1,415 research outputs found
Understanding the "Family Gap" in Pay for Women with Children
As the gender gap in pay between women and men has been narrowing, the "family gap" in pay between mothers and nonmothers has been widening. One reason may be the institutional structure in the United States, which has emphasized equal pay and opportunity policies but not family policies, in contrast to other countries that have implemented both. The authors now have evidence on the links between one such family policy and women's pay. Recent research suggests that maternity leave coverage, by raising women's retention after childbirth, also raises women's levels of work experience, job tenure, and pay
Single-cell profiling of alveolar rhabdomyosarcoma reveals RAS pathway inhibitors as cell-fate hijackers with therapeutic relevance
Rhabdomyosarcoma (RMS) is a group of pediatric cancers with features of developing skeletal muscle. The cellular hierarchy and mechanisms leading to developmental arrest remain elusive. Here, we combined single-cell RNA sequencing, mass cytometry, and high-content imaging to resolve intratumoral heterogeneity of patient-derived primary RMS cultures. We show that the aggressive alveolar RMS (aRMS) subtype contains plastic muscle stem-like cells and cycling progenitors that drive tumor growth, and a subpopulation of differentiated cells that lost its proliferative potential and correlates with better outcomes. While chemotherapy eliminates cycling progenitors, it enriches aRMS for muscle stem-like cells. We screened for drugs hijacking aRMS toward clinically favorable subpopulations and identified a combination of RAF and MEK inhibitors that potently induces myogenic differentiation and inhibits tumor growth. Overall, our work provides insights into the developmental states underlying aRMS aggressiveness, chemoresistance, and progression and identifies the RAS pathway as a promising therapeutic target
A rhetoric-in-context approach to building commitment to multiple strategic goals
There are still few explanations of the micro-level practices by which top managers influence employee commitment to multiple strategic goals. This paper argues that, through their language, top managers can construct a context for commitment to multiple strategic goals. We therefore propose a rhetoric-in-context approach to illuminate some of the micro practices through which top managers influence employee commitment. Based upon an empirical study of the rhetorical practices through which top managers influence academic commitment to multiple strategic goals in university contexts, we demonstrate relationships between rhetoric and context. Specifically, we show that rhetorical influences over commitment to multiple goals are associated with the historical context for multiple goals, the degree to which top managers' rhetoric instantiates a change in that context, and the internal consistency of the rhetorical practices used by top managers. Copyright © 2007 SAGE Publications
A method for comparing multiple imputation techniques: A case study on the U.S. national COVID cohort collaborative.
Healthcare datasets obtained from Electronic Health Records have proven to be extremely useful for assessing associations between patients’ predictors and outcomes of interest. However, these datasets often suffer from missing values in a high proportion of cases, whose removal may introduce severe bias. Several multiple imputation algorithms have been proposed to attempt to recover the missing information under an assumed missingness mechanism. Each algorithm presents strengths and weaknesses, and there is currently no consensus on which multiple imputation algorithm works best in a given scenario. Furthermore, the selection of each algorithm’s pa- rameters and data-related modeling choices are also both crucial and challenging
The Medical Action Ontology: A tool for annotating and analyzing treatments and clinical management of human disease.
BACKGROUND: Navigating the clinical literature to determine the optimal clinical management for rare diseases presents significant challenges. We introduce the Medical Action Ontology (MAxO), an ontology specifically designed to organize medical procedures, therapies, and interventions.
METHODS: MAxO incorporates logical structures that link MAxO terms to numerous other ontologies within the OBO Foundry. Term development involves a blend of manual and semi-automated processes. Additionally, we have generated annotations detailing diagnostic modalities for specific phenotypic abnormalities defined by the Human Phenotype Ontology (HPO). We introduce a web application, POET, that facilitates MAxO annotations for specific medical actions for diseases using the Mondo Disease Ontology.
FINDINGS: MAxO encompasses 1,757 terms spanning a wide range of biomedical domains, from human anatomy and investigations to the chemical and protein entities involved in biological processes. These terms annotate phenotypic features associated with specific disease (using HPO and Mondo). Presently, there are over 16,000 MAxO diagnostic annotations that target HPO terms. Through POET, we have created 413 MAxO annotations specifying treatments for 189 rare diseases.
CONCLUSIONS: MAxO offers a computational representation of treatments and other actions taken for the clinical management of patients. Its development is closely coupled to Mondo and HPO, broadening the scope of our computational modeling of diseases and phenotypic features. We invite the community to contribute disease annotations using POET (https://poet.jax.org/). MAxO is available under the open-source CC-BY 4.0 license (https://github.com/monarch-initiative/MAxO).
FUNDING: NHGRI 1U24HG011449-01A1 and NHGRI 5RM1HG010860-04
Positive and Normative Judgments Implicit in U.S. Tax Policy, and the Costs of Unequal Growth and Recessions
Expansion of the Human Phenotype Ontology (HPO) knowledge base and resources.
The Human Phenotype Ontology (HPO)-a standardized vocabulary of phenotypic abnormalities associated with 7000+ diseases-is used by thousands of researchers, clinicians, informaticians and electronic health record systems around the world. Its detailed descriptions of clinical abnormalities and computable disease definitions have made HPO the de facto standard for deep phenotyping in the field of rare disease. The HPO\u27s interoperability with other ontologies has enabled it to be used to improve diagnostic accuracy by incorporating model organism data. It also plays a key role in the popular Exomiser tool, which identifies potential disease-causing variants from whole-exome or whole-genome sequencing data. Since the HPO was first introduced in 2008, its users have become both more numerous and more diverse. To meet these emerging needs, the project has added new content, language translations, mappings and computational tooling, as well as integrations with external community data. The HPO continues to collaborate with clinical adopters to improve specific areas of the ontology and extend standardized disease descriptions. The newly redesigned HPO website (www.human-phenotype-ontology.org) simplifies browsing terms and exploring clinical features, diseases, and human genes
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