Modeling of Acoustic Emission Failure Mechanism Data from a Unidirectional Fiberglass/Epoxy Tensile Test Specimen

The purpose of this work was to model the acoustic emission (AE) flaw growth data that resulted from the tensile test of a unidirectional fiberglass/epoxy specimen. The data collected and stored during the test were the six standard AE quantification parameters for each event. A classification neural network was used to sort the data into five failure mechanism clusters. The resulting frequency histograms of the sorted data were then mathematically modeled herein using the three types of Johnson distributions: bounded, lognormal, and unbounded. These provided a reasonably good fit for all six AE parameter distributions for each of the five failure mechanisms

Development of a Cx46 Targeting Strategy for Cancer Stem Cells

Gap-junction-mediated cell-cell communication enables tumor cells to synchronize complex processes. We previously found that glioblastoma cancer stem cells (CSCs) express higher levels of the gap junction protein Cx46 compared to non-stem tumor cells (non-CSCs) and that this was necessary and sufficient for CSC maintenance. To understand the mechanism underlying this requirement, we use point mutants to disrupt specific functions of Cx46 and find that Cx46-mediated gap-junction coupling is critical for CSCs. To develop a Cx46 targeting strategy, we screen a clinically relevant small molecule library and identify clofazimine as an inhibitor of Cx46-specific cell-cell communication. Clofazimine attenuates proliferation, self-renewal, and tumor growth and synergizes with temozolomide to induce apoptosis. Although clofazimine does not cross the blood-brain barrier, the combination of clofazimine derivatives optimized for brain penetrance with standard-of-care therapies may target glioblastoma CSCs. Furthermore, these results demonstrate the importance of targeting cell-cell communication as an anti-cancer therapy

Meeting the stakeholder needs and sustaining business through sustainability risk management practices: A case study of Malaysian environmentally sensitive companies

Sustainability issues such as climate change, carbon emissions, and energy consumption have become increasingly important issues among business organisations, academics and policy makers. Considering this complexity, stakeholders currently demanding companies to have a sound risk management that are aligned to their interest. Sustaining business requires a strong foundational on the economic, environmental and social aspects to address risks and capture value. Sustainability risk management (SRM) is a process that systematically integrates environmental, social, and economic aspects to address emerging risks and other non-quantifiable risk for company survival. This study aims to examine the impact of SRM practices on the company survival among the environmentally sensitive companies in Malaysia. A case study was carried out to examine the SRM implementation among the environmentally sensitive companies. The finding shows that leadership and compliance are considered as important factors in implementing SRM programme. Other factors such as sound risk culture, adequate risk management tools, and effective business continuity planning are crucial to support SRM implementation. Overall findings revealthat the companies are at the early stage implementing SRM programme and denote there is much room for improvement in the risk management process to create long-term value creation for the stakeholders. This study provides empirical evidence on the significance of SRM factors to the company survival. Given the huge environmental and social costs arising from sustainability issues, companies should intensify their effort to fully implement SRM programme across the organisation to sustain longer

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 hospitalization2–4 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

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

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

Exome-wide association study to identify rare variants influencing COVID-19 outcomes : Results from the Host Genetics Initiative

Publisher Copyright: Copyright: © 2022 Butler-Laporte et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.Host genetics is a key determinant of COVID-19 outcomes. Previously, the COVID-19 Host Genetics Initiative genome-wide association study used common variants to identify multiple loci associated with COVID-19 outcomes. However, variants with the largest impact on COVID-19 outcomes are expected to be rare in the population. Hence, studying rare variants may provide additional insights into disease susceptibility and pathogenesis, thereby informing therapeutics development. Here, we combined whole-exome and whole-genome sequencing from 21 cohorts across 12 countries and performed rare variant exome-wide burden analyses for COVID-19 outcomes. In an analysis of 5,085 severe disease cases and 571,737 controls, we observed that carrying a rare deleterious variant in the SARS-CoV-2 sensor toll-like receptor TLR7 (on chromosome X) was associated with a 5.3-fold increase in severe disease (95% CI: 2.75–10.05, p = 5.41x10-7). This association was consistent across sexes. These results further support TLR7 as a genetic determinant of severe disease and suggest that larger studies on rare variants influencing COVID-19 outcomes could provide additional insights.Peer reviewe