With the COVID-19 pandemic, behavioural scientists aimed to illuminate reasons why people comply with (or not) large-scale cooperative activities. Here we investigated the motives that underlie support for COVID-19 pr...
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With the COVID-19 pandemic, behavioural scientists aimed to illuminate reasons why people comply with (or not) large-scale cooperative activities. Here we investigated the motives that underlie support for COVID-19 preventive behaviours in a sample of 12,758 individuals from 34 countries. We hypothesized that the associations of empathic prosocial concern and fear of disease with support towards preventive COVID-19 behaviours would be moderated by trust in the government. Results suggest that the association between fear of disease and support for COVID-19 preventive behaviours was strongest when trust in the government was weak (both at individual- and country-level). Conversely, the association with empathic prosocial concern was strongest when trust in the government was high, but this moderation was only found at individual-level scores of governmental trust. We discuss how motivations may be shaped by socio-cultural context, and outline how findings may contribute to a better understanding of collective action during global crises.
FAST is a multi-threaded, I/O optimized Seed-and-Extend alignment program. FAST is extensible to nucleotide sequences making it comparable to both BLASTn and BLASTp, and also features several new usage flags reporting...
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ISBN:
(纸本)9781509000128
FAST is a multi-threaded, I/O optimized Seed-and-Extend alignment program. FAST is extensible to nucleotide sequences making it comparable to both BLASTn and BLASTp, and also features several new usage flags reporting only HSPs meeting user defined e-value cut-offs. FASTs threaded database construction allows fast, low memory database construction e.g., RefSeq (9.4GB) can be indexed in under 5 minutes using 20 threads. The threaded database construction gives users the ability to create custom databases on demand which is useful for tasks requiring self-alignment, such as network construction [30]. Finally, FAST supports incremental database construction enabling users to keep their databases up-to-date by adding sequences without suffering the cost of reformatting the entire database. The FAST source is freely available through GitHub https:// ***/hallamlab/FAST and test datasets can be found on Dropbox https://***/sh/xvvavweuzgqybc4/ AAAWCrRnol67ZsXi2qLQWUuOa?
In total, 15 out of 51 loci could be linked to three major pathways involved in susceptibility and severity defined by expert-driven classification (Supplementary Note): (1) viral entry; (2) entry defence in airway mu...
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In total, 15 out of 51 loci could be linked to three major pathways involved in susceptibility and severity defined by expert-driven classification (Supplementary Note): (1) viral entry; (2) entry defence in airway mucus; and (3) type I interferon response.
[...]the phenome-wide association analysis identified nine loci involved in the upkeep of healthy lung tissue.
[...]four loci contain candidate causal genes for entry defence in the airway mucus (Extended data Fig. lb), such as previously reported MUC1/THBS3 (lq22) and MUC5B (lip 15.5) as well as novel MUC4 (3q29) and MUC16 (19pl3.2).
[...]the previously reported locus lq22 contains an intergenic lead variant rsl2752585:G>A that decreases the risk of infection (OR = 0.98,95% CI = 0.97-0.98, P = 1.5 x 10_11) and increases MUCI expression in the oesophagus mucosa in GTEx v8 (P=5.2 x 10-9).
[...]six loci contain candidate causal genes that are linked to the type I interferon pathway (Extended data Fig. 1c), such as previously reported IFNAR2 (21q22.11), OAS1 (12q24.13) and TYK2 (19pl3.2), as well as additionally identified JAKI (lp31.3), IRF1 (5q31.1) and IFNa-coding genes (9p21.3).
Genome-wide association studies (GWAS) have identified >250 loci for body mass index (BMI), implicating pathways related to neuronal biology. Most GWAS loci represent clusters of common, noncoding variants from whi...
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Genome-wide association studies (GWAS) have identified >250 loci for body mass index (BMI), implicating pathways related to neuronal biology. Most GWAS loci represent clusters of common, noncoding variants from which pinpointing causal genes remains challenging. Here we combined data from 718,734 individuals to discover rare and low-frequency (minor allele frequency (MAF) < 5%) coding variants associated with BMI. We identified 14 coding variants in 13 genes, of which 8 variants were in genes (ZBTB7B, ACHE, RAPGEF3, RAB21, ZFHX3, ENTPD6, ZFR2 and ZNF169) newly implicated in human obesity, 2 variants were in genes (MC4R and KSR2) previously observed to be mutated in extreme obesity and 2 variants were in GIPR. The effect sizes of rare variants are ~10 times larger than those of common variants, with the largest effect observed in carriers of an MC4R mutation introducing a stop codon (***35Ter, MAF = 0.01%), who weighed ~7 kg more than non-carriers. Pathway analyses based on the variants associated with BMI confirm enrichment of neuronal genes and provide new evidence for adipocyte and energy expenditure biology, widening the potential of genetically supported therapeutic targets in obesity.
Change History: This Article has been retracted; see accompanying Retraction. Corrected online 20 January: In this Article, author Frank Rigo was incorrectly listed with a middle initial; this has been corrected in th...
Change History: This Article has been retracted; see accompanying Retraction. Corrected online 20 January: In this Article, author Frank Rigo was incorrectly listed with a middle initial; this has been corrected in the online versions of the paper.
In the version of this article initially published, the name of author Manuela Gago-Dominguez was misspelled as Manuela Gago Dominguez. The error has been corrected in the HTML and PDF version of the article.
In the version of this article initially published, the name of author Manuela Gago-Dominguez was misspelled as Manuela Gago Dominguez. The error has been corrected in the HTML and PDF version of the article.
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