66 research outputs found

    Cellular Therapy for Fanconi Anemia: The Past, Present, and Future

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    Allogeneic hematopoietic cell transplantation (HCT) remains the only proven curative therapy for the hematologic manifestation of Fanconi anemia (FA). Over the past 2 decades, major advances have been made such that transplant outcomes have markedly improved. With the development of in vitro fertilization and preimplantation genetic diagnosis, HLA-matched sibling donor umbilical blood transplantation may be an option for more patients with FA. Recently, the use of pluripotent stem cells has been explored as a novel approach to model the hematopoietic developmental defects in FA, and to provide a potential source of autologous stem cells that can be genetically manipulated and used to generate corrected hematopoietic progenitors

    Dynamic instability of genomic methylation patterns in pluripotent stem cells

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    <p>Abstract</p> <p>Background</p> <p>Genomic methylation patterns are established during gametogenesis, and perpetuated in somatic cells by faithful maintenance methylation. There have been previous indications that genomic methylation patterns may be less stable in embryonic stem (ES) cells than in differentiated somatic cells, but it is not known whether different mechanisms of <it>de novo </it>and maintenance methylation operate in pluripotent stem cells compared with differentiating somatic cells.</p> <p>Results</p> <p>In this paper, we show that ablation of the DNA methyltransferase regulator DNMT3L (DNA methyltransferase 3-like) in mouse ES cells renders them essentially incapable of <it>de novo </it>methylation of newly integrated retroviral DNA. We also show that ES cells lacking DNMT3L lose DNA methylation over time in culture, suggesting that DNA methylation in ES cells is the result of dynamic loss and gain of DNA methylation. We found that wild-type female ES cells lose DNA methylation at a much faster rate than do male ES cells; this defect could not be attributed to sex-specific differences in expression of DNMT3L or of any DNA methyltransferase. We also found that human ES and induced pluripotent stem cell lines showed marked but variable loss of methylation that could not be attributed to sex chromosome constitution or time in culture.</p> <p>Conclusions</p> <p>These data indicate that DNA methylation in pluripotent stem cells is much more dynamic and error-prone than is maintenance methylation in differentiated cells. DNA methylation requires DNMT3L in stem cells, but DNMT3L is not expressed in differentiating somatic cells. Error-prone maintenance methylation will introduce unpredictable phenotypic variation into clonal populations of pluripotent stem cells, and this variation is likely to be much more pronounced in cultured female cells. This epigenetic variability has obvious negative implications for the clinical applications of stem cells.</p

    Eight pruning deep learning models for low storage and high-speed COVID-19 computed tomography lung segmentation and heatmap-based lesion localization: A multicenter study using COVLIAS 2.0.

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    COVLIAS 1.0: an automated lung segmentation was designed for COVID-19 diagnosis. It has issues related to storage space and speed. This study shows that COVLIAS 2.0 uses pruned AI (PAI) networks for improving both storage and speed, wiliest high performance on lung segmentation and lesion localization.ology: The proposed study uses multicenter ∼9,000 CT slices from two different nations, namely, CroMed from Croatia (80 patients, experimental data), and NovMed from Italy (72 patients, validation data). We hypothesize that by using pruning and evolutionary optimization algorithms, the size of the AI models can be reduced significantly, ensuring optimal performance. Eight different pruning techniques (i) differential evolution (DE), (ii) genetic algorithm (GA), (iii) particle swarm optimization algorithm (PSO), and (iv) whale optimization algorithm (WO) in two deep learning frameworks (i) Fully connected network (FCN) and (ii) SegNet were designed. COVLIAS 2.0 was validated using "Unseen NovMed" and benchmarked against MedSeg. Statistical tests for stability and reliability were also conducted.Pruning algorithms (i) FCN-DE, (ii) FCN-GA, (iii) FCN-PSO, and (iv) FCN-WO showed improvement in storage by 92.4%, 95.3%, 98.7%, and 99.8% respectively when compared against solo FCN, and (v) SegNet-DE, (vi) SegNet-GA, (vii) SegNet-PSO, and (viii) SegNet-WO showed improvement by 97.1%, 97.9%, 98.8%, and 99.2% respectively when compared against solo SegNet. AUC > 0.94 (p 0.86 (p < 0.0001) on NovMed data set for all eight EA model. PAI <0.25 s per image. DenseNet-121-based Grad-CAM heatmaps showed validation on glass ground opacity lesions.Eight PAI networks that were successfully validated are five times faster, storage efficient, and could be used in clinical settings

    Drug discovery for Diamond-Blackfan anemia using reprogrammed hematopoietic progenitors

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    Diamond-Blackfan anemia (DBA) is a congenital disorder characterized by the failure of erythroid progenitor differentiation, severely curtailing red blood cell production. Because many DBA patients fail to respond to corticosteroid therapy, there is considerable need for therapeutics for this disorder. Identifying therapeutics for DBA requires circumventing the paucity of primary patient blood stem and progenitor cells. To this end, we adopted a reprogramming strategy to generate expandable hematopoietic progenitor cells from induced pluripotent stem cells (iPSCs) from DBA patients. Reprogrammed DBA progenitors recapitulate defects in erythroid differentiation, which were rescued by gene complementation. Unbiased chemical screens identified SMER28, a small-molecule inducer of autophagy, which enhanced erythropoiesis in a range of in vitro and in vivo models of DBA. SMER28 acted through autophagy factor ATG5 to stimulate erythropoiesis and up-regulate expression of globin genes. These findings present an unbiased drug screen for hematological disease using iPSCs and identify autophagy as a therapeutic pathway in DBA.National Institute of Diabetes and Digestive and Kidney Diseases (U.S.) (Grant R24-DK092760)National Institute of Diabetes and Digestive and Kidney Diseases (U.S.) (Grant R24-DK49216)National Institute of Diabetes and Digestive and Kidney Diseases (U.S.) (Grant U54DK110805)National Heart, Lung, and Blood Institute (Grant UO1-HL100001)National Heart, Lung, and Blood Institute (Grant U01HL134812)National Heart, Lung, and Blood Institute (Grant R01HL04880)National Institutes of Health (U.S.) (Grant R24OD017870-01

    Multimodality carotid plaque tissue characterization and classification in the artificial intelligence paradigm: a narrative review for stroke application

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    Cardiovascular disease (CVD) is one of the leading causes of morbidity and mortality in the United States of America and globally. Carotid arterial plaque, a cause and also a marker of such CVD, can be detected by various non-invasive imaging modalities such as magnetic resonance imaging (MRI), computer tomography (CT), and ultrasound (US). Characterization and classification of carotid plaque-type in these imaging modalities, especially into symptomatic and asymptomatic plaque, helps in the planning of carotid endarterectomy or stenting. It can be challenging to characterize plaque components due to (I) partial volume effect in magnetic resonance imaging (MRI) or (II) varying Hausdorff values in plaque regions in CT, and (III) attenuation of echoes reflected by the plaque during US causing acoustic shadowing. Artificial intelligence (AI) methods have become an indispensable part of healthcare and their applications to the non-invasive imaging technologies such as MRI, CT, and the US. In this narrative review, three main types of AI models (machine learning, deep learning, and transfer learning) are analyzed when applied to MRI, CT, and the US. A link between carotid plaque characteristics and the risk of coronary artery disease is presented. With regard to characterization, we review tools and techniques that use AI models to distinguish carotid plaque types based on signal processing and feature strengths. We conclude that AI-based solutions offer an accurate and robust path for tissue characterization and classification for carotid artery plaque imaging in all three imaging modalities. Due to cost, user-friendliness, and clinical effectiveness, AI in the US has dominated the most

    Somatic coding mutations in human induced pluripotent stem cells

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    Defined transcription factors can induce epigenetic reprogramming of adult mammalian cells into induced pluripotent stem cells. Although DNA factors are integrated during some reprogramming methods, it is unknown whether the genome remains unchanged at the single nucleotide level. Here we show that 22 human induced pluripotent stem (hiPS) cell lines reprogrammed using five different methods each contained an average of five protein-coding point mutations in the regions sampled (an estimated six protein-coding point mutations per exome). The majority of these mutations were non-synonymous, nonsense or splice variants, and were enriched in genes mutated or having causative effects in cancers. At least half of these reprogramming-associated mutations pre-existed in fibroblast progenitors at low frequencies, whereas the rest occurred during or after reprogramming. Thus, hiPS cells acquire genetic modifications in addition to epigenetic modifications. Extensive genetic screening should become a standard procedure to ensure hiPS cell safety before clinical use

    Simultaneous sequencing of oxidized methylcytosines produced by TET/JBP dioxygenases in Coprinopsis cinerea

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    A prominent epigenetic mechanism for gene regulation is methylation of cytosine bases in DNA. TET enzymes facilitate DNA demethylation by converting 5-methylcytosine (5mC) to oxidized methylcytosines (oxi-mCs). We show that oxi-mCs are generated by conserved TET/JBP enzymes encoded in the genome of the model organism Coprinopsis cinerea and present a method for simultaneous mapping of the three different species of oxi-mCs at near–base-pair resolution. We observe that centromeres and transposable elements exhibit distinctive patterns of 5mC and oxi-mC, and show that gene body 5mC and oxi-mC mark silent paralogous multicopy genes. Our study describes a method to map three species of oxi-mC simultaneously and reveals the colocation of 5mC and oxi-mC at functional elements throughout the C. cinerea genome

    Large intergenic non-coding RNA-RoR modulates reprogramming of human induced pluripotent stem cells

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    February 17, 2011The conversion of lineage-committed cells to induced pluripotent stem cells (iPSCs) by reprogramming is accompanied by a global remodeling of the epigenome[superscript 1, 2, 3, 4, 5], resulting in altered patterns of gene expression[superscript 2, 6, 7, 8, 9]. Here we characterize the transcriptional reorganization of large intergenic non-coding RNAs (lincRNAs)[superscript 10, 11] that occurs upon derivation of human iPSCs and identify numerous lincRNAs whose expression is linked to pluripotency. Among these, we defined ten lincRNAs whose expression was elevated in iPSCs compared with embryonic stem cells, suggesting that their activation may promote the emergence of iPSCs. Supporting this, our results indicate that these lincRNAs are direct targets of key pluripotency transcription factors. Using loss-of-function and gain-of-function approaches, we found that one such lincRNA (lincRNA-RoR) modulates reprogramming, thus providing a first demonstration for critical functions of lincRNAs in the derivation of pluripotent stem cells
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