16 research outputs found

    Emerging disease-modifying therapies for sickle cell disease

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    Sickle cell disease afflicts millions of people worldwide and approximately 100,000 Americans. Complications are myriad and arise as a result of complex pathological pathways ‘downstream’ to a point mutation in DNA, and include red blood cell membrane damage, inflammation, chronic hemolytic anemia with episodic vaso-occlusion, ischemia and pain, and ultimately risk of cumulative organ damage with reduced lifespan of affected individuals. The National Heart, Lung, and Blood Institute’s 2014 evidence-based guideline for sickle cell disease management states that additional research is needed before investigational curative therapies will be widely available to most patients with sickle cell disease. To date, sickle cell disease has been cured by hematopoietic stem cell transplantation in approximately 1,000 people, most of whom were children, and significantly ameliorated by gene therapy in a handful of subjects who have only limited follow-up thus far. During a timespan in which over 20 agents were approved for the treatment of cystic fibrosis by the Food and Drug Administration, similar approval was granted for only two drugs for sickle cell disease (hydroxyurea and L-glutamine) despite the higher prevalence of sickle cell disease. This trajectory appears to be changing, as the lack of multimodal agent therapy in sickle cell disease has spurred engagement among many in academia and industry who, in the last decade, have developed new drugs poised to prevent complications and alleviate suffering. Identified therapeutic strategies include fetal hemoglobin induction, inhibition of intracellular HbS polymerization, inhibition of oxidant stress and inflammation, and perturbation of the activation of the endothelium and other blood components (e.g. platelets, white blood cells, coagulation proteins) involved in the pathophysiology of sickle cell disease. In this article, we present a crash-course review of disease-modifying approaches (minus hematopoietic stem cell transplant and gene therapy) for patients with sickle cell disease currently, or recently, tested in clinical trials in the era following approval of hydroxyurea

    Pulmonary Alveolar Proteinosis in Association with Congenital Dyserythropoietic Anemia: A Case Report

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    A two-year-old girl with congenital dyserythropoietic anemia (CDA) acutely developed fever, tachypnea, and increased oxygen requirement. Chest X-ray revealed bilateral interstitial infiltrates and mild cardiomegaly. Blood cultures grew no infectious agents, while pulmonary specimens grew cytomegalovirus (CMV). Treatment with intravenous ganciclovir was initiated but without response. Final cytologic preparations of bronchoalveolar lavage (BAL) fluid revealed eosinophilic amorphous material consistent with pulmonary alveolar proteinosis (PAP). CDA and PAP are extremely rare disorders in pediatrics. PAP should be considered in patients with hematological disorders who present with acute interstitial pneumonia, after infectious causes are ruled out

    iCLOTS: open-source, artificial intelligence-enabled software for analyses of blood cells in microfluidic and microscopy-based assays

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    Abstract While microscopy-based cellular assays, including microfluidics, have significantly advanced over the last several decades, there has not been concurrent development of widely-accessible techniques to analyze time-dependent microscopy data incorporating phenomena such as fluid flow and dynamic cell adhesion. As such, experimentalists typically rely on error-prone and time-consuming manual analysis, resulting in lost resolution and missed opportunities for innovative metrics. We present a user-adaptable toolkit packaged into the open-source, standalone Interactive Cellular assay Labeled Observation and Tracking Software (iCLOTS). We benchmark cell adhesion, single-cell tracking, velocity profile, and multiscale microfluidic-centric applications with blood samples, the prototypical biofluid specimen. Moreover, machine learning algorithms characterize previously imperceptible data groupings from numerical outputs. Free to download/use, iCLOTS addresses a need for a field stymied by a lack of analytical tools for innovative, physiologically-relevant assays of any design, democratizing use of well-validated algorithms for all end-user biomedical researchers who would benefit from advanced computational methods
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