25 research outputs found

    Use of radiographic and histologic scores to evaluate cats with idiopathic megacolon grouped based on the duration of their clinical signs

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    Since the duration of clinical signs could be used to identify cases of chronic constipation, in addition, prolonged duration is often associated with irreversible changes. Thus, the main objective of this study was to determine whether the duration of clinical signs of idiopathic megacolon in cats affected their diagnosis and prognosis after treatment. Medical records of cats that either had confirmed megacolon for an unknown cause (cat patients) or with normal bowels (control cats) were reviewed. Cat patients were grouped based on the duration of their clinical signs (constipation/obstipation) to cats <6 months and ≥6 months. For all feline patients, abdominal radiographs (for colonic indexes) and resected colon specimens (for histology) were assessed vs. control cats. Treatment applied to cat patients was also evaluated. Cat patients were older (p = 0.0138) and had a higher maximum colon diameter (MCD; mean 41.25 vs. 21.67 mm, p < 0.0001) and MCD/L5L ratio (1.77 vs. 0.98, p < 0.0001) than controls. Compared to cats with <6 months, cats ≥6 months showed a higher MCD (43.78 vs. 37.12 mm, p < 0.0001) and MCD/L5L ratio (1.98 vs. 1.67, p < 0.0001). Histologically, increased thickness of the smooth muscularis mucosa (54.1 vs. 22.33 μm, p < 0.05), and inner circular (743.65 vs. 482.67 μm, p < 0.05) and outer longitudinal (570.68 vs. 330.33 μm, p < 0.05) smooth muscular layers of the muscularis externa was noted only in cat patients with ≥6 months compared to controls. Similarly, fewer ganglion cells (0.93 vs. 2.87, p < 0.005) and more necrotized myocytes (2.25 vs. 0.07, p < 0.005) were observed in cats with ≥6 months. In contrast to <6 months, the majority of cats (94.4%) with ≥6 months duration did not show any response to medical treatment and therefore underwent surgery with favorable results. In conclusion, this study suggests that the duration of clinical signs should be considered in conjunction with maximal colon scores to evaluate cats for idiopathic megacolon and determine the level of treatment. Functional abnormalities of the colonic smooth muscles may be a possible cause of idiopathic megacolon in cats

    Consensus Middle East and North Africa Registry on Inborn Errors of Immunity

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    Background: Inborn errors of immunity (IEIs) are a heterogeneous group of genetic defects of immunity, which cause high rates of morbidity and mortality mainly among children due to infectious and non-infectious complications. The IEI burden has been critically underestimated in countries from middle- and low-income regions and the majority of patients with IEI in these regions lack a molecular diagnosis. Methods: We analyzed the clinical, immunologic, and genetic data of IEI patients from 22 countries in the Middle East and North Africa (MENA) region. The data was collected from national registries and diverse databases such as the Asian Pacific Society for Immunodeficiencies (APSID) registry, African Society for Immunodeficiencies (ASID) registry, Jeffrey Modell Foundation (JMF) registry, J Project centers, and International Consortium on Immune Deficiency (ICID) centers. Results: We identified 17,120 patients with IEI, among which females represented 39.4%. Parental consanguinity was present in 60.5% of cases and 27.3% of the patients were from families with a confirmed previous family history of IEI. The median age of patients at the onset of disease was 36 months and the median delay in diagnosis was 41 months. The rate of registered IEI patients ranges between 0.02 and 7.58 per 100,000 population, and the lowest rates were in countries with the highest rates of disability-adjusted life years (DALY) and death rates for children. Predominantly antibody deficiencies were the most frequent IEI entities diagnosed in 41.2% of the cohort. Among 5871 patients genetically evaluated, the diagnostic yield was 83% with the majority (65.2%) having autosomal recessive defects. The mortality rate was the highest in patients with non-syndromic combined immunodeficiency (51.7%, median age: 3.5 years) and particularly in patients with mutations in specific genes associated with this phenotype (RFXANK, RAG1, and IL2RG). Conclusions: This comprehensive registry highlights the importance of a detailed investigation of IEI patients in the MENA region. The high yield of genetic diagnosis of IEI in this region has important implications for prevention, prognosis, treatment, and resource allocation

    SARS-CoV-2 susceptibility and COVID-19 disease severity are associated with genetic variants affecting gene expression in a variety of tissues

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    Variability in SARS-CoV-2 susceptibility and COVID-19 disease severity between individuals is partly due to genetic factors. Here, we identify 4 genomic loci with suggestive associations for SARS-CoV-2 susceptibility and 19 for COVID-19 disease severity. Four of these 23 loci likely have an ethnicity-specific component. Genome-wide association study (GWAS) signals in 11 loci colocalize with expression quantitative trait loci (eQTLs) associated with the expression of 20 genes in 62 tissues/cell types (range: 1:43 tissues/gene), including lung, brain, heart, muscle, and skin as well as the digestive system and immune system. We perform genetic fine mapping to compute 99% credible SNP sets, which identify 10 GWAS loci that have eight or fewer SNPs in the credible set, including three loci with one single likely causal SNP. Our study suggests that the diverse symptoms and disease severity of COVID-19 observed between individuals is associated with variants across the genome, affecting gene expression levels in a wide variety of tissue types

    Whole-genome sequencing reveals host factors underlying critical COVID-19

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    Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2–4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes—including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)—in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease

    A first update on mapping the human genetic architecture of COVID-19

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    A Cloud-based Malware Detection Framework

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    Malwares are increasing rapidly. The nature of distribution and effects of malwares attacking several applications requires a real-time response. Therefore, a high performance detection platform is required. In this paper, Hadoop is utilized to perform static binary search and detection for malwares and viruses in portable executable files deployed mainly on the cloud. The paper presents an approach used to map the portable executable files to Hadoop compatible files. The Boyer–Moore-Horspool Search algorithm is modified to benefit from the distribution of Hadoop. The performance of the proposed model is evaluated using a standard virus database and the system is found to outperform similar platforms
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