RESUMEN
COVID-19 has been widely explored in relation to its symptoms, outcomes, and risk profiles for the severe form of the disease. Our aim was to identify clusters of pregnant and postpartum women with severe acute respiratory syndrome (SARS) due to COVID-19 by analyzing data available in the Influenza Epidemiological Surveillance Information System of Brazil (SIVEP-Gripe) between March 2020 and August 2021. The study's population comprised 16,409 women aged between 10 and 49 years old. Multiple correspondence analyses were performed to summarize information from 28 variables related to symptoms, comorbidities, and hospital characteristics into a set of continuous principal components (PCs). The population was segmented into three clusters based on an agglomerative hierarchical cluster analysis applied to the first 10 PCs. Cluster 1 had a higher frequency of younger women without comorbidities and with flu-like symptoms; cluster 2 was represented by women who reported mainly ageusia and anosmia; cluster 3 grouped older women with the highest frequencies of comorbidities and poor outcomes. The defined clusters revealed different levels of disease severity, which can contribute to the initial risk assessment of the patient, assisting the referral of these women to health services with an appropriate level of complexity.
Asunto(s)
COVID-19 , Gripe Humana , Femenino , Humanos , Embarazo , Anciano , Niño , Adolescente , Adulto Joven , Adulto , Persona de Mediana Edad , COVID-19/epidemiología , SARS-CoV-2 , Mujeres Embarazadas , Aprendizaje Automático no Supervisado , Gripe Humana/epidemiologíaRESUMEN
Amyotrophic lateral sclerosis (ALS) is a multi-system neurodegenerative disease that affects both upper and lower motor neurons, resulting from a combination of genetic, environmental, and lifestyle factors. Usually, the association between single-nucleotide polymorphisms (SNPs) and this disease is tested individually, which leads to the testing of multiple hypotheses. In addition, this classical approach does not support the detection of interaction-dependent SNPs. We applied a two-step procedure to select SNPs and pairwise interactions associated with ALS. SNP data from 276 ALS patients and 268 controls were analyzed by a two-step group LASSO in 2000 iterations. In the first step, we fitted a group LASSO model to a bootstrap sample and a random subset of predictors (25%) from the original data set aiming to screen for important SNPs and, in the second step, we fitted a hierarchical group LASSO model to evaluate pairwise interactions. An in silico analysis was performed on a set of variables, which were prioritized according to their bootstrap selection frequency. We identified seven SNPs (rs16984239, rs10459680, rs1436918, rs1037666, rs4552942, rs10773543, and rs2241493) and two pairwise interactions (rs16984239:rs2118657 and rs16984239:rs3172469) potentially involved in nervous system conservation and function. These results may contribute to the understanding of ALS pathogenesis, its diagnosis, and therapeutic strategy improvement.
RESUMEN
Megalodoras uranoscopus (Eigenmann & Eigenmann) (Siluriformes, Doradidae) (the giant-talking catfish or the giant-raphael catfish), from the Peruvian Amazon, hosts a new species of Cosmetocleithrum described herein as Cosmetocleithrum falsunilatum sp. n. The male copulatory organ of the new species closely resembles that of Unilatus spp. - with multiple tight loops and non-articulated accessory piece - which reveals its morphological uniqueness among members of Cosmetocleithrum. A phylogenetic analysis using 28S rDNA of available sequences suggests that Cosmetocleithrum is composed by two basal clades, one of them composed by sequences of the new species and C. trachydorasi.