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Background The emerging of psychological problems triggered by COVID-19 particularly in children have been extensively highlighted and emphasized, but original research in this respect is still lagging behind. Therefore, we designed this study to evaluate the impact of COVID-19 pandemic on mental health and the effectiveness and attitudes towards online education among Chinese children aged 7–15 years. Methods A detailed questionnaire, comprising of 62 questions was designed and parents or caretakers of 7 to 15 years old children were invited to participate via WeChat, a multi-purpose messaging, social media and mobile payment app, which is widely used by the Chinese population. A total of 668 parents across different regions of China were included. Results During COVID-19 pandemic, 20.7 and 7.2% children report experiencing post-traumatic stress disorder (PTSD) and depressive symptoms due to the COVID-19 pandemic. PTSD and SMFQ-P scores are significantly higher in middle school and boarding school students compared to primary and day school students. Multiple logistic regression analysis revealed that school system and province of origin are factors significantly associated with developing PSTD symptoms. 44.3% respondents feel online education is effective in gaining knowledge and improving practical and communications skills. 78.0% believe the online education system is efficient. Overall 79.8% respondents are satisfied and children can adapt to this new education system. During the COVID-19 pandemic, we found 1 in five children have PTSD and 1 in 14 children have depressive symptoms. Conclusion In summary, COVID-19 epidemic has caused PTSD and depression symptoms among Chinese children aged 7 to 15 years. In general, a large proportion of respondents are satisfied with online education, but still a substantial proportion of students are not comfortable with this new form of learning. Authorities should optimize online education systems and implement effective interventions to cope with the psychological effects of COVID-19 on children, as it is affecting the global population and remains uncertain when it will end.

Amorpha-4,11-diene synthase (ADS) and Cyt P450 monooxygenase (CYP71AV1) in Artemisia annua L. are two key enzymes involved in the biosynthesis of artemisinin. The promoters of ADS and CYP71AV1 contain E-box elements, which are putative binding sites for basic helix-loop-helix (bHLH) transcription factors. This study successfully isolated a bHLH transcription factor gene from A. annua, designated as AabHLH1, from a cDNA library of the glandular secretory trichomes (GSTs) in which artemisinin is synthesized and sequestered. AabHLH1 encodes a protein of 650 amino acids containing one putative bHLH domain. AabHLH1 and ADS genes were strongly induced by ABA and the fungal elicitor, chitosan. The transient expression analysis of the AabHLH1-green fluorescent protein (GFP) reporter gene revealed that AabHLH1 was targeted to nuclei. Biochemical analysis demonstrated that the AabHLH1 protein was capable of binding to the E-box cis-elements, present in both ADS and CYP71AV1 promoters, and possessed transactivation activity in yeast. In addition, transient co-transformation of AabHLH1 and CYP71AV1Pro::GUS in A. annua leaves showed a significant activation of the expression of the GUS (β-glucuronidase) gene in transformed A. annua, but mutation of the E-boxes resulted in abolition of activation, suggesting that the E-box is important for the CYP71AV1 promoter activity. Furthermore, transient expression of AabHLH1 in A. annua leaves increased transcript levels of the genes involved in artemisinin biosynthesis, such as ADS, CYP71AV1 and HMGR. These results suggest that AabHLH1 can positively regulate the biosynthesis of artemisinin.

Background: Net primary productivity (NPP) in forests plays an important role in the global carbon cycle. However, it is not well known about the increase rate of China's forest NPP, and there are different opinions about the key factors controlling the variability of forest NPP. Methods: This paper established a statistics-based multiple regression model to estimate forest NPP, using the observed NPP, meteorological and remote sensing data in five major forest ecosystems. The fluctuation values of NPP and environment variables were extracted to identify the key variables influencing the variation of forest NPP by correlation analysis. Results: The long-term trends and annual fluctuations of forest NPP between 2000 and 2018 were examined. The results showed a significant increase in forest NPP for all five forest ecosystems, with an average rise of 5.2 gC•m − 2 •year − 1 over China. Over 90% of the forest area had an increasing NPP range of 0-161 gC•m − 2 •year − 1. Forest NPP had an interannual fluctuation of 50-269 gC•m − 2 •year − 1 for the five major forest ecosystems. The evergreen broadleaf forest had the largest fluctuation. The variability in forest NPP was caused mainly by variations in precipitation, then by temperature fluctuations. Conclusions: All five forest ecosystems in China exhibited a significant increasing NPP along with annual fluctuations evidently during 2000-2018. The variations in China's forest NPP were controlled mainly by changes in precipitation.