A Bayesian Model Based on Local Phenotypic Resistance Data to Inform Empiric Antibiotic Escalation Decisions.

Introduction: Clinicians commonly escalate empiric antibiotic therapy due to poor clinical progress without microbiology guidance. When escalating, they should take account of how resistance to an initial antibiotic affects the probability of resistance to subsequent options. The term "escalation antibiogram" (EA) has been coined to describe this concept.

Epidemiology of Escherichia coli bloodstream infection antimicrobial resistance trends across South West England during the first 2 years of the coronavirus disease 2019 pandemic response.

Objectives: Between 2016 and 2019, the proportion of Escherichia coli bloodstream infection (BSI) with resistance to at least one antibiotic increased nationally. Public health interventions implemented in response to the COVID-19 pandemic changed population contact patterns and healthcare systems, with consequent effects on epidemiological trends of numerous pathogens. We investigated the impact of COVID-19 restrictions on epidemiological trends of E.

Five Inhibitory Receptors Display Distinct Vesicular Distributions in Murine T Cells.

T cells can express multiple inhibitory receptors. Upon induction of T cell exhaustion in response to a persistent antigen, prominently in the anti-tumor immune response, many are expressed simultaneously. Key inhibitory receptors are CTLA-4, PD-1, LAG3, TIM3, and TIGIT, as investigated here.

Five inhibitory receptors display distinct vesicular distributions in T cells.

T cells can express multiple inhibitory receptors. Upon induction of T cell exhaustion in response to persistent antigen, prominently in the anti-tumor immune response, many are expressed simultaneously. Key inhibitory receptors are CTLA-4, PD-1, LAG3, TIM3 and TIGIT, as investigated here.