid symptoms among nursing students, in order to provide a reference basis for promoting the development of nursing students mental health.@*Methods@#Using a prospective study design, baseline survey was conducted in January 2019 among a random cluster sample of 1 716 individuals in three medical universities in Hefei, Anhui Province, and a follow-up survey was conducted in October 2019, with a valid number of 1 573 individuals after matching with the baseline survey. The Pittsburgh Sleep Quality Index (PSQI) was used to assess nursing students sleep quality, and the Depression Anxiety Stress Scale (DASS-21) to assess the anxiety-depression comorbid symptoms.@*Results@#The detection rates of anxiety-depression co-morbidities among nursing students at baseline and follow-up survey were 16.9% and 18.2%, respectively, and the detection rates of poor sleep quality among nursing students at baseline and follow-up survey were 10.1% and 10.3%, respectively. The results of the binary Logistic regression model showed that baseline PSQI score were positively associated with the risk of anxiety-depression co-morbid symptoms among nursing students at baseline ( OR=1.49, 95%CI =1.40-1.59) and after nine months of follow-up ( OR=1.22, 95%CI =1.16-1.28). Furthermore, the influence of baseline sleep quality on the risk of anxiety-depression co-morbid symptoms were mainly concentrated in the five dimensions of sleep time, sleep efficiency, sleep disorders, hypnotic drugs and daytime dysfunction, and such effects of sleep time, sleep disorders and daytime dysfunction still existed in the follow-up investigation.@*Conclusion@#Poor sleep quality of nursing students can increase the risk of anxiety-depression co-morbidities. Improving sleep quality of nursing students has a positive effect on improving their mental health.

[Mediating role of IL-10 in the association between health-risk behaviors and depressive symptoms of college students].

OBJECTIVE: To examine the relationship between health-risk behaviors and depressive symptoms among college students, and explore the mediating role of plasma IL-10 level in the relationship between the two. METHODS: Freshman students in two universities in Hefei City, Anhui Province and Shangrao City, Jiangxi Province were recruited between April and May 2019, and follow-up investigation was conducted 6 months later. Health risk behaviors were measured based on the Young Risk Behavior Surveillance System(YRBSS) questionnaire, and depressive symptoms was evaluated by using the Depression Anxiety Stress Scale(DASS-21) among college students at baseline and 6 months follow-up survey. Plasma interleukin-10(IL-10) level was measured at baseline. Univariate analysis was used to compare the correlation between health risk behaviors and depressive symptoms among college students. Binary Logistic regression analyzed the relationship between health risk behaviors, IL-10 and depressive symptoms. The mediation model was used to explore the mediating role of IL-10 levels in the association between health risk behaviors and depressive symptoms. RESULTS: At baseline, boys reported a higher rate of depressive symptoms than that of girls(χ~2=6.33, P=0.01); higher rates of depressive symptoms were observed in students who were from a family with a low perceived economic status(χ~2=7.31, P=0.03)or in poor health(χ~2=6.71, P=0.04). Participants who reported low physical activity(χ~2=19.09, P<0.01), smoking(χ~2=7.03, P<0.01), and poor sleep quality(χ~2=68.78, P<0.01)at baseline were more likely to experience depressive symptoms. Multiple health-risk behaviors at baseline were positively correlated with depressive symptoms among college students. After adjusting gender, self-reported family economy and self-rated health, the regression model showed that plasma IL-10 at baseline was negatively associated with the prevalence of depressive symptoms(OR=0.36, 95% CI 0.18-0.72) and the incidence of depressive symptoms after 6 months(OR=0.20, 95% CI 0.08-0.49). Structural equation model showed that health-risk behaviors was negatively correlated to IL-10 level(ß=-0.13, SE=0.04), IL-10 negatively predicted depressive symptoms at follow-up(ß=-0.09, SE=0.04), and IL-10 play a mediating role between health risk behavior and depressive symptoms. CONCLUSION: Health risk behaviors are positively correlated with depressive symptoms among college students. Plasma IL-10 level at baseline was negatively associated with the incidence of depressive symptoms after 6 months, and IL-10 level at baseline has a partial mediating effect between baseline health risk behavior clustering and depressive symptoms at follow-up.

Association between trajectories of problematic mobile phone use and chronotype among Chinese college students.

AIMS: This study aimed to describe the prevalence of problematic mobile phone use (PMPU) and chronotype among Chinese college students, estimate PMPU development trajectories, and further examine the effect of PMPU trajectories on chronotype. DESIGN: In a stratified cluster sampling design, PMPU and chronotype were evaluated in 999 college students from two universities in a 2-year prospective investigation from April 2019 to April 2021, and an investigation was conducted every six months (time 1 âˆ¼ time 5, T1 âˆ¼ T5). PARTICIPANTS: N = 999 college students (mean age at T1: 18.8 years (SD = 1.2), 37.7% male) took part in the study. MEASUREMENTS: The Self-rating Questionnaire for Adolescent Problematic Mobile Phone Use (SQAPMPU) and the Pittsburgh Sleep Quality Index (PSQI) were used to assess the PMPU and sleep quality of college students at each time point. The Morning and Evening Questionnaire (MEQ) was adopted to investigate the chronotype of college students at T5. FINDINGS: The prevalence of PMPU at T1 âˆ¼ T5 was 24.3%, 27.3%, 35.1%, 31.2% and 31.9%, respectively. The prevalence rates of morning types (M-types), neutral types (N-types), and evening types (E-types) were 19.1%, 70.8%, and 10.1%, respectively. Using latent growth mixture modelling, we identified three trajectories of PMPU: low-level (49.5%), moderate-level (38.6%), and high-level score trajectories (11.9%). Multivariate logistic regression analysis results showed that a trajectory with a high score was positively associated with E-types (P < 0.05). After stratification by gender, a high-level score trajectory was positively associated with E-types only among female college students (P < 0.05). There were sex differences in the association between trajectories of PMPU and chronotype. CONCLUSION: Long-term symptoms of PMPU may be a potential risk factor for circadian rhythm disturbance among college students, and this effect was significantly different between genders.

Near-Infrared Spectral Characteristic Extraction and Qualitative Analysis Method for Complex Multi-Component Mixtures Based on TRPCA-SVM.

Quality identification of multi-component mixtures is essential for production process control. Artificial sensory evaluation is a conventional quality evaluation method of multi-component mixture, which is easily affected by human subjective factors, and its results are inaccurate and unstable. This study developed a near-infrared (NIR) spectral characteristic extraction method based on a three-dimensional analysis space and establishes a high-accuracy qualitative identification model. First, the Norris derivative filtering algorithm was used in the pre-processing of the NIR spectrum to obtain a smooth main absorption peak. Then, the third-order tensor robust principal component analysis (TRPCA) algorithm was used for characteristic extraction, which effectively reduced the dimensionality of the raw NIR spectral data. Finally, on this basis, a qualitative identification model based on support vector machines (SVM) was constructed, and the classification accuracy reached 98.94%. Therefore, it is possible to develop a non-destructive, rapid qualitative detection system based on NIR spectroscopy to mine the subtle differences between classes and to use low-dimensional characteristic wavebands to detect the quality of complex multi-component mixtures. This method can be a key component of automatic quality control in the production of multi-component products.

Aquaporin 4 deficiency eliminates the beneficial effects of voluntary exercise in a mouse model of Alzheimer's disease.

Regular exercise has been shown to reduce the risk of Alzheimer's disease (AD). Our previous study showed that the protein aquaporin 4 (AQP4), which is specifically expressed on the paravascular processes of astrocytes, is necessary for glymphatic clearance of extracellular amyloid beta (Aß) from the brain, which can delay the progression of Alzheimer's disease. However, it is not known whether AQP4-regulated glymphatic clearance of extracellular Aß is involved in beneficial effects of exercise in AD patients. Our results showed that after 2 months of voluntary wheel exercise, APP/PS1 mice that were 3 months old at the start of the intervention exhibited a decrease in Aß burden, glial activation, perivascular AQP4 mislocalization, impaired glymphatic transport, synapse protein loss, and learning and memory defects compared with mice not subjected to the exercise intervention. In contrast, APP/PS1 mice that were 7 months old at the start of the intervention exhibited impaired AQP4 polarity and reduced glymphatic clearance of extracellular Aß, and the above-mentioned impairments were not alleviated after the 2-month exercise intervention. Compared with age-matched APP/PS1 mice, AQP4 knockout APP/PS1 mice had more serious defects in glymphatic function, Aß plaque deposition, and cognitive impairment, which could not be alleviated after the exercise intervention. These findings suggest that AQP4-dependent glymphatic transport is the neurobiological basis for the beneficial effects of voluntary exercises that protect against the onset of AD.

Interaction between physical activity and outdoor time on allostatic load in Chinese college students.

BACKGROUND: Physical activity (PA) deficiency, outdoor time reduction during college have been associated with higher cumulative physiological burden as measured by allostatic load (AL). Therefore, the present research sought to analyze the independent and interaction effects of PA and outdoor time on AL in college students. METHODS: A cross-sectional survey was conducted in two universities from April to May 2019. Self-assessment questionnaire and International Physical Activity Questionnaire Short Version (IPAQ-SF) were used in the investigation, AL level was assessed according to the results of biochemical examination, blood pressure and human body morphological measurements. Binary Logistic Analysis was used to analyze the relationships between PA, outdoor time and AL. RESULTS: The prevalence of low PA, low outdoor time and high AL were 16.3%, 71.1% and 47.6%, respectively. Low PA (OR=1.83, 95%CI: 1.20~2.78) and low outdoor time (OR=1.90, 95%CI: 1.35~2.67) are independently associated with high AL (P<0.05, for each). Interaction analysis indicated that low PA and low outdoor time were interactively associated with high AL (OR=2.93, 95%CI: 1.73~4.94, P<0.05). CONCLUSIONS: There were the significant independent and interaction effects between PA and outdoor time on AL. In the future, college students' physical education can be arranged reasonably to reduce the health risks.

Gene Expression Nebulas (GEN): a comprehensive data portal integrating transcriptomic profiles across multiple species at both bulk and single-cell levels.

Transcriptomic profiling is critical to uncovering functional elements from transcriptional and post-transcriptional aspects. Here, we present Gene Expression Nebulas (GEN, https://ngdc.cncb.ac.cn/gen/), an open-access data portal integrating transcriptomic profiles under various biological contexts. GEN features a curated collection of high-quality bulk and single-cell RNA sequencing datasets by using standardized data processing pipelines and a structured curation model. Currently, GEN houses a large number of gene expression profiles from 323 datasets (157 bulk and 166 single-cell), covering 50 500 samples and 15 540 169 cells across 30 species, which are further categorized into six biological contexts. Moreover, GEN integrates a full range of transcriptomic profiles on expression, RNA editing and alternative splicing for 10 bulk datasets, providing opportunities for users to conduct integrative analysis at both transcriptional and post-transcriptional levels. In addition, GEN provides abundant gene annotations based on value-added curation of transcriptomic profiles and delivers online services for data analysis and visualization. Collectively, GEN presents a comprehensive collection of transcriptomic profiles across multiple species, thus serving as a fundamental resource for better understanding genetic regulatory architecture and functional mechanisms from tissues to cells.

Depressive symptoms predict longitudinal changes of chronic inflammation at the transition to adulthood.

Background: Inflammation is closely related to poor mental and physical health, including depressive symptoms and its specific symptoms. To reveal the linear and nonlinear relationships between depressive symptoms and chronic inflammation levels, and perform further analysis of the associations between symptom-specificity of depressive symptoms and inflammation among young adults by using a prospective design. Methods: In this longitudinal study, we examined college students recruited from two universities in China, who were examined at baseline and 2-years follow-up. Depressive symptoms were measured by applying the Patient Health Questionnaire 9 (PHQ-9) at baseline. Plasma levels of four inflammatory biomarkers, including interleukin-6 (IL-6), interleukin-1ß (IL-1ß), tumor necrosis factor-α (TNF-α), and C reactive protein (CRP) were assayed at baseline and 2-year follow-up. In addition to the conventional generalized linear models, as well as restricted cubic splines were innovatively used to analyze the cross-sectional and longitudinal nonlinear relationships between depressive symptoms and inflammatory biomarkers. Results: Generalized linear model analysis revealed that there were no statistical associations between depressive symptoms and any inflammatory biomarker levels. The results of the restricted cubic spline demonstrated a U-shaped nonlinear association between depressive symptoms and ΔIL-1ß or ΔTNF-α (changes in baseline and 2-year follow-up), but these associations disappeared after adjusting the confounders. Symptom-specificity of depressive symptoms such as sleeping problems and suicidal ideation were associated with lower IL-1ß at baseline or changes in IL-1ß levels. Sleeping problems and psychomotor changes at baseline were associated with higher CRP at 2-year follow-up. Suicidal ideation at baseline was associated with changes in TNF-α levels. Conclusion: Our findings suggested that symptom-specificity of depressive symptoms was associated with inflammation during a 2-year follow-up at the transition to adulthood. Simultaneously, more research is warranted to seek the directionality of depressive symptoms and chronic inflammation.

GSA-Human: Genome Sequence Archive for Human.

The Genome Sequence Archive for Human (GSA-Human) is a data repository specialized for human genetic related data derived from biomedical researches, and also supports the data collection and management of National Key Research and Development Projects. GSA-Human has a data security management strategy according to the national regulations of human genetic resources. It provides two different models of data access: Open-access and Controlled-access. Open-access data are universally and freely accessible for global researchers, while Controlled-access ensures that data are accessed only by authorized users with the permission of the Data Access Committee (DAC). Till July 2021, GSA-Human has housed more than 5.27 PB of data from 750 datasets.

PIN3-mediated auxin transport contributes to blue light-induced adventitious root formation in Arabidopsis.

Adventitious rooting is a heritable quantitative trait that is influenced by multiple endogenous and exogenous factors in plants, and one important environmental factor required for efficient adventitious root formation is light signaling. However, the physiological significance and molecular mechanism of light underlying adventitious root formation are still largely unexplored. Here, we report that blue light-induced adventitious root formation is regulated by PIN-FORMED3 (PIN3)-mediated auxin transport in Arabidopsis. Adventitious root formation is significantly impaired in the loss-of-function mutants of the blue light receptors, PHOTOROPIN1 (PHOT1) and PHOTOROPIN2 (PHOT2), as well as the phototropic transducer, NON-PHOTOTROPIC HYPOCOTYL3 (NPH3). In addition, blue light enhanced the auxin content in the adventitious root, and the pin3 loss-of-function mutant had a reduced adventitious rooting response under blue light compared to the wild type. The PIN3 protein level was higher in plants treated with blue light than in those in darkness, especially in the hypocotyl pericycle, while PIN3-GFP failed to accumulate in nph3 PIN3::PIN3-GFP. Furthermore, the results showed that PIN3 physically interacted with NPH3, a key transducer in phototropic signaling. Taken together, our study demonstrates that blue light induces adventitious root formation through the phototropic signal transducer, NPH3, which regulates adventitious root formation by affecting PIN3-mediated auxin transport.