92 research outputs found

    Transcriptional recapitulation and subversion of embryonic colon development by mouse colon tumor models and human colon cancer

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    Colon tumors from four independent mouse models and 100 human colorectal cancers all exhibited striking recapitulation of embryonic colon gene expression from embryonic days 13.5-18.5

    Lipids, blood pressure and kidney update 2015

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    Updated International Tuberous Sclerosis Complex Diagnostic Criteria and Surveillance and Management Recommendations

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    Background: Tuberous sclerosis complex (TSC) is an autosomal dominant genetic disease affecting multiple body systems with wide variability in presentation. In 2013, Pediatric Neurology published articles outlining updated diagnostic criteria and recommendations for surveillance and management of disease manifestations. Advances in knowledge and approvals of new therapies necessitated a revision of those criteria and recommendations. Methods: Chairs and working group cochairs from the 2012 International TSC Consensus Group were invited to meet face-to-face over two days at the 2018 World TSC Conference on July 25 and 26 in Dallas, TX, USA. Before the meeting, working group cochairs worked with group members via e-mail and telephone to (1) review TSC literature since the 2013 publication, (2) confirm or amend prior recommendations, and (3) provide new recommendations as required. Results: Only two changes were made to clinical diagnostic criteria reported in 2013: “multiple cortical tubers and/or radial migration lines” replaced the more general term “cortical dysplasias,” and sclerotic bone lesions were reinstated as a minor criterion. Genetic diagnostic criteria were reaffirmed, including highlighting recent findings that some individuals with TSC are genetically mosaic for variants in TSC1 or TSC2. Changes to surveillance and management criteria largely reflected increased emphasis on early screening for electroencephalographic abnormalities, enhanced surveillance and management of TSC-associated neuropsychiatric disorders, and new medication approvals. Conclusions: Updated TSC diagnostic criteria and surveillance and management recommendations presented here should provide an improved framework for optimal care of those living with TSC and their families

    Global gene expression profile progression in Gaucher disease mouse models

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    <p>Abstract</p> <p>Background</p> <p>Gaucher disease is caused by defective glucocerebrosidase activity and the consequent accumulation of glucosylceramide. The pathogenic pathways resulting from lipid laden macrophages (Gaucher cells) in visceral organs and their abnormal functions are obscure.</p> <p>Results</p> <p>To elucidate this pathogenic pathway, developmental global gene expression analyses were conducted in distinct <it>Gba1 </it>point-mutated mice (V394L/V394L and D409 V/null). About 0.9 to 3% of genes had altered expression patterns (≥ ± 1.8 fold change), representing several categories, but particularly macrophage activation and immune response genes. Time course analyses (12 to 28 wk) of INFγ-regulated pro-inflammatory (13) and IL-4-regulated anti-inflammatory (11) cytokine/mediator networks showed tissue differential profiles in the lung and liver of the <it>Gba1 </it>mutant mice, implying that the lipid-storage macrophages were not functionally inert. The time course alterations of the INFγ and IL-4 pathways were similar, but varied in degree in these tissues and with the <it>Gba1 </it>mutation.</p> <p>Conclusions</p> <p>Biochemical and pathological analyses demonstrated direct relationships between the degree of tissue glucosylceramides and the gene expression profile alterations. These analyses implicate IFNγ-regulated pro-inflammatory and IL-4-regulated anti-inflammatory networks in differential disease progression with implications for understanding the Gaucher disease course and pathophysiology.</p

    International comparisons of laboratory values from the 4CE collaborative to predict COVID-19 mortality

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    Given the growing number of prediction algorithms developed to predict COVID-19 mortality, we evaluated the transportability of a mortality prediction algorithm using a multi-national network of healthcare systems. We predicted COVID-19 mortality using baseline commonly measured laboratory values and standard demographic and clinical covariates across healthcare systems, countries, and continents. Specifically, we trained a Cox regression model with nine measured laboratory test values, standard demographics at admission, and comorbidity burden pre-admission. These models were compared at site, country, and continent level. Of the 39,969 hospitalized patients with COVID-19 (68.6% male), 5717 (14.3%) died. In the Cox model, age, albumin, AST, creatine, CRP, and white blood cell count are most predictive of mortality. The baseline covariates are more predictive of mortality during the early days of COVID-19 hospitalization. Models trained at healthcare systems with larger cohort size largely retain good transportability performance when porting to different sites. The combination of routine laboratory test values at admission along with basic demographic features can predict mortality in patients hospitalized with COVID-19. Importantly, this potentially deployable model differs from prior work by demonstrating not only consistent performance but also reliable transportability across healthcare systems in the US and Europe, highlighting the generalizability of this model and the overall approach
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