Suchergebnisse

Abstract
Genomic rearrangements describe gross DNA changes of the size ranging from a couple of hundred base pairs, the size of an average exon, to megabases (Mb). When greater than 3 to 5 Mb, such changes are usually visible microscopically by chromosome studies. Human diseases that result from genomic rearrangements have been called genomic disorders. Three major mechanisms have been proposed for genomic rearrangements in the human genome. Non-allelic homologous recombination (NAHR) is mostly mediated by low-copy repeats (LCRs) with recombination hotspots, gene conversion and apparent minimal efficient processing segments. NAHR accounts for most of the recurrent rearrangements: those that share a common size, show clustering of breakpoints, and recur in multiple individuals. Non-recurrent rearrangements are of different sizes in each patient, but may share a smallest region of overlap whose change in copy number may result in shared clinical features among different patients. LCRs do not mediate, but may stimulate non-recurrent events. Some rare NAHRs can also be mediated by highly homologous repetitive sequences (for example, Alu, LINE); these NAHRs account for some of the non-recurrent rearrangements. Other non-recurrent rearrangements can be explained by non-homologous end-joining (NHEJ) and the Fork Stalling and Template Switching (FoSTeS) models. These mechanisms occur both in germ cells, where the rearrangements can be associated with genomic disorders, and in somatic cells in which such genomic rearrangements can cause disorders such as cancer. NAHR, NHEJ and FoSTeS probably account for the majority of genomic rearrangements in our genome and the frequency distribution of the three at a given locus may partially reflect the genomic architecture in proximity to that locus. We provide a review of the current understanding of these three models.

Background: Females with novel coronavirus disease 2019 (COVID-19) state-ordered home isolation were associated with higher anxiety and reduced sleep quality than males. Sex differences in psychobehavioral changes during the COVID-19 stay-at home orders among healthcare workers remained unclear. The purpose of this study was to explore the sex differences in psychological burden and health behaviors among these persons. Methods: This was a cross-sectional study using online data available in the open Interuniversity Consortium for Political and Social Research (OPENICPSR). Healthcare workers including females and males who transitioned to working from home during the COVID-19 stay-at-home orders were included. Sex differences were compared using the chi-square test and Student's t-test. We performed logistic and linear regression analyses to determine the association of females with psychological burden and health behaviors. Results: A total of 537 respondents (425 females and 112 males) were enrolled in our study. Sex differences in age (42.1 ± 12.3 years vs. 46.6 ± 15.7 years, t = −2.821, p = 0.005), occupation (χ(2) = 41.037, p < 0.001), mood change (n = 297, 69.9% vs. n = 61, 54.5%, χ(2) = 9.482, p = 0.002), bedtime schedule (χ(2) = 6.254, p = 0.044) and news consumption (n = 344, 80.9% vs. n = 76, 67.9%, χ(2) = 8.905, p = 0.003) were statistically significant. Logistic regression showed that females was negatively associated with better mood status (OR = 0.586, 95% CI 0.153–2.247, p = 0.436). In addition, linear regression showed that females were not correlated with total sleep time after adjusting for sio-demographics, mental health outcomes and health behaviors (B = 0.038, 95% CI −0.313–0.388, p = 0.833). Conclusion: No sex differences in psychological burden and health behaviors of healthcare workers were found during the COVID-19 stay-at-home orders. The COVID-19 state-ordered home isolation may be a potential way to reduce disproportionate effects of COVID-19 pandemic on females and help to ...