Abstract Myeloblast expansion is a hallmark of disease progression and comprises CD34+ hematopoietic stem and progenitor cells (HSPC). How this compartment evolves during disease progression in chronic myeloid neoplasms is unknown. Using single-cell RNA sequencing and high-parameter flow cytometry, we show that chronic myelomonocytic leukemia (CMML) CD34+ HSPC can be classified into three differentiation trajectories: monocytic, megakaryocyte-erythroid progenitor (MEP), and normal-like. Hallmarks of monocytic-biased trajectory were enrichment of CD120b+ inflammatory granulocyte–macrophage progenitor (GMP)-like cells, activated cytokine receptor signaling, phenotypic hematopoietic stem cell (HSC) depletion, and adverse outcomes. Cytokine receptor diversity was generally an adverse feature and elevated in CD120b+ GMPs. Hypomethylating agents decreased monocytic-biased cells in CMML patients. Given the enrichment of RAS pathway mutations in monocytic-biased cells, NRAS-competitive transplants and LPS-treated xenograft models recapitulated monocytic-biased CMML, suggesting that hematopoietic stress precipitates the monocytic-biased state. Deconvolution of HSPC compartments in other myeloid neoplasms and identifying therapeutic strategies to mitigate the monocytic-biased differentiation trajectory should be explored. Significance: Our findings establish that multiple differentiation states underlie CMML disease progression. These states are negatively augmented by inflammation and positively affected by hypomethylating agents. Furthermore, we identify HSC depletion and expansion of GMP-like cells with increased cytokine receptor diversity as a feature of myeloblast expansion in inflammatory chronic myeloid neoplasms. This article is highlighted in the In This Issue feature, p. 476
Introduction: Residency interview apparel has traditionally been the dark business suit. We changed the interview dress code from a traditionally established unwritten 'formal' attire to an explicitly described 'informal' attire. We sought to assess if the change in dress code attire changed applicants' perceptions of the residency program or decreased costs.Methods: The authors conducted an anonymous survey of applicants applying to one emergency medicine residency program during two application cycles ending in 2012 and 2013. Applicants were asked if the change in dress code affected their perception of the program, comfort level, overall costs and how it affected their rank lists.Results: We sent the survey to 308 interviewed applicants over two years. Of those, 236 applicants completed the survey for a combined response rate of 76.6% (236/308). Among respondents, 85.1% (200 of 235) stated they appreciated the change; 66.7% (154 of 231) stated the change caused them to worry more about what to wear. Males were more uncomfortable than females due to the lack of uniformity on the interview day (18.5% of males [25/135] vs. 7.4% of females [7/95], collapsed results p-value 0.008). A total of 27.7% (64/231) agreed that the costs were less overall. The change caused 50 of 230 (21.7%) applicants to rank the program higher on their rank list and only one applicant to rank the program lower.Conclusion: A change to a more informal dress code resulted in more comfort and fewer costs for applicants to a single residency program. The change also resulted in some applicants placing the program higher on their rank order list. [West J Emerg Med. 2015;16(1):-0.]
Background & Aims Accurate data resources are essential for impactful medical research. To date, most large-scale studies have relied on structured sources, such as International Classification of Diseases codes, to determine patient diagnoses and outcomes. However, these structured datasets are often incomplete or inaccurate. Recent advances in natural language processing, specifically the introduction of open-weight large language models (LLMs), enable more accurate data extraction from unstructured text in electronic health records (EHRs). Methods We created an approach using LLMs for identifying histopathologic diagnoses, including presence of dysplasia and cancer, in pathology reports from the Department of Veterans Affairs Healthcare System, including those patients with genotype data within the Million Veteran Program (MVP) biobank. Our approach requires no additional training and utilizes a simple 'yes/no' question prompt to obtain an answer. We validated the method on 3 diagnostic tasks by applying the same prompts to reports from patients with vs without diagnoses of inflammatory bowel disease (IBD) and calculating F-1 scores as a balanced accuracy measure. Results In patients without IBD in MVP, we achieved F1-scores of 99.3% for identifying any dysplasia, 98.2% for identifying high-grade dysplasia and/or colorectal adenocarcinoma (HGD/CRC), and 96.2% for identifying CRC using LLM Gemma-2. In IBD patients in MVP, we achieved F1-scores of 97.1% for identifying dysplasia, 96.4% for identifying HGD/CRC, and 97.1% for identifying CRC. Conclusion LLMs provide excellent accuracy in extracting diagnoses from EHRs and can be applied to a variety of tasks with no additional human-led development required. Our validated methods generalized to unstructured pathology notes, even withstanding challenges of resource-limited computing environments.
Objectives: To determine the quantitative differences in telithromycin and azithromycin MIC values against Streptococcus pneumoniae, Haemophilus influenzae and Streptococcus pyogenes obtained using two recommended and commonly used methodologies: CLSI reference standard broth microdilution in ambient air and Etest® concentration gradient in CO2.
A growing number of countries are embracing graduate training in the specialty of Family Medicine as a core component of global health systems reform. One significant challenge for new programs is to adequately prepare for educational excellence and leadership. Promising residents are often encouraged to remain in their program as faculty, but may not have had the benefit of specific training in teaching, curriculum development, learner assessment or educational leadership. Faculty Development is a potential avenue to providing these skills to new Family Medicine Faculty and to encourage new graduates to consider teaching. We are currently seeking to further clarify what the current needs and future possibilities are for Family Medicine Faculty Development in Sub-Saharan Africa.
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