Design Principles for Signal Detection in Modern Job Application Systems: Identifying Fabricated Qualifications

Hiring a new employee is traditionally thought to be an uncertain investment. This uncertainty is lessened by the presence of signals that indicate job fitness. Ideally, job applicants objectively signal their qualifications, and those signals are correctly assessed by the hiring team. In reality, signal manipulation is pervasive in the hiring process, mitigating the reliability of signals used to make hiring decisions. To combat these inefficiencies, we propose and evaluate SIGHT, a theoretical class of systems affording more robust signal evaluation during the job application process. A prototypical implementation of the SIGHT framework was evaluated using a mock-interview paradigm. Results provide initial evidence that SIGHT systems can elicit and capture qualification signals beyond what can be traditionally obtained from a typical application and that SIGHT systems can assess signals more effectively than unaided decision-making. SIGHT principles may extend to domains such as audit and security interviews

V-SVA: an R Shiny application for detecting and annotating hidden sources of variation in single-cell RNA-seq data.

SUMMARY: Single-cell RNA-sequencing (scRNA-seq) technology enables studying gene expression programs from individual cells. However, these data are subject to diverse sources of variation, including \u27unwanted\u27 variation that needs to be removed in downstream analyses (e.g. batch effects) and \u27wanted\u27 or biological sources of variation (e.g. variation associated with a cell type) that needs to be precisely described. Surrogate variable analysis (SVA)-based algorithms, are commonly used for batch correction and more recently for studying \u27wanted\u27 variation in scRNA-seq data. However, interpreting whether these variables are biologically meaningful or stemming from technical reasons remains a challenge. To facilitate the interpretation of surrogate variables detected by algorithms including IA-SVA, SVA or ZINB-WaVE, we developed an R Shiny application [Visual Surrogate Variable Analysis (V-SVA)] that provides a web-browser interface for the identification and annotation of hidden sources of variation in scRNA-seq data. This interactive framework includes tools for discovery of genes associated with detected sources of variation, gene annotation using publicly available databases and gene sets, and data visualization using dimension reduction methods. AVAILABILITY AND IMPLEMENTATION: The V-SVA Shiny application is publicly hosted at https://vsva.jax.org/ and the source code is freely available at https://github.com/nlawlor/V-SVA. CONTACT: [email protected] or [email protected]. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online

Emergency department visits and hospitalizations by tube-fed nursing home residents with varying degrees of cognitive impairment: a national study

BACKGROUND: Numerous studies indicate that the use of feeding tubes (FT) in persons with advanced cognitive impairment (CI) does not improve clinical outcomes or survival, and results in higher rates of hospitalization and emergency department (ED) visits. It is not clear, however, whether such risk varies by resident level of CI and whether these ED visits and hospitalizations are potentially preventable. The objective of this study was to determine the rates of ED visits, hospitalizations and potentially preventable ambulatory care sensitive (ACS) ED visits and ACS hospitalizations for long-stay NH residents with FTs at differing levels of CI. METHODS: We linked Centers for Medicare and Medicaid Services inpatient & outpatient administrative claims and beneficiary eligibility data with Minimum Data Set (MDS) resident assessment data for nursing home residents with feeding tubes in a 5% random sample of Medicare beneficiaries residing in US nursing facilities in 2006 (n = 3479). Severity of CI was measured using the Cognitive Performance Scale (CPS) and categorized into 4 groups: None/Mild (CPS = 0-1, MMSE = 22-25), Moderate (CPS = 2-3, MMSE = 15-19), Severe (CPS = 4-5, MMSE = 5-7) and Very Severe (CPS = 6, MMSE = 0-4). ED visits, hospitalizations, ACS ED visits and ACS hospitalizations were ascertained from inpatient and outpatient administrative claims. We estimated the risk ratio of each outcome by CI level using over-dispersed Poisson models accounting for potential confounding factors. RESULTS: Twenty-nine percent of our cohort was considered “comatose” and “without any discernible consciousness”, suggesting that over 20,000 NH residents in the US with feeding tubes are non-interactive. Approximately 25% of NH residents with FTs required an ED visit or hospitalization, with 44% of hospitalizations and 24% of ED visits being potentially preventable or for an ACS condition. Severity of CI had a significant effect on rates of ACS ED visits, but little effect on ACS hospitalizations. CONCLUSIONS: ED visits and hospitalizations are common in cognitively impaired tube-fed nursing home residents and a substantial proportion of ED visits and hospitalizations are potentially preventable due to ACS conditions

Reconstituting ring-rafts in bud-mimicking topography of model membranes.

During vesicular trafficking and release of enveloped viruses, the budding and fission processes dynamically remodel the donor cell membrane in a protein- or a lipid-mediated manner. In all cases, in addition to the generation or relief of the curvature stress, the buds recruit specific lipids and proteins from the donor membrane through restricted diffusion for the development of a ring-type raft domain of closed topology. Here, by reconstituting the bud topography in a model membrane, we demonstrate the preferential localization of cholesterol- and sphingomyelin-enriched microdomains in the collar band of the bud-neck interfaced with the donor membrane. The geometrical approach to the recapitulation of the dynamic membrane reorganization, resulting from the local radii of curvatures from nanometre-to-micrometre scales, offers important clues for understanding the active roles of the bud topography in the sorting and migration machinery of key signalling proteins involved in membrane budding