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BackgroundSub-therapeutic antibiotics are widely used as growth promoters in the poultry industry; however, the resulting antibiotic resistance threatens public health. A plant-derived growth promoter, Macleaya cordata extract (MCE), with effective ingredients of benzylisoquinoline alkaloids, is a potential alternative to antibiotic growth promoters. Altered intestinal microbiota play important roles in growth promotion, but the underlying mechanism remains unknown.ResultsWe generated 1.64 terabases of metagenomic data from 495 chicken intestinal digesta samples and constructed a comprehensive chicken gut microbial gene catalog (9.04 million genes), which is also the first gene catalog of an animal’s gut microbiome that covers all intestinal compartments. Then, we identified the distinctive characteristics and temporal changes in the foregut and hindgut microbiota. Next, we assessed the impact of MCE on chickens and gut microbiota. Chickens fed with MCE had improved growth performance, and major microbial changes were confined to the foregut, with the predominant role of Lactobacillus being enhanced, and the amino acids, vitamins, and secondary bile acids biosynthesis pathways being upregulated, but lacked the accumulation of antibiotic-resistance genes. In comparison, treatment with chlortetracycline similarly enriched some biosynthesis pathways of nutrients in the foregut microbiota, but elicited an increase in antibiotic-producing bacteria and antibiotic-resistance genes.ConclusionThe reference gene catalog of the chicken gut microbiome is an important supplement to animal gut metagenomes. Metagenomic analysis provides insights into the growth-promoting mechanism of MCE, and underscored the importance of utilizing safe and effective growth promoters.Electronic supplementary materialThe online version of this article (10.1186/s40168-018-0590-5) contains supplementary material, which is available to authorized users.

IMPORTANCE Associations between adverse childhood experiences (ACEs) and chronic diseases among middle-aged or older Chinese individuals have not been well documented. In addition, whether demographic and socioeconomic characteristics modify any such associations has been underexplored. OBJECTIVESTo examine associations between ACEs and subsequent chronic diseases and to assess whether age, sex, educational level, annual per capita household expenditure level, and childhood economic hardship modify these associations. DESIGN, SETTING, AND PARTICIPANTSThis population-based cross-sectional study used data from the China Health and Retirement Longitudinal Study (CHARLS), a survey of residents aged 45 years or older in 28 provinces across China; specifically, the study used data from the CHARLS life history survey conducted from June 1 to December 31, 2014, and a CHARLS follow-up health survey conducted from July 1 to September 30, 2015. The study population included 11 972 respondents aged 45 years or older who had data on at least 1 of 14 specified chronic diseases and information on all 12 of the ACE indicators included in this study. Data analysis was performed from December 1 to 30, 2020. EXPOSURES Any of 12 ACEs (physical abuse, emotional neglect, household substance abuse, household mental illness, domestic violence, incarcerated household member, parental separation or divorce, unsafe neighborhood, bullying, parental death, sibling death, and parental disability), measured by indicators on a questionnaire. The number of ACEs per participant was summed and categorized into 1 of 5 cumulative-score groups: 0, 1, 2, 3, and 4 or more.MAIN OUTCOMES AND MEASURES Hypertension, dyslipidemia, diabetes, heart disease, stroke, chronic lung disease, asthma, liver disease, cancer, digestive disease, kidney disease, arthritis, psychiatric disease, and memory-related disease were defined by self-reported physician diagnoses or in combination with health assessment and medication data. Multimorbidity was defined as the presence of 2 or more of these 14 chronic diseases. Logistic regression models were used to assess associations of the 12 ACEs with the 14 chronic diseases and with multimorbidity. Modification of the associations by demographic and socioeconomic characteristics was assessed by stratified analyses and tests for interaction. RESULTSOf the 11 972 individuals included (mean [SD] age, 59.85 [9.56] years; 6181 [51.6%] were females), 80.9% had been exposed to at least 1 ACE and 18.0% reported exposure to 4 or more ACEs.Compared with those without ACE exposure, participants who experienced 4 or more ACEs had increased risks of dyslipidemia, chronic lung disease, asthma, liver disease, digestive disease, kidney (continued) Key Points Question Are adverse childhood experiences (ACEs) associated with subsequent chronic diseases among middle-aged or older adults in China, and do demographic and socioeconomic characteristics modify these associations? Findings In this cross-sectional study of 11 972 Chinese individuals age...

Association mapping based on the linkage disequilibrium provides a promising tool to identify genes responsible for quantitative variations underlying complex traits. Presented here is a maize association mapping panel consisting of 155 inbred lines with mainly temperate germplasm, which was phenotyped for 34 traits and genotyped using 82 SSRs and 1,536 SNPs. Abundant phenotypic and genetic diversities were observed within the panel based on the phenotypic and genotypic analysis. A model-based analysis using 82 SSRs assigned all inbred lines to two groups with eight subgroups. The relative kinship matrix was calculated using 884 SNPs with minor allele frequency > or = 20% indicating that no or weak relationships were identified for most individual pairs. Three traits (total tocopherol content in maize kernel, plant height and kernel length) and 1,414 SNPs with missing data < 20% were used to evaluate the performance of four models for association mapping analysis. For all traits, the model controlling relative kinship (K) performed better than the model controlling population structure (Q), and similarly to the model controlling both population structure and relative kinship (Q + K) in this panel. Our results suggest this maize panel can be used for association mapping analysis targeting multiple agronomic and quality traits with optimal association model.

Introduction: Limited longitudinal studies on smoking cessation have been reported in Asia, and it remains unclear whether determinants of quitting are similar to those found in Western countries. This study examined prospective predictors of smoking cessation among adult smokers in Thailand and Malaysia.Methods: Four thousand and four smokers were surveyed in Malaysia and Thailand in 2005. Of these, 2,426 smokers were followed up in 2006 (61% retention). Baseline measures of sociodemographics, dependence, and interest in quitting were used to predict both making quit attempts and point prevalence maintenance of cessation.Results: More Thai than Malaysian smokers reported having made quit attempts between waves, but among those who tried, the rates of staying quit were not considerably different between Malaysians and Thais. Multivariate analyses showed that smoking fewer cigarettes per day, higher levels of self-efficacy, and more immediate quitting intentions were predictive of both making a quit attempt and staying quit in both countries. Previous shorter quit attempts and higher health concerns about smoking were only predictive of making an attempt, whereas prior abstinence for 6 months or more and older age were associated with maintenance.Discussion: In Malaysia and Thailand, predictors of quitting activity appear to be similar. However, as in the West, predictors of making quit attempts are not all the same as those who predict maintenance. The actual predictors differ in potentially important ways from those found in the West. We need to determine the relative contributions of cultural factors and the shorter history of efforts to encourage quitting in Asia.

Comprehensive identification of somatic structural variations (SVs) and understanding their mutational mechanisms in cancer might contribute to understanding biological differences and help to identify new therapeutic targets. Unfortunately, characterization of complex SVs across the whole genome and the mutational mechanisms underlying esophageal squamous cell carcinoma (ESCC) is largely unclear. To define a comprehensive catalog of somatic SVs, affected target genes, and their underlying mechanisms in ESCC, we re-analyzed whole-genome sequencing (WGS) data from 31 ESCCs using Meerkat algorithm to predict somatic SVs and Patchwork to determine copy-number changes. We found deletions and translocations with NHEJ and alt-EJ signature as the dominant SV types, and 16% of deletions were complex deletions. SVs frequently led to disruption of cancer-associated genes (e.g., CDKN2A and NOTCH1) with different mutational mechanisms. Moreover, chromothripsis, kataegis, and breakage-fusion-bridge (BFB) were identified as contributing to locally mis-arranged chromosomes that occurred in 55% of ESCCs. These genomic catastrophes led to amplification of oncogene through chromothripsis-derived double-minute chromosome formation (e.g., FGFR1 and LETM2) or BFB-affected chromosomes (e.g., CCND1, EGFR, ERBB2, MMPs, and MYC), with approximately 30% of ESCCs harboring BFB-derived CCND1 amplification. Furthermore, analyses of copy-number alterations reveal high frequency of whole-genome duplication (WGD) and recurrent focal amplification of CDCA7 that might act as a potential oncogene in ESCC. Our findings reveal molecular defects such as chromothripsis and BFB in malignant transformation of ESCCs and demonstrate diverse models of SVs-derived target genes in ESCCs. These genome-wide SV profiles and their underlying mechanisms provide preventive, diagnostic, and therapeutic implications for ESCCs.

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