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Multidrug resistant organisms are a serious threat to human health1,2. Fast, accurate antibiotic susceptibility testing (AST) is a critical need in addressing escalating antibiotic resistance, since delays in identifying multidrug resistant organisms increase mortality3,4 and use of broad-spectrum antibiotics, further selecting for resistant organisms. Yet current growth-based AST assays, such as broth microdilution5, require several days before informing key clinical decisions. Rapid AST would transform the care of patients with infection while ensuring that our antibiotic arsenal is deployed as efficiently as possible. Growth-based assays are fundamentally constrained in speed by doubling time of the pathogen, and genotypic assays are limited by the ever-growing diversity and complexity of bacterial antibiotic resistance mechanisms. Here we describe a rapid assay for combined genotypic and phenotypic AST through RNA detection, GoPhAST-R, that classifies strains with 94–99% accuracy by coupling machine learning analysis of early antibiotic-induced transcriptional changes with simultaneous detection of key genetic resistance determinants to increase accuracy of resistance detection, facilitate molecular epidemiology and enable early detection of emerging resistance mechanisms. This two-pronged approach provides phenotypic AST 24–36 h faster than standard workflows, with

ObjectiveTo determine the association between ruptured saccular aneurysms and aspirin use/aspirin dose.MethodsFour thousand seven hundred one patients who were diagnosed at the Massachusetts General Hospital and Brigham and Women's Hospital between 1990 and 2016 with 6,411 unruptured and ruptured saccular intracranial aneurysms were evaluated. Univariable and multivariable logistic regression analyses were performed to determine the association between aneurysmal subarachnoid hemorrhage and aspirin use, including aspirin dose. Inverse probability weighting using propensity scores was used to adjust for potential differences in baseline characteristics between cases and controls. Additional analyses were performed to examine the association of aspirin use and rerupture before treatment.ResultsIn multivariate analysis with propensity score weighting, aspirin use (odds ratio [OR] 0.60, 95% confidence interval [CI] 0.45–0.80) was significantly associated with decreased risk of ruptured intracranial aneurysms. There was a significant inverse dose-response relationship between aspirin dose and aneurysmal subarachnoid hemorrhage (OR 0.65, 95% CI 0.53–0.81). In contrast, there was a significant association between aspirin use and increased risk of rerupture before treatment (OR 8.15, 95% CI 2.22–30.0).ConclusionsIn this large case-control study, aspirin therapy at diagnosis was associated with a significantly decreased risk of subarachnoid hemorrhage, with an inverse dose-response relationship among aspirin users. However, once rupture has occurred, aspirin is associated with an increased risk of rerupture before treatment.

Although RNA-seq is a powerful tool, the considerable time and cost associated with library construction has limited its utilization for various applications. RNAtag-Seq, an approach to generate multiple RNA-seq libraries in a single reaction, lowers time and cost per sample, and it produces data on prokaryotic and eukaryotic samples that are comparable to those generated by traditional strand-specific RNA-seq approaches.