In silico predictive models for toxicology include quantitative structure-activity relationship (QSAR) and physiologically based kinetic (PBK) approaches to predict physico-chemical and ADME properties, toxicological effects and internal exposure. Such models are used to fill data gaps as part of chemical risk assessment. There is a growing need to ensure in silico predictive models for toxicology are available for use and that they are reproducible.
View Article and Find Full Text PDFDysregulated host responses to infection can lead to organ dysfunction and sepsis, causing millions of global deaths each year. To alleviate this burden, improved prognostication and biomarkers of response are urgently needed. We investigated the use of whole-blood transcriptomics for stratification of patients with severe infection by integrating data from 3149 samples from patients with sepsis due to community-acquired pneumonia or fecal peritonitis admitted to intensive care and healthy individuals into a gene expression reference map.
View Article and Find Full Text PDFBackground: Better understanding of patient and family member experiences of delirium and related distress during critical care is required to inform the development of targeted nonpharmacologic interventions.
Objective: To examine and synthesize qualitative data on patient and family member delirium experiences and relieving factors in the Intensive Care Unit (ICU).
Design: We conducted a systematic review and qualitative meta-synthesis.