Matrix Inversion and Subset Selection (MISS): A pipeline for mapping of diverse cell types across the murine brain.

The advent of increasingly sophisticated imaging platforms has allowed for the visualization of the murine nervous system at single-cell resolution. However, current experimental approaches have not yet produced whole-brain maps of a comprehensive set of neuronal and nonneuronal types that approaches the cellular diversity of the mammalian cortex. Here, we aim to fill in this gap in knowledge with an open-source computational pipeline, Matrix Inversion and Subset Selection (MISS), that can infer quantitatively validated distributions of diverse collections of neural cell types at 200-µm resolution using a combination of single-cell RNA sequencing (RNAseq) and in situ hybridization datasets. We rigorously demonstrate the accuracy of MISS against literature expectations. Importantly, we show that gene subset selection, a procedure by which we filter out low-information genes prior to performing deconvolution, is a critical preprocessing step that distinguishes MISS from its predecessors and facilitates the production of cell-type maps with significantly higher accuracy. We also show that MISS is generalizable by generating high-quality cell-type maps from a second independently curated single-cell RNAseq dataset. Together, our results illustrate the viability of computational approaches for determining the spatial distributions of a wide variety of cell types from genetic data alone.

Urinary Tract Infections in Hospitalized Ischemic Stroke Patients: Source and Impact on Outcome.

BACKGROUND:  Urinary tract infections (UTIs) in ischemic stroke patients are a common occurrence and the frequent focus of quality improvement initiatives. However, many UTIs are community-acquired and the impact of such infections on patient outcomes remains controversial. METHODS:  We conducted a retrospective analysis of our Stroke Center Database and electronic medical records to determine the incidence of both community-acquired UTI (CA-UTI) and hospital-acquired UTI (HA-UTI) in hospitalized ischemic stroke patients. We assessed risk factors for UTI, as well as clinical outcome, the length of stay (LOS), and hospital charges. RESULTS:  In our study sample of 395 patients, UTIs were found in 11.7% and the majority of these (65%) were found on admission. Patients admitted from another hospital were more likely to be diagnosed with a UTI of any type compared to those arriving from home (odds ratio (OR) 2.42 95%, confidence interval (CI) 1.18, 4.95) and were considerably more likely to have an HA-UTI than a CA-UTI (OR 12.06 95% CI 2.14, 95.32). Those with a Foley catheter were also more likely to have a UTI (OR 2.65 95% CI 1.41, 4.98). In the multivariable analysis, we did not find a statistically significant relationship between any UTI or a specific UTI subtype and discharge modified Rankin Score (mRS), LOS, or hospital charges. Admission stroke severity remained associated with higher odds of discharge in poor condition (adjusted odds ratio (aOR) 6.23 95% CI2.33, 16.62), an extended LOS (6.84 vs 5.07, p = 0.006), and higher hospital charges ($18,305 vs $12,162, p = 0.001).  Conclusions: Urinary tract infections remain a common occurrence in stroke patients. However, the majority of UTIs are present on admission and may have little impact on discharge clinical condition, LOS, or hospital charges. These results may have implications for quality improvement (QI) initiatives that focus on the prevention and treatment of hospital-acquired UTIs.