Clonal chromosomal mosaicism and loss of chromosome Y in elderly men increase vulnerability for SARS-CoV-2

The pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2, COVID-19) had an estimated overall case fatality ratio of 1.38% (pre-vaccination), being 53% higher in males and increasing exponentially with age. Among 9578 individuals diagnosed with COVID-19 in the SCOURGE study, we found 133 cases (1.42%) with detectable clonal mosaicism for chromosome alterations (mCA) and 226 males (5.08%) with acquired loss of chromosome Y (LOY). Individuals with clonal mosaic events (mCA and/or LOY) showed a 54% increase in the risk of COVID-19 lethality. LOY is associated with transcriptomic biomarkers of immune dysfunction, pro-coagulation activity and cardiovascular risk. Interferon-induced genes involved in the initial immune response to SARS-CoV-2 are also down-regulated in LOY. Thus, mCA and LOY underlie at least part of the sex-biased severity and mortality of COVID-19 in aging patients. Given its potential therapeutic and prognostic relevance, evaluation of clonal mosaicism should be implemented as biomarker of COVID-19 severity in elderly people. Among 9578 individuals diagnosed with COVID-19 in the SCOURGE study, individuals with clonal mosaic events (clonal mosaicism for chromosome alterations and/or loss of chromosome Y) showed an increased risk of COVID-19 lethality

Alternaria toxins in Argentinean wheat, bran, and flour

Alternaria species have been reported to infect a wide variety of vegetables, fruits, and cereal crops. Wheat is one of the most consumed cereal worldwide. A sensitive HPLC-DAD methodology was applied to quantify alternariol (AOH), alternariol methyl ether (AME) and tenuazonic acid (TeA) in 65 samples of whole wheat, bran, and flour. The extraction methodology allowed extracting the three toxins simultaneously. Limits of detection in wheat were 3.4, 4.5, and 0.5 µg kg −1 for AOH, AME and TeA, respectively. For bran, these data were 3.1, 4.5, and 12 µg kg −1 and for flour 50, 70, and 14 µg kg −1 , respectively. The studied recoveries were higher than 70% and RSD was below 10%. Wheat and bran samples showed low AOH and AME contamination compared to TeA. The averages levels found for TeA in wheat, bran and flour were 19,190, 16,760, and 7360 µg kg −1 , respectively.Fil: Romero Bernal, Ángela Rocío. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; ArgentinaFil: Reynoso, Cora Marcela. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; ArgentinaFil: García Londoño, Víctor Alonso. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina. Fundación de Investigaciones Científicas Teresa Benedictina de la Cruz; ArgentinaFil: Broggi, Leticia Elvira. Universidad Nacional de Entre Ríos. Facultad de Bromatología; ArgentinaFil: Resnik, Silvia Liliana. Fundación de Investigaciones Científicas Teresa Benedictina de la Cruz; Argentina. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina. Provincia de Buenos Aires. Gobernación. Comisión de Investigaciones Científicas; Argentin

El contexto y su incidencia en la interpretación lectora.

Universidad de San Buenaventura Bogotá La presente investigación busca analizar la incidencia del contexto en las interpretaciones que hacen los estudiantes de un cuento colombiano, a través de un estudio de casos aplicado a estudiantes de grado octavo, divididos en dos grupos diferenciados por el conocimiento o desconocimiento del contexto del cuento. Por último, se presentan las conclusiones de la investigaciónUniversidad de San Buenaventura Bogot

Discovering HIV related information by means of association rules and machine learning

Acquired immunodeficiency syndrome (AIDS) is still one of the main health problems worldwide. It is therefore essential to keep making progress in improving the prognosis and quality of life of affected patients. One way to advance along this pathway is to uncover connections between other disorders associated with HIV/AIDS-so that they can be anticipated and possibly mitigated. We propose to achieve this by using Association Rules (ARs). They allow us to represent the dependencies between a number of diseases and other specific diseases. However, classical techniques systematically generate every AR meeting some minimal conditions on data frequency, hence generating a vast amount of uninteresting ARs, which need to be filtered out. The lack of manually annotated ARs has favored unsupervised filtering, even though they produce limited results. In this paper, we propose a semi-supervised system, able to identify relevant ARs among HIV-related diseases with a minimal amount of annotated training data. Our system has been able to extract a good number of relationships between HIV-related diseases that have been previously detected in the literature but are scattered and are often little known. Furthermore, a number of plausible new relationships have shown up which deserve further investigation by qualified medical experts

New insights into the genetic etiology of Alzheimer’s disease and related dementias

Characterization of the genetic landscape of Alzheimer’s disease (AD) and related dementias (ADD) provides a unique opportunity for a better understanding of the associated pathophysiological processes. We performed a two-stage genome-wide association study totaling 111,326 clinically diagnosed/‘proxy’ AD cases and 677,663 controls. We found 75 risk loci, of which 42 were new at the time of analysis. Pathway enrichment analyses confirmed the involvement of amyloid/tau pathways and highlighted microglia implication. Gene prioritization in the new loci identified 31 genes that were suggestive of new genetically associated processes, including the tumor necrosis factor alpha pathway through the linear ubiquitin chain assembly complex. We also built a new genetic risk score associated with the risk of future AD/dementia or progression from mild cognitive impairment to AD/dementia. The improvement in prediction led to a 1.6- to 1.9-fold increase in AD risk from the lowest to the highest decile, in addition to effects of age and the APOE ε4 allele