A Qualitative Study of Transgender Women and Cisgender Men Living Together in Two Recovery Homes

Oxford Houses (OH) are a peer-run sober living homes that are the largest network of recovery homes with over 2,000 in the US. They are self-run without any professional staff. The current study focused on better understanding the facilitators and barriers to OH entry for transgender individuals. The study explored ways in which transgender people found entry into the OHs and the experiences of transgender residents in OHs in comparison to cisgender residents

Preparing Faculty to Incorporate Health Systems Science into the Clinical Learning Environment: Factors Associated with Sustained Outcomes

This study assesses participants’ perceptions of long-term impacts of the Teachers of Quality Academy, a medical school faculty development program designed to prepare faculty to both practice and teach health system science. A previously published 1-year evaluation of the first cohort of 27 participants showed improved perceived skills, with positive career and health system impacts. In this 5-year evaluation, a mixed-methods design included a questionnaire followed by semistructured interviews to assess perceived long-term impacts on participants. Quantitative and qualitative analyses were completed. Questionnaire response rate was 88% (N = 22), and 14 interviews were analyzed. Results demonstrated that participants had incorporated quality improvement concepts into their clinical work and teaching, better understood interprofessionalism, and observed continued improvements in care delivery. They felt the longitudinal training, delivered in a shared setting, created a learning community with lasting positive effects in institutional culture, supported long-term professional development, and had broader institutional impact. Advancements in clinical care, medical education, and professional and academic advancements were noted

Exploring the Characteristics and Context that Allow Master Adaptive Learners to Thrive

Because change is ubiquitous in healthcare, clinicians must constantly make adaptations to their practice to provide the highest quality care to patients. In a previous article, Cutrer et al. described a metacognitive approach to learning based on self-regulation, which facilitates the development of the Master Adaptive Learner (MAL). The MAL process helps individuals to cultivate and demonstrate adaptive expertise, allowing them to investigate new concepts (learn) and create new solu- tions (innovate). An individual’s ability to learn in this manner is driven by several internal characteristics and is also impacted by numerous aspects of their context. In this article, the authors examine the important internal and contextual factors that can impede or foster Master Adaptive Learning

Development of Learning Objectives to Guide Enhancement of Chronic Disease Prevention and Management Curricula in Undergraduate Medical Education

Phenomenon: Chronic disease is a leading cause of death and disability in the United States. With an increase in the demand for healthcare and rising costs related to chronic care, physicians need to be better trained to address chronic disease at various stages of illness in a collaborative and cost-effective manner. Specific and measurable learning objectives are key to the design and evaluation of effective training, but there has been no consensus on chronic disease learning objectives appropriate to medical student education. Approach: Wagner’sChronic Care Model (CCM) was selected as a theoretical framework to guide development of an enhanced chronic dis-ease prevention and management (CDPM) curriculum. Findings of a literature review of CDPM competencies, objectives, and topical statements were mapped to each of the six domains of the CCM to understand the breadth of existing learning topics within each domain. At an in-person meeting, medical educators prepared a survey for the modified Delphi approach. Attendees iden-tified 51 possible learning objectives from the literature review mapping, rephrased the CCM domains as competencies, constructed possible CDPM learning objectives for each competency with the goal of reaching multi-institutional consensus on a limited number of CDPM learning objectives that would be feasible for institutions to use to guide enhancement of medical student curricula related to CDPM. After the meeting, the group developed a survey which included 39 learning objectives. In the study phase of the modified Delphi approach, 32 physician CDPM experts and educators completed an online survey to prioritize the top 20 objectives. The next step occurred at a CDPM interest group in-person meeting with the goal of identifying the top 10 objectives. Findings: The CCM domains were reframed as the following competencies for medical student education: patient self-care management, decision support, clinical information systems, community resources, delivery systems and teams, and health system practice and improvement. Eleven CDPM learning objectives were identified within the six competencies that were most important in developing curriculum for medical students. Insights: These learning objectives cut across education on the prevention and management of individual chronic diseases and frame chronic disease care as requiring the health system science competencies identified in the CCM. They are intended to be used in combination with traditional disease-specific pathophysiology and treatment objectives. Additional efforts are needed to identify specific curricular strategies and assessment tools for each learning objective

The triple helix of clinical, research, and education missions in academic health centers: A qualitative study of diverse stakeholder perspectives.

Introduction: Academic health centers are poised to improve health through their clinical, education, and research missions. However, these missions often operate in silos. The authors explored stakeholder perspectives at diverse institutions to understand challenges and identify alignment strategies. Methods: Authors used an exploratory qualitative design and thematic analysis approach with data obtained from electronic surveys sent to participants at five U.S. academic health centers (2017-18), with four different types of medical school/health system partnerships. Participants included educators, researchers, system leaders, administrators, clinical providers, resident/fellow physicians, and students. Investigators coded data using constant comparative analysis, met regularly to reconcile uncertainties, and collapsed/combined categories. Results: Of 175 participants invited, 113 completed the survey (65%). Three results categories were identified. First, five higher-order themes emerged related to aligning missions, including (a) shared vision and strategies, (b) alignment of strategy with community needs, (c) tension of economic drivers, (d) coproduction of knowledge, and (e) unifying set of concepts spanning all missions. Second, strategies for each mission were identified, including education (new competencies, instructional methods, recruitment), research (shifting agenda, developing partnerships, operations), and clinical operations (delivery models, focus on patient factors/needs, value-based care, well-being). Lastly, strategies for integrating each dyadic mission pair, including research-education, clinical operations education, and research-clinical operations, were identified. Conclusions: Academic health centers are at a crossroads in regard to identity and alignment across the tripartite missions. The study\u27s results provide pragmatic strategies to advance the tripartite missions and lead necessary change for improved patient health

Triad pattern algorithm for predicting strong promoter candidates in bacterial genomes

Abstract Background Bacterial promoters, which increase the efficiency of gene expression, differ from other promoters by several characteristics. This difference, not yet widely exploited in bioinformatics, looks promising for the development of relevant computational tools to search for strong promoters in bacterial genomes. Results We describe a new triad pattern algorithm that predicts strong promoter candidates in annotated bacterial genomes by matching specific patterns for the group I σ70 factors of Escherichia coli RNA polymerase. It detects promoter-specific motifs by consecutively matching three patterns, consisting of an UP-element, required for interaction with the α subunit, and then optimally-separated patterns of -35 and -10 boxes, required for interaction with the σ70 subunit of RNA polymerase. Analysis of 43 bacterial genomes revealed that the frequency of candidate sequences depends on the A+T content of the DNA under examination. The accuracy of in silico prediction was experimentally validated for the genome of a hyperthermophilic bacterium, Thermotoga maritima, by applying a cell-free expression assay using the predicted strong promoters. In this organism, the strong promoters govern genes for translation, energy metabolism, transport, cell movement, and other as-yet unidentified functions. Conclusion The triad pattern algorithm developed for predicting strong bacterial promoters is well suited for analyzing bacterial genomes with an A+T content of less than 62%. This computational tool opens new prospects for investigating global gene expression, and individual strong promoters in bacteria of medical and/or economic significance.</p

Co-evolution of a broadly neutralizing HIV-1 antibody and founder virus

Current HIV-1 vaccines elicit strain-specific neutralizing antibodies. However, cross-reactive neutralizing antibodies arise in ~20% of HIV-1-infected individuals, and details of their generation could provide a roadmap for effective vaccination. Here we report the isolation, evolution and structure of a broadly neutralizing antibody from an African donor followed from time of infection. The mature antibody, CH103, neutralized ~55% of HIV-1 isolates, and its co-crystal structure with gp120 revealed a novel loop-based mechanism of CD4-binding site recognition. Virus and antibody gene sequencing revealed concomitant virus evolution and antibody maturation. Notably, the CH103-lineage unmutated common ancestor avidly bound the transmitted/founder HIV-1 envelope glycoprotein, and evolution of antibody neutralization breadth was preceded by extensive viral diversification in and near the CH103 epitope. These data elucidate the viral and antibody evolution leading to induction of a lineage of HIV-1 broadly neutralizing antibodies and provide insights into strategies to elicit similar antibodies via vaccination

Cell-type–specific eQTL of primary melanocytes facilitates identification of melanoma susceptibility genes

Most expression quantitative trait locus (eQTL) studies to date have been performed in heterogeneous tissues as opposed to specific cell types. To better understand the cell-type–specific regulatory landscape of human melanocytes, which give rise to melanoma but account for <5% of typical human skin biopsies, we performed an eQTL analysis in primary melanocyte cultures from 106 newborn males. We identified 597,335 cis-eQTL SNPs prior to linkage disequilibrium (LD) pruning and 4997 eGenes (FDR < 0.05). Melanocyte eQTLs differed considerably from those identified in the 44 GTEx tissue types, including skin. Over a third of melanocyte eGenes, including key genes in melanin synthesis pathways, were unique to melanocytes compared to those of GTEx skin tissues or TCGA melanomas. The melanocyte data set also identified trans-eQTLs, including those connecting a pigmentation-associated functional SNP with four genes, likely through cis-regulation of IRF4. Melanocyte eQTLs are enriched in cis-regulatory signatures found in melanocytes as well as in melanoma-associated variants identified through genome-wide association studies. Melanocyte eQTLs also colocalized with melanoma GWAS variants in five known loci. Finally, a transcriptome-wide association study using melanocyte eQTLs uncovered four novel susceptibility loci, where imputed expression levels of five genes (ZFP90, HEBP1, MSC, CBWD1, and RP11-383H13.1) were associated with melanoma at genome-wide significant P-values. Our data highlight the utility of lineage-specific eQTL resources for annotating GWAS findings, and present a robust database for genomic research of melanoma risk and melanocyte biology

The Theory of Interval Probabilistic Logic Programs

Two approaches to logic programming with probabilities emerged over time: Bayesian reasoning and probabilistic satisfiability (PSAT). The attractiveness of the former is in tying the logic programming research to the body of work on Bayes networks. The second approach ties, from the point of view of computation, reasoning about probabilities to linear programming, and allows for natural expression of imprecision in probabilities via the use of intervals. In this paper we construct precise semantics for one PSAT-based formalism for reasoning with interval probabilities: disjunctive probabilistic logic programs (dp-programs). It has two origins: (1) disjunctive logic programs, a powerful language for knowledge representation, first proposed by Minker in the early eighties [20] and (2) a logic programming language with interval probabilities originally considered by Ng and Subrahmanian [21,22]. We show that the probability ranges of atoms and formulas in dp-programs cannot be expressed as single intervals. We construct the precise description of the set of models for the class of dp-programs and study the computational complexity of this problem, as well as the problem of consistency of a dp-program. We also study the conditions under which our semantics coincides with the single-interval semantics originally proposed by Ng and Subrahmanian. Our work sheds light on the complexity of constructing reasoning formalisms for imprecise probabilities and suggests that interval probabilities alone are inadequate to support such reasoning