Caracterização mecânica das argamassas de assentamento para alvenaria estrutural – previsão e modo de ruptura

Este trabalho pretende avaliar o comportamento mecânico das argamassas de assentamento para o uso estrutural, por meio das propriedades de resistência à compressão, tração na flexão e módulo de elasticidade, sob estados de tensões uniaxial e multiaxial. Portanto, estabelecer correlações entre os resultados mecânicos de diferentes traços de argamassas, relações água/cimento e geometria da amostra associada ao modo de ruptura. As principais conclusões obtidas, entre outras, são: existe uma relação potencial entre a resistência a compressão da amostra de geometria cúbica, cilíndrica e a resistência à flexão (amostra de geometria prismática) em função da relação água/cimento; a função linear é a que melhor ajusta os valores médios do módulo de elasticidade em função da resistência à compressão; a envoltória de ruptura da argamassa confinada lateralmente pode ser representada como uma relação linear de Mohr-Coulomb; observou-se, por meio de ensaios de microscopia eletrônica de varredura a existência de fissuras de retração na interface pasta-agregado e poros isolados, devido ao fluxo ascendente de água causado pela exsudação

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

Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2,3,4 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 Network Approach to Developing Immuno-Oncology Combinations in Canada

Immune checkpoint inhibitors have revolutionized care for many cancer indications, with considerable effort now being focused on increasing the rate, depth, and duration of patient response. One strategy is to combine immune strategies (for example, CTLA-4 and PD-1/L1–directed agents) to harness additive or synergistic efficacy while minimizing toxicity. Despite encouraging results with such combinations in multiple tumour types, numerous clinical challenges remain, including a lack of biomarkers that reliably predict outcome, the emergence of therapeutic resistance, and optimal management of immune-related toxicities. Furthermore, the selection of ideal combinations from the myriad of immune, systemic, and locoregional therapies has yet to be determined. A longitudinal network-based approach could offer advantages in addressing those critical questions, including long-term follow-up of patients beyond individual trials