Finding Our Way through Phenotypes

Despite a large and multifaceted effort to understand the vast landscape of phenotypic data, their current form inhibits productive data analysis. The lack of a community-wide, consensus-based, human- and machine-interpretable language for describing phenotypes and their genomic and environmental contexts is perhaps the most pressing scientific bottleneck to integration across many key fields in biology, including genomics, systems biology, development, medicine, evolution, ecology, and systematics. Here we survey the current phenomics landscape, including data resources and handling, and the progress that has been made to accurately capture relevant data descriptions for phenotypes. We present an example of the kind of integration across domains that computable phenotypes would enable, and we call upon the broader biology community, publishers, and relevant funding agencies to support efforts to surmount today's data barriers and facilitate analytical reproducibility

Early correlates of visual awareness following orientation and colour rivalry

Binocular rivalry occurs when dissimilar images are presented to corresponding retinal regions of the two eyes: visibility alternates irregularly between the two images, interspersed by brief transitions when parts of both may be visible. We measured event-related potentials (ERPs) following binocular rivalry by changing the stimulus viewed by one eye to be identical to that in the other eye, eliciting binocular fusion. Because of the rivalry, observers either saw the change, when it happened to the visible stimulus, or did not see the change, when it happened to the invisible stimulus. The earliest ERP differences between visible and invisible changes occurred after about 100 ms (P1) when the rivalry was between stimuli differing in orientation, and after about 200 ms (N1) when the rivalry was between stimuli differing in colour. These differences originated from ventro-lateral temporal and prefrontal areas. We conclude that the rivalling stimulus property influences the timing of modulation of correlates of visual awareness in a property-independent cortical network. (C) 2008 Elsevier Ltd. All rights reserved

The association between macrovascular complications and intensive care admission, invasive mechanical ventilation, and mortality in people with diabetes hospitalized for coronavirus disease-2019 (COVID-19)

International audienceAbstract Background It is not clear whether pre-existing macrovascular complications (ischemic heart disease, stroke or peripheral artery disease) are associated with health outcomes in people with diabetes mellitus hospitalized for COVID-19. Methods We conducted cohort studies of adults with pre-existing diabetes hospitalized for COVID-19 infection in the UK, France, and Spain during the early phase of the pandemic (between March 2020—October 2020). Logistic regression models adjusted for demographic factors and other comorbidities were used to determine associations between previous macrovascular disease and relevant clinical outcomes: mortality, intensive care unit (ICU) admission and use of invasive mechanical ventilation (IMV) during the hospitalization. Output from individual logistic regression models for each cohort was combined in a meta-analysis. Results Complete data were available for 4,106 (60.4%) individuals. Of these, 1,652 (40.2%) had any prior macrovascular disease of whom 28.5% of patients died. Mortality was higher for people with compared to those without previous macrovascular disease (37.7% vs 22.4%). The combined crude odds ratio (OR) for previous macrovascular disease and mortality for all four cohorts was 2.12 (95% CI 1.83–2.45 with an I 2 of 60%, reduced after adjustments for age, sex, type of diabetes, hypertension, microvascular disease, ethnicity, and BMI to adjusted OR 1.53 [95% CI 1.29–1.81]) for the three cohorts. Further analysis revealed that ischemic heart disease and cerebrovascular disease were the main contributors of adverse outcomes. However, proportions of people admitted to ICU (adjOR 0.48 [95% CI 0.31–0.75], I 2 60%) and the use of IMV during hospitalization (adjOR 0.52 [95% CI 0.40–0.68], I 2 37%) were significantly lower for people with previous macrovascular disease. Conclusions This large multinational study of people with diabetes mellitus hospitalized for COVID-19 demonstrates that previous macrovascular disease is associated with higher mortality and lower proportions admitted to ICU and treated with IMV during hospitalization suggesting selective admission criteria. Our findings highlight the importance correctly assess the prognosis and intensive monitoring in this high-risk group of patients and emphasize the need to design specific public health programs aimed to prevent SARS-CoV-2 infection in this subgroup