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Misperception of nutritional status is common and hinders the progress of childhood obesity prevention. This study aimed to examine the effectiveness of a smartphone-assisted intervention to improve student and parental perception of students' nutritional status (underweight, normal weight, overweight, obese). We conducted a parallel-group controlled trial with a non-randomized design in three junior middle schools of Beijing, China in 2019. One school was allocated to the intervention group and two schools to the control group. A total of 573 students (aged 13.1 ± 0.4 years) participated in the trial. The 3-month intervention included three components: health education sessions for students and parents, regular monitoring of students' weight, and the provision of feedback via a smartphone application. Schools in the control group continued their usual practice. Primary outcomes included the student and parental accurate perception of students' nutritional status. The percentage of students' accurate perception of their own nutritional status in the intervention group increased from 49.0% to 59.2% from baseline to three months, whereas it decreased from 64.1% to 58.1% in the control group; the adjusted odds ratio (OR) between the two groups was 1.71 (95% confidence interval (CI): 1.13, 2.59). The intervention did not significantly improve parental perception of students' nutritional status ( p > 0.05). The study findings provided a brief approach for improving perception of nutritional status among middle school students.

Tuberculosis (TB), an infectious disease caused by Mycobacterium tuberculosis, kills over 1 million people worldwide annually. Development of drug resistance (DR) in the pathogen is a major challenge for TB control. We conducted whole-genome analysis of seven Taiwan M. tuberculosis isolates: One drug susceptible (DS) and five DR Beijing lineage isolates and one DR Euro-American lineage isolate. Developing a new method for DR mutation identification and applying it to the next-generation sequencing (NGS) data from the 6 Beijing lineage isolates, we identified 13 known and 6 candidate DR mutations and provided experimental support for 4 of them. We assembled the genomes of one DS and two DR Beijing lineage isolates and the Euro-American lineage isolate using NGS data. Moreover, using both PacBio and NGS sequencing data, we obtained a high-quality assembly of an extensive DR Beijing lineage isolate. Comparative analysis of these five newly assembled genomes and two published complete genomes revealed a large number of genetic changes, including gene gains and losses, indels and translocations, suggesting rapid evolution of M. tuberculosis. We found the MazEF toxin-antitoxin system in all the seven isolates studied and several interesting mutations in MazEF proteins. Finally, we used the four assembled Beijing lineage genomes to construct a high-quality Beijing lineage reference genome that is DS and contains all the genes in the four genomes. It contains 212 genes not found in the standard reference H37Rv, which is Euro-American. It is therefore a better reference than H37Rv for the Beijing lineage, the predominant lineage in Asia., (© The Author(s) 2020. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.)

Objective: To analyze the influencing factors of acute gastroenteritis outbreaks caused by norovirus in Beijing from 2014 to 2018. Methods: Data of acute gastroenteritis events caused by norovirus in Beijing from April 2014 to March 2018 were collected. Unconditional logistic regression model was conducted to identify the risk factors of the outbreaks. Results: A total of 765 acute gastroenteritis epidemics caused by norovirus were reported in Beijing, in which 85.88 % (657/765) were cluster events and 14.12 % (108/765) were outbreaks. Among the outbreaks, 70.37 % (76/108) were reported in 2017; 84.26 % (91/108) were reported in winter and spring; 88.89 % (96/108) were reported in kindergartens, primary or secondary schools; 81.48 % (88/108) were through person-to-person transmission; 93.52 % (101/108) were caused by norovirus GⅡ infection. The risk of outbreaks in suburban and out suburb area were 1.84 times (95 %CI : 1.13-3.02) and 3.78 times (95 %CI : 1.62-8.82) as high as that in urban area, respectively. The risks of outbreaks in primary, secondary schools and other institutions were 6.26 times (95 %CI : 3.53-11.10), 14.98 times (95 %CI : 6.23-36.01) and 8.71 times (95 %CI : 3.07-24.71) as high as that in kindergartens, respectively. The risk of outbreak in which patients having lower hospital visiting rate than the median rate of all events was 2.29 times than that in the context of having higher hospital visiting rate (95 %CI :1.42-3.68). The risk of foodborne outbreak was 14.55 times as high as that transmitted through person-to-person (95 %CI : 3.15-67.07). Conclusion: Measures such as strengthening the prevention and control of norovirus outbreaks in suburbs, primary schools, secondary schools and other institutions, promoting patients to visit the hospital actively, improving the management of foodborne events and kitchen workers should be taken to reduce the incidence of acute gastroenteritis outbreaks caused by norovirus.

Objective: To analyze the spatial distribution of the incidence of tuberculosis (TB) in China from 2012 to 2014 and provide evidence for the prevention and control of TB. Methods: The database of TB in China from 2012 to 2014 was established by using geographical information system, the spatial distribution map was drawn, trend analysis and spatial autocorrelation analysis were conducted to explore the spatial distribution pattern of TB and identify hot areas. Results: The trend surface analysis showed that the incidence of TB decreased gradually from the west to the east in China, and the U type curve could reflect the TB distribution from the south to the north; Global spatial autocorrelation analysis showed the 2012-2014 global Moran's I were 0.366, 0.364 and 0.358 ( P <0.01), suggesting that the incidence of TB had a spatial clustering in China; Local Getis-OrdG (i) spatial autocorrelation analysis by ArcGIS software showed that there was 11 cluster areas, 3 high incidence areas (Xinjiang, Tibet, Qinghai) and 8 low incidence areas (Beijing, Tianjin, Shanghai, Hebei, Inner Mongolia, Shanxi, Shandong, Jiangsu). Conclusion: The incidence of TB had obviously spatial clustering characteristic, the areas at high risk were mainly in the northwestern and plateau area in China.