Honorebuck9856

Leprosy remains concentrated among the poorest communities in low-and middle-income countries and it is one of the primary infectious causes of disability. Although there have been increasing advances in leprosy surveillance worldwide, leprosy underreporting is still common and can hinder decision-making regarding the distribution of financial and health resources and thereby limit the effectiveness of interventions. In this study, we estimated the proportion of unreported cases of leprosy in Brazilian microregions.

Using data collected between 2007 to 2015 from each of the 557 Brazilian microregions, we applied a Bayesian hierarchical model that used the presence of grade 2 leprosy-related physical disabilities as a direct indicator of delayed diagnosis and a proxy for the effectiveness of local leprosy surveillance program. We also analyzed some relevant factors that influence spatial variability in the observed mean incidence rate in the Brazilian microregions, highlighting the importance of socioecono and efforts are warranted to improve leprosy case detection. Our estimates in Brazilian microregions can be used to guide effective interventions, efficient resource allocation, and target actions to mitigate transmission.

Fibrosis progression is the most important prognostic factor, and insulin resistance is one of the main mechanisms associated with fibrosis progression in patients with nonalcoholic fatty liver disease (NAFLD). We evaluate the association between baseline insulin resistance and future fibrosis progression in patients with NAFLD without diabetes.

This retrospective longitudinal study with 8-year follow-up period included 32,606 (men, 83%) participants aged >20 years (average age, 38.0 years) without diabetes at baseline who completed at least two comprehensive health checkups from January 1, 2010 to December 31, 2018. U0126 NAFLD was diagnosed based on ultrasonography. The homeostasis model assessment of insulin resistance (HOMA-IR) was used to evaluate baseline insulin resistance. Fibrosis progression was assessed using the aspartate aminotransferase to platelet ratio index (APRI). The advanced liver fibrosis with an APRI value above the intermediate fibrosis probability (≥0.5) developed in a total of 2,897 d that the degree of baseline insulin resistance, assessed by HOMA-IR values, was positively associated with future fibrosis progression in patients with NAFLD without diabetes.Chromoanagenesis is a genomic catastrophe that results in chromosomal shattering and reassembly. These extreme single chromosome events were first identified in cancer, and have since been observed in other systems, but have so far only been formally documented in plants in the context of haploid induction crosses. The frequency, origins, consequences, and evolutionary impact of such major chromosomal remodeling in other situations remain obscure. Here, we demonstrate the occurrence of chromoanagenesis in poplar (Populus sp.) trees produced from gamma-irradiated pollen. Specifically, in this population of siblings carrying indel mutations, two individuals exhibited highly frequent copy number variation (CNV) clustered on a single chromosome, one of the hallmarks of chromoanagenesis. Using short-read sequencing, we confirmed the presence of clustered segmental rearrangement. Independently, we identified and validated novel DNA junctions and confirmed that they were clustered and corresponded to these rearrangements. Our reconstruction of the novel sequences suggests that the chromosomal segments have reorganized randomly to produce a novel rearranged chromosome but that two different mechanisms might be at play. Our results indicate that gamma irradiation can trigger chromoanagenesis, suggesting that this may also occur when natural or induced mutagens cause DNA breaks. We further demonstrate that such events can be tolerated in poplar, and even replicated clonally, providing an attractive system for more in-depth investigations of their consequences.A salient feature of mammalian sleep is the alternation between rapid eye movement (REM) and non-REM (NREM) sleep. However, how these two sleep stages influence each other and thereby regulate the timing of REM sleep episodes is still largely unresolved. Here, we developed a statistical model that specifies the relationship between REM and subsequent NREM sleep to quantify how REM sleep affects the following NREM sleep duration and its electrophysiological features in mice. We show that a lognormal mixture model well describes how the preceding REM sleep duration influences the amount of NREM sleep till the next REM sleep episode. The model supports the existence of two different types of sleep cycles Short cycles form closely interspaced sequences of REM sleep episodes, whereas during long cycles, REM sleep is first followed by an interval of NREM sleep during which transitions to REM sleep are extremely unlikely. This refractory period is characterized by low power in the theta and sigma range of the electroencephalogram (EEG), low spindle rate and frequent microarousals, and its duration proportionally increases with the preceding REM sleep duration. Using our model, we estimated the propensity for REM sleep at the transition from NREM to REM sleep and found that entering REM sleep with higher propensity resulted in longer REM sleep episodes with reduced EEG power. Compared with the light phase, the buildup of REM sleep propensity was slower during the dark phase. Our data-driven modeling approach uncovered basic principles underlying the timing and duration of REM sleep episodes in mice and provides a flexible framework to describe the ultradian regulation of REM sleep in health and disease.

Scrub typhus (ST) and murine typhus (MT) are common but poorly understood causes of fever in Laos. We examined the spatial and temporal distribution of ST and MT, with the intent of informing interventions to prevent and control both diseases.

This study included samples submitted from 2003 to 2017 to Mahosot Hospital, Vientiane, for ST and MT investigation. Serum samples were tested using IgM rapid diagnostic tests. Patient demographic data along with meteorological and environmental data from Laos were analysed. Approximately 17% of patients were positive for either ST (1,337/8,150 patients tested) or MT (1,283/7,552 patients tested). While both diseases occurred in inhabitants from Vientiane Capital, from the univariable analysis MT was positively and ST negatively associated with residence in Vientiane Capital. ST was highly seasonal, with cases two times more likely to occur during the wet season months of July-September compared to the dry season whilst MT peaked in the dry season. Multivariable regression analysis linked ST incidence to fluctuations in relative humidity whereas MT was linked to variation in temperature. Patients with ST infection were more likely to come from villages with higher levels of surface flooding and vegetation in the 16 days leading up to diagnosis.

The data suggest that as cities expand, high risk areas for MT will also expand. With global heating and risks of attendant higher precipitation, these data suggest that the incidence and spatial distribution of both MT and ST will increase.

The data suggest that as cities expand, high risk areas for MT will also expand. With global heating and risks of attendant higher precipitation, these data suggest that the incidence and spatial distribution of both MT and ST will increase.

Suicidal ideation (SI) among pregnant women is a major public health concern worldwide and is associated with a higher risk of completed suicide. However, there are limited studies that determined the prevalence and the potential determinants of suicidal ideation in Sub-Saharan Africa, including Ethiopia. Therefore, this study aimed to explore the prevalence of suicidal ideation and associated factors among pregnant women attending antenatal care in Jimma, Ethiopia.

An institutional-based cross-sectional study was conducted among 423 pregnant women attending Jimma medical center in Southwest, Ethiopia. A systematic random sampling technique was used to select the study participants. Suicidal ideation assessed using the Suicidality Module of the World Mental Health survey initiative version of the World Health Organization Composite International Diagnostic Interview (CIDI). Other tools used are EPDS, Abuse Assessment Scale (AAS), DASS -21, PSS, Maternity Social Support Scale (MSSS), and Pittsburgh Sleep QSI are needed.

The prevalence of SI among pregnant women was found to be huge. Lack of cohabiting partners, previous history of abortion, depression, anxiety, intimate partner violence, poor sleep quality, and stress were variables that are independent predictors of suicidal ideation. Screening and interventions of antenatal SI are needed.The newly emerged and rapidly spreading SARS-CoV-2 causes coronavirus disease 2019 (COVID-19). To facilitate a deeper understanding of the viral biology we developed a capture sequencing methodology to generate SARS-CoV-2 genomic and transcriptome sequences from infected patients. We utilized an oligonucleotide probe-set representing the full-length genome to obtain both genomic and transcriptome (subgenomic open reading frames [ORFs]) sequences from 45 SARS-CoV-2 clinical samples with varying viral titers. For samples with higher viral loads (cycle threshold value under 33, based on the CDC qPCR assay) complete genomes were generated. Analysis of junction reads revealed regions of differential transcriptional activity among samples. Mixed allelic frequencies along the 20kb ORF1ab gene in one sample, suggested the presence of a defective viral RNA species subpopulation maintained in mixture with functional RNA in one sample. The associated workflow is straightforward, and hybridization-based capture offers an effective and scalable approach for sequencing SARS-CoV-2 from patient samples.

Prediction models should be externally validated to assess their performance before implementation. Several prediction models for coronavirus disease-19 (COVID-19) have been published. This observational cohort study aimed to validate published models of severity for hospitalized patients with COVID-19 using clinical and laboratory predictors.

Prediction models fitting relevant inclusion criteria were chosen for validation. The outcome was either mortality or a composite outcome of mortality and ICU admission (severe disease). 1295 patients admitted with symptoms of COVID-19 at Kings Cross Hospital (KCH) in London, United Kingdom, and 307 patients at Oslo University Hospital (OUH) in Oslo, Norway were included. The performance of the models was assessed in terms of discrimination and calibration.

We identified two models for prediction of mortality (referred to as Xie and Zhang1) and two models for prediction of severe disease (Allenbach and Zhang2). The performance of the models was variable. For prediction of mortality Xie had good discrimination at OUH with an area under the receiver-operating characteristic (AUROC) 0.87 [95% confidence interval (CI) 0.79-0.95] and acceptable discrimination at KCH, AUROC 0.79 [0.76-0.82]. In prediction of severe disease, Allenbach had acceptable discrimination (OUH AUROC 0.81 [0.74-0.88] and KCH AUROC 0.72 [0.68-0.75]). The Zhang models had moderate to poor discrimination. Initial calibration was poor for all models but improved with recalibration.

The performance of the four prediction models was variable. The Xie model had the best discrimination for mortality, while the Allenbach model had acceptable results for prediction of severe disease.

The performance of the four prediction models was variable. The Xie model had the best discrimination for mortality, while the Allenbach model had acceptable results for prediction of severe disease.