l e t t e r sHow an insect evolves to become a successful herbivore is of profound biological and practical importance. Herbivores are often adapted to feed on a specific group of evolutionarily and biochemically related host plants 1 , but the genetic and molecular bases for adaptation to plant defense compounds remain poorly understood 2 . We report the first whole-genome sequence of a basal lepidopteran species, Plutella xylostella, which contains 18,071 protein-coding and 1,412 unique genes with an expansion of gene families associated with perception and the detoxification of plant defense compounds. A recent expansion of retrotransposons near detoxification-related genes and a wider system used in the metabolism of plant defense compounds are shown to also be involved in the development of insecticide resistance. This work shows the genetic and molecular bases for the evolutionary success of this worldwide herbivore and offers wider insights into insect adaptation to plant feeding, as well as opening avenues for more sustainable pest management.The global pest P. xylostella (Lepidoptera: Yponomeutidae) is thought to have coevolved with the crucifer plant family 3 ( Supplementary Fig. 1) and has become the most destructive pest of economically important food crops, including rapeseed, cauliflower and cabbage 4 . Recently, the total cost of damage and management worldwide was estimated at $4-5 billion per annum 5,6 . This insect is the first species to have evolved resistance to dichlorodiphenyltrichloroethane (DDT) in the 1950s 7 and to Bacillus thuringiensis (Bt) toxins in the 1990s 8 and has developed resistance to all classes of insecticide, making it increasingly difficult to control 9,10 . P. xylostella provides an exceptional system for understanding the genetic and molecular bases of how insect herbivores cope with the broad range of plant defenses and chemicals encountered in the environment (Supplementary Fig. 2).We used a P. xylostella strain (Fuzhou-S) collected from a field in Fuzhou in southeastern China (26.08 °N, 119.28 °E) for sequencing ( Supplementary Fig. 1). Whole-genome shotgun-based Illumina sequencing of single individuals (Supplementary Table 1), even after ten generations of laboratory inbreeding, resulted in a poor initial assembly (N50 = 2.4 kb, representing the size above which 50% of the total length of the sequences is included), owing to high levels of heterozygosity ( Supplementary Figs. 3 and 4 and Supplementary Table 2). Subsequently, we sequenced 100,800 fosmid clones (comprising ~10× the genome length) to a depth of 200× ( Supplementary Fig. 5 and Supplementary Tables 3-5), assembling the resulting sequence data into 1,819 scaffolds, with an N50 of 737 kb, spanning ~394 Mb of the genome sequence (version 1; Supplementary Fig. 6 and Supplementary Table 6). The assembly covered 85.5% of a set of protein-coding ESTs (Supplementary Tables 7 and 8) generated by transcriptome sequencing 11 . Alignment of a subject scaffold against a 126-kb BAC (GenBank GU058050) from an altern...

SUMMARY Recently, it has been recognized that oral infection, especially periodontitis, may affect the course and pathogenesis of a number of systemic diseases, such as cardiovascular disease, bacterial pneumonia, diabetes mellitus, and low birth weight. The purpose of this review is to evaluate the current status of oral infections, especially periodontitis, as a causal factor for systemic diseases. Three mechanisms or pathways linking oral infections to secondary systemic effects have been proposed: (i) metastatic spread of infection from the oral cavity as a result of transient bacteremia, (ii) metastatic injury from the effects of circulating oral microbial toxins, and (iii) metastatic inflammation caused by immunological injury induced by oral microorganisms. Periodontitis as a major oral infection may affect the host's susceptibility to systemic disease in three ways: by shared risk factors; subgingival biofilms acting as reservoirs of gram-negative bacteria; and the periodontium acting as a reservoir of inflammatory mediators. Proposed evidence and mechanisms of the above odontogenic systemic diseases are given.

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Background Since its outbreak in January 2020, COVID-19 has quickly spread worldwide and has become a global pandemic. Social media platforms have been recognized as important tools for health-promoting practices in public health, and the use of social media is widespread among the public. However, little is known about the effects of social media use on health promotion during a pandemic such as COVID-19. Objective In this study, we aimed to explore the predictive role of social media use on public preventive behaviors in China during the COVID-19 pandemic and how disease knowledge and eHealth literacy moderated the relationship between social media use and preventive behaviors. Methods A national web-based cross-sectional survey was conducted by a proportionate probability sampling among 802 Chinese internet users (“netizens”) in February 2020. Descriptive statistics, Pearson correlations, and hierarchical multiple regressions were employed to examine and explore the relationships among all the variables. Results Almost half the 802 study participants were male (416, 51.9%), and the average age of the participants was 32.65 years. Most of the 802 participants had high education levels (624, 77.7%), had high income >¥5000 (US $736.29) (525, 65.3%), were married (496, 61.8%), and were in good health (486, 60.6%). The average time of social media use was approximately 2 to 3 hours per day (mean 2.34 hours, SD 1.11), and the most frequently used media types were public social media (mean score 4.49/5, SD 0.78) and aggregated social media (mean score 4.07/5, SD 1.07). Social media use frequency (β=.20, P<.001) rather than time significantly predicted preventive behaviors for COVID-19. Respondents were also equipped with high levels of disease knowledge (mean score 8.15/10, SD 1.43) and eHealth literacy (mean score 3.79/5, SD 0.59). Disease knowledge (β=.11, P=.001) and eHealth literacy (β=.27, P<.001) were also significant predictors of preventive behaviors. Furthermore, eHealth literacy (P=.038) and disease knowledge (P=.03) positively moderated the relationship between social media use frequency and preventive behaviors, while eHealth literacy (β=.07) affected this relationship positively and disease knowledge (β=–.07) affected it negatively. Different social media types differed in predicting an individual’s preventive behaviors for COVID-19. Aggregated social media (β=.22, P<.001) was the best predictor, followed by public social media (β=.14, P<.001) and professional social media (β=.11, P=.002). However, official social media (β=.02, P=.597) was an insignificant predictor. Conclusions Social media is an effective tool to promote behaviors to prevent COVID-19 among the public. Health literacy is essential for promotion of individual health and influences the extent to which the public engages in preventive behaviors during a pandemic. Our results not only enrich the theoretical paradigm of public health management and health communication but also have practical implications in pandemic control for China and other countries.