Differences in health-related behaviors between middle school, high school, and college students in Jiangsu province, China

BACKGROUND AND OBJECTIVES: Increasing rates of obesity among Chinese adolescents has become a major public health concern in recent years. Studies have shown that factors such as food choices, physical activity, and screen time play important roles in fostering obesity. We examined a number of biological and social determinants that influence these factors. To determine whether dietary behavior, physical activity, and screen time varied among students in different stages of their education. METHODS AND STUDY DESIGN: Students in 13 cities across Jiangsu Province completed an anonymous survey assessing demographics and various health-related behaviors in a controlled setting. The survey population ranged from middle school students to undergraduates. 55,361 surveys were returned, and 46,611 (84.2%) were usable for the analysis. Multiple linear regression models were used to investigate the relationship between four behavioral factors (dietary behavior, screen time, physical activity, and moderate exercise) and seven predictors (gender, age, BMI, mother's education, nearsightedness, allowance, and geographic region). RESULTS: Baseline characteristics of the survey population analyzed by education level (middle school, high school, college and beyond) showed moderate differences in demographics among the three groups. Physical activity, moderate exercise, and dietary behavior decreased with educational level, while screen time increased. All predictors in the four considered regression models were statistically significant. CONCLUSIONS: This unique, large-scale survey of Chinese students in a region of contrasting economic development revealed numerous relationships between health-related diet and physical-activity, region, and education level. These findings can inform the development of measures to counteract the rise of obesity in China

Morphological and Genomic Characterizations of Redi, a Novel Mycobacterium Phage

Mentor: Sarah Elgin and Kathy Hafer From the Washington University Undergraduate Research Digest: WUURD, Volume 6, Issue 1, Fall 2010. Published by the Office of Undergraduate Research. Henry Biggs, Director of Undergraduate Research and Associate Dean in the College of Arts & Sciences; Joy Zalis Kiefer, Undergraduate Research Coordinator, Co-editor, and Assistant Dean in the College of Arts & Sciences; Kristin Sobotka, Editor

Corn Classification System based on Computer Vision

Automated classification of corn is important for corn sorting in intelligent agriculture. This paper presents a reliable corn classification method based on techniques of computer vision and machine learning. To discriminate different damaged types of corns, a line profile segmentation method is firstly used to segment and separate a group of touching corns. Then, twelve color features and five shape features are extracted for each individual corn object. Finally, a maximum likelihood estimator is trained to classify normal and damaged corns. To evaluate the performance of the proposed method, a private dataset consisting of images of normal corn and six kinds of damage corns, including heat-damaged, germ-damaged, cob-rot-damaged, blue eye mold-damaged, insect-damaged, and surface mold-damaged, were collected in this work. The proposed method achieved an accuracy of 96.67% for the classification between normal corns and the first four common damaged corns, and an accuracy of 74.76% was achieved for the classification between normal corns and six kinds of damaged corns. The experimental results demonstrated the effectiveness of the proposed corn classification system

Population Scale Retrospective Analysis Reveals Potential Risk of Cholestasis in Pregnant Women Taking Omeprazole, Lansoprazole, and Amoxicillin

In nearly 50% of patients with drug-induced liver injury, the bile flow is impaired known as cholestasis. Intrahepatic cholestasis of pregnancy (ICP) is the most common liver disease that happens in pregnancy. Some of the clinical symptoms include pruritus, dark urine, and abnormal liver function tests. A rise of serum bile acids is the most accurate diagnostic evidence. ICP may lead to premature birth, fetal distress, and even postpartum hemorrhage or stillbirth in some severe cases. Higher bile acid levels (> 40 μmol/L) are associated with higher rates of adverse fetal outcomes. Due to the multifactorial nature of ICP, its etiology is still not fully understood. Therefore, the current treatments of ICP are limited to control symptoms and protect fetuses. Among various causing factors, drug exposure during pregnancy is one common factor, and it can be prevented if we know drugs with increasing risk of cholestasis. Here we analyzed over 9.5 million FDA adverse effect reports to identify drugs with increasing risks of cholestasis as an adverse effect. Patients treated for cholestasis or liver diseases were removed. The odds ratio analysis reveals that lansoprazole (LSPZ), omeprazole (OMPZ) and amoxicillin (AMXC) are associated with an increased risk of cholestasis. LSPZ is associated with increased reported cholestasis by a factor of 2.32 (OR with 95% confidence interval [2.21, 2.43]). OMPZ is associated with increased reported cholestasis by a factor of 2.61 [2.54, 2.69]. AMXC is associated with increased reported cholestasis adverse effect by a factor of 6.79 [6.49, 7.11]. The risk of cholestasis associated with these three drugs is further increased in pregnant women. These findings justify careful reassessment of the safety of the three identified drugs

Expressing Anger Is More Dangerous than Feeling Angry when Driving

Anger is an emotion that drivers often feel and express while driving, and it is believed by researchers to be an important cause of dangerous driving behavior. In this study, the relationships between driving trait anger, driving anger expression, and dangerous driving behaviors were analyzed. The Driving Anger Scale (DAS) was used to measure driving trait anger, whereas the Driving Anger Expression (DAX) Inventory was used to measure expressions of driving anger. A sample of 38 drivers completed the DAS, DAX, and a driving simulation session on a simulator where their driving behaviors were recorded. Correlation analysis showed that the higher scores on the DAS were associated with longer durations of speeding in the simulator. The more participants expressed their anger in verbal and physical ways, the more likely they were to crash the virtual vehicle during the simulation. Regression analyses illustrated the same pattern. The findings suggest that, although trait anger is related to speeding, the passive expression of anger is the real factor underling traffic accidents. This study extends findings about the predictive effects of self-report scales of driving behaviors to behaviors recorded on a simulator. Thus, if in traffic safety propaganda, guiding drivers to use positive ways to cope with driving anger is recommended by our findings

Identification of paternal germline mosaicism by MicroSeq and targeted next‐generation sequencing

Abstract Background Prezygotic de novo mutations may be inherited from parents with germline mosaicism and are often overlooked when the resulting phenotype affects only one child. We aimed to identify paternal germline mosaicism in an index family and provide a strategy to determine germline mosaicism.‘ Methods Whole‐exome sequencing was performed on an Alport syndrome‐affected child. Variants were validated using Sanger sequencing in the pedigree analysis. An apparent de novo mutation was tested by next‐generation sequencing (NGS) following chromosome microdissection of the mutant region (MicroSeq) to clarify its homologous chromosome source. Mosaic mutation in sperm samples was detected using targeted next‐generation sequencing (TNGS). Self‐prepared mosaic DNA samples of the 3% and 0.1% mutant fractions were used to evaluate the TNGS detection sensitivity. Results Two novel heterozygous variants, maternally inherited c.1322delT (p.Ile441Thrfs*17) and the de novo mutation c.2939T>A (p.Leu980Ter), in the COL4A3 gene were discovered in the propositus. MicroSeq identified c.2939T>A in the paternal chromosome, which was in trans with c.1322delT. The frequency of c.2937A was 2.65% in the father's sperm sample. We also showed that a 500X depth coverage may detect a mosaic mutation with an allele frequency as low as 2%–3% using TNGS. Conclusion MicroSeq is a valuable tool to identify the allele source of de novo mutations in a single patient. TNGS can be used to assess the mosaic ratios of known sites. We provided a systematic algorithm to detect germinal mosaicism in a single patient. This algorithm may have implications for genetic and reproductive counseling on germline mosaicism

Map of the route that participants had to drive (instructed by an audio guide).

<p>Map of the route that participants had to drive (instructed by an audio guide).</p

Descriptive statistics for the driving-related variables.

<p>Descriptive statistics for the driving-related variables.</p

Correlations between the driving-related variables.

<p>Correlations between the driving-related variables.</p

Nanostructured Ternary Nanocomposite of rGO/CNTs/MnO₂ for High-Rate Supercapacitors

A three-dimensional (3D) nanostructure comprised of ternary rGO/CNTs/MnO₂ nanocomposites was successfully developed and prepared for high-rate supercapacitors. The optimized nanocomposite exhibited a high specific capacitance (SC) of 319 F g^–1 with enhanced rate capability (222 F g^–1 even at 60 A g^–1) and cycling stability (85.4% retention of original capacity after cycling for 3000 times) in a 1 M Na₂SO₄ aqueous solution. Such outstanding capacitive behaviors are mainly attributed to smart nanostructures, which possess several advantages as supercapacitor electrodes, such as easy access pseudoactive species with high utilization and fast ion/electron transfer and also a strong interaction between the 3D rGO/CNTs carbon matrix and pseudoactive MnO₂ nanoflakes. It is concluded that the present 3D rGO/CNTs/MnO₂ nanocomposites can serve as promising electrode materials for advanced supercapacitors