Kenneth D. Gibbs

Bio: Kenneth D. Gibbs is an academic researcher from National Institutes of Health. The author has contributed to research in topics: Haematopoiesis & Progenitor cell. The author has an hindex of 16, co-authored 24 publications receiving 3291 citations. Previous affiliations of Kenneth D. Gibbs include University of Maryland, Baltimore County & National Science Foundation.

Extracting a cellular hierarchy from high-dimensional cytometry data with SPADE

Abstract: The ability to analyze multiple single-cell parameters is critical for understanding cellular heterogeneity. Despite recent advances in measurement technology, methods for analyzing high-dimensional single-cell data are often subjective, labor intensive and require prior knowledge of the biological system. To objectively uncover cellular heterogeneity from single-cell measurements, we present a versatile computational approach, spanning-tree progression analysis of density-normalized events (SPADE). We applied SPADE to flow cytometry data of mouse bone marrow and to mass cytometry data of human bone marrow. In both cases, SPADE organized cells in a hierarchy of related phenotypes that partially recapitulated well-described patterns of hematopoiesis. We demonstrate that SPADE is robust to measurement noise and to the choice of cellular markers. SPADE facilitates the analysis of cellular heterogeneity, the identification of cell types and comparison of functional markers in response to perturbations.

What Do I Want to Be with My PhD? The Roles of Personal Values and Structural Dynamics in Shaping the Career Interests of Recent Biomedical Science PhD Graduates

Abstract: Interest in faculty careers decreases as graduate training progresses; however, the process underlying career-interest formation remains poorly defined. To better understand this process and whether/how it differs across social identity (i.e., race/ethnicity, gender), we conducted focus groups with 38 biomedical scientists who received PhDs between 2006 and 2011, including 23 women and 18 individuals from underrepresented minority (URM) backgrounds. Objective performance and quality of advisor relationships were not significantly different between scientists with high versus low interest in faculty careers. Career interests were fluid and formed in environments that generally lacked structured career development. Vicarious learning shaped similar outcome expectations about academic careers for all scientists; however, women and URMs recounted additional, distinct experiences and expectations. Scientists pursuing faculty careers described personal values, which differed by social identity, as their primary driver. For scientists with low interest in faculty careers, a combination of values, shared across social identity, and structural dynamics of the biomedical workforce (e.g., job market, grant funding, postdoc pay, etc.) played determinative roles. These findings illuminate the complexity of career choice and suggest attracting the best, most diverse academic workforce requires institutional leaders and policy makers go beyond developing individual skill, attending to individuals' values and promoting institutional and systemic reforms.

Biomedical Science Ph.D. Career Interest Patterns by Race/Ethnicity and Gender.

Abstract: Increasing biomedical workforce diversity remains a persistent challenge. Recent reports have shown that biomedical sciences (BMS) graduate students become less interested in faculty careers as training progresses; however, it is unclear whether or how the career preferences of women and underrepresented minority (URM) scientists change in manners distinct from their better-represented peers. We report results from a survey of 1500 recent American BMS Ph.D. graduates (including 276 URMs) that examined career preferences over the course of their graduate training experiences. On average, scientists from all social backgrounds showed significantly decreased interest in faculty careers at research universities, and significantly increased interest in non-research careers at Ph.D. completion relative to entry. However, group differences emerged in overall levels of interest (at Ph.D. entry and completion), and the magnitude of change in interest in these careers. Multiple logistic regression showed that when controlling for career pathway interest at Ph.D. entry, first-author publication rate, faculty support, research self-efficacy, and graduate training experiences, differences in career pathway interest between social identity groups persisted. All groups were less likely than men from well-represented (WR) racial/ethnic backgrounds to report high interest in faculty careers at research-intensive universities (URM men: OR 0.60, 95% CI: 0.36–0.98, p50.04; WR women: OR: 0.64, 95% CI: 0.47–0.89, p50.008; URM women: OR: 0.46, 95% CI: 0.30–0.71, p,0.001), and URM women were more likely than all other groups to report high interest in non-research careers (OR: 1.93, 95% CI: 1.28–2.90, p50.002). The persistence of disparities in the career interests of Ph.D. recipients suggests that a supply-side (or ‘‘pipeline’’) framing of biomedical workforce diversity challenges may limit the effectiveness of efforts to attract and retain the best and most diverse workforce. We propose incorporation of

Qualitative research for education: An introduction to theories and methods

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The dynamics and regulators of cell fate decisions are revealed by pseudotemporal ordering of single cells

Abstract: Defining the transcriptional dynamics of a temporal process such as cell differentiation is challenging owing to the high variability in gene expression between individual cells. Time-series gene expression analyses of bulk cells have difficulty distinguishing early and late phases of a transcriptional cascade or identifying rare subpopulations of cells, and single-cell proteomic methods rely on a priori knowledge of key distinguishing markers. Here we describe Monocle, an unsupervised algorithm that increases the temporal resolution of transcriptome dynamics using single-cell RNA-Seq data collected at multiple time points. Applied to the differentiation of primary human myoblasts, Monocle revealed switch-like changes in expression of key regulatory factors, sequential waves of gene regulation, and expression of regulators that were not known to act in differentiation. We validated some of these predicted regulators in a loss-of function screen. Monocle can in principle be used to recover single-cell gene expression kinetics from a wide array of cellular processes, including differentiation, proliferation and oncogenic transformation.

Molecular mechanisms of cell death: recommendations of the Nomenclature Committee on Cell Death 2018.

Abstract: Over the past decade, the Nomenclature Committee on Cell Death (NCCD) has formulated guidelines for the definition and interpretation of cell death from morphological, biochemical, and functional perspectives. Since the field continues to expand and novel mechanisms that orchestrate multiple cell death pathways are unveiled, we propose an updated classification of cell death subroutines focusing on mechanistic and essential (as opposed to correlative and dispensable) aspects of the process. As we provide molecularly oriented definitions of terms including intrinsic apoptosis, extrinsic apoptosis, mitochondrial permeability transition (MPT)-driven necrosis, necroptosis, ferroptosis, pyroptosis, parthanatos, entotic cell death, NETotic cell death, lysosome-dependent cell death, autophagy-dependent cell death, immunogenic cell death, cellular senescence, and mitotic catastrophe, we discuss the utility of neologisms that refer to highly specialized instances of these processes. The mission of the NCCD is to provide a widely accepted nomenclature on cell death in support of the continued development of the field.

Tumour-associated macrophages as treatment targets in oncology

Abstract: Macrophages are crucial drivers of tumour-promoting inflammation. Tumour-associated macrophages (TAMs) contribute to tumour progression at different levels: by promoting genetic instability, nurturing cancer stem cells, supporting metastasis, and taming protective adaptive immunity. TAMs can exert a dual, yin-yang influence on the effectiveness of cytoreductive therapies (chemotherapy and radiotherapy), either antagonizing the antitumour activity of these treatments by orchestrating a tumour-promoting, tissue-repair response or, instead, enhancing the overall antineoplastic effect. TAMs express molecular triggers of checkpoint proteins that regulate T-cell activation, and are targets of certain checkpoint-blockade immunotherapies. Other macrophage-centred approaches to anticancer therapy are under investigation, and include: inhibition of macrophage recruitment to, and/or survival in, tumours; functional re-education of TAMs to an antitumour, 'M1-like' mode; and tumour-targeting monoclonal antibodies that elicit macrophage-mediated extracellular killing, or phagocytosis and intracellular destruction of cancer cells. The evidence supporting these strategies is reviewed herein. We surmise that TAMs can provide tools to tailor the use of cytoreductive therapies and immunotherapy in a personalized medicine approach, and that TAM-focused therapeutic strategies have the potential to complement and synergize with both chemotherapy and immunotherapy.