A Visionary Think Tank to Address the Nursing Workforce Crisis.

The COVID-19 pandemic exacerbated an existing problem plaguing hospital systems across the United States: a nursing workforce shortage. This article describes how one institution applied the American Organization for Nursing Leadership Nurse Executive Competencies to convene an immersive think tank to reimagine the nursing workforce.

Surge Planning and Implementation: A Required Competency for Today's Nurse Leaders.

The ability to respond effectively and efficiently during times of crisis, including a pandemic, has emerged as a competency for nurse leaders. This article describes one institution's experience using the American Organization of Nurse Leaders Competencies for Nurse Executives in operationalizing the concept of surge capacity.

Integrating the Social Determinants of Health into Nursing Practice: Nurses' Perspectives.

Purpose: The purpose of this study was to assess nurses' knowledge, perceived self-efficacy, and intended behaviors relative to integrating the social determinants of health (SDoH) into clinical practice.

Design And Methods: A cross-sectional study was completed with 768 nurses working in three hospitals within a large regional healthcare system located in the Midwest. Data were collected using an adapted 71-item SDoH Survey, which measured nurses' confidence in and frequency of discussing the SDoH with patients, general knowledge of the SDoH, familiarity with patients' social and economic conditions, and awareness of their institution's health equity strategic plan to achieve health equity.

Erythroid differentiation displays a peak of energy consumption concomitant with glycolytic metabolism rearrangements.

Our previous single-cell based gene expression analysis pointed out significant variations of LDHA level during erythroid differentiation. Deeper investigations highlighted that a metabolic switch occurred along differentiation of erythroid cells. More precisely we showed that self-renewing progenitors relied mostly upon lactate-productive glycolysis, and required LDHA activity, whereas differentiating cells, mainly involved mitochondrial oxidative phosphorylation (OXPHOS).

WASABI: a dynamic iterative framework for gene regulatory network inference.

Background: Inference of gene regulatory networks from gene expression data has been a long-standing and notoriously difficult task in systems biology. Recently, single-cell transcriptomic data have been massively used for gene regulatory network inference, with both successes and limitations.

Results: In the present work we propose an iterative algorithm called WASABI, dedicated to inferring a causal dynamical network from time-stamped single-cell data, which tackles some of the limitations associated with current approaches.

Automated cell cycle and cell size measurements for single-cell gene expression studies.

Objectives: Recent rise of single-cell studies revealed the importance of understanding the role of cell-to-cell variability, especially at the transcriptomic level. One of the numerous sources of cell-to-cell variation in gene expression is the heterogeneity in cell proliferation state. In order to identify how cell cycle and cell size influences gene expression variability at the single-cell level, we provide an universal and automatic toxic-free label method, compatible with single-cell high-throughput RT-qPCR.

Integrated time-lapse and single-cell transcription studies highlight the variable and dynamic nature of human hematopoietic cell fate commitment.

Individual cells take lineage commitment decisions in a way that is not necessarily uniform. We address this issue by characterising transcriptional changes in cord blood-derived CD34+ cells at the single-cell level and integrating data with cell division history and morphological changes determined by time-lapse microscopy. We show that major transcriptional changes leading to a multilineage-primed gene expression state occur very rapidly during the first cell cycle.

Single-Cell-Based Analysis Highlights a Surge in Cell-to-Cell Molecular Variability Preceding Irreversible Commitment in a Differentiation Process.

In some recent studies, a view emerged that stochastic dynamics governing the switching of cells from one differentiation state to another could be characterized by a peak in gene expression variability at the point of fate commitment. We have tested this hypothesis at the single-cell level by analyzing primary chicken erythroid progenitors through their differentiation process and measuring the expression of selected genes at six sequential time-points after induction of differentiation. In contrast to population-based expression data, single-cell gene expression data revealed a high cell-to-cell variability, which was masked by averaging.