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15,738 results for “stem cells”
Efficient gene expression in human stem cell derived-cortical organoids using adeno associated virus
<p><strong>Supplementary figure 6. Neuronal network activity in human cortical organoid</strong>. Videos of AAV-mediated expression of the calcium indicator jGCaMP7 under the human synapsin promoter for control (aCSF), glutamate, gabazine and TTX treated cortical organoids.</p>
Dataset with values of morphological parameters and phenotypes of cells and colonies from three human pluripotent stem cell lines
<p>The dataset is a part of the following manuscript submitted for publication in International Journal of Molecular Sciences (MDPI):</p> <p>"Prognostic Analysis of Human Pluripotent Stem Cells Based on their Morphological Portrait and Expression of Pluripotent Markers" by Olga A. Krasnova, Vitaly V. Gursky, Alina S. Chabina, K. A. Kulakova, L. L. Alekseenko, Alexandra V. Panova, Sergey L. Kiselev and Irina E. Neganova</p> <p>The files contain values of several morphological parameters and phenotypes obtained for cells and colonies from hESC line H9, hiPSC line AD3, and hiPSC line CaSR. The phenotypic information is presented in three forms: four possible classes of colonies according to the visually assessed phenotype ('bad', 'average', 'good', and 'excellent'), three possible classes (previous 'good' and 'excellent' combined in one 'good' class), and two possible classes (previous 'bad' and 'average' combined in one 'bad' class, and previous 'good' and 'excellent' combined in one 'good' class).</p>
H3K4me1 marks DNA regions hypomethylated during aging in human stem and differentiated cells
<p>In differentiated cells, aging is associated with hypermethylation of DNA regions enriched in repressive histone post-translational modifications. However, the chromatin marks associated with changes in DNA methylation in adult stem cells during lifetime are still largely unknown. Here, DNA methylation profiling of mesenchymal stem cells (MSCs) obtained from individuals aged 2 to 92 yr identified 18,735 hypermethylated and 45,407 hypomethylated CpG sites associated with aging. As in differentiated cells, hypermethylated sequences were enriched in chromatin repressive marks. Most importantly, hypomethylated CpG sites were strongly enriched in the active chromatin mark H3K4me1 in stem and differentiated cells, suggesting this is a cell type-independent chromatin signature of DNA hypomethylation during aging. Analysis of scedasticity showed that interindividual variability of DNA methylation increased during aging in MSCs and differentiated cells, providing a new avenue for the identification of DNA methylation changes over time. DNA methylation profiling of genetically identical individuals showed that both the tendency of DNA methylation changes and scedasticity depended on nongenetic as well as genetic factors. Our results indicate that the dynamics of DNA methylation during aging depend on a complex mixture of factors that include the DNA sequence, cell type, and chromatin context involved and that, depending on the locus, the changes can be modulated by genetic and/or external factors.</p>
Dataset of the study "Open Access and Data Sharing in Cancer Stem Cells research"
<p>Dataset of the study "Open Access and Data Sharing in Cancer Stem Cells research"</p>
RT PCR data for publication Transplantation of neural stem cells improves recovery of stroke affected mice and induces cell-specific changes in GSDMD and MLKL expression
Open the record for dataset details and reuse information.
Annotation for human genomic variation during the BMP4-induced conversion from embryonic stem cells to trophoblast by bone
<p>Whole genomic data of three cell lines were sequenced. These three cell lines are two hESC lines (H1 & H9) by invasion assays and iPSC cell line MRucR. These three cell lines are two hESC lines (H1 & H9) by invasion assays and iPSC cell line MRucR. Paired-end DNA libraries were prepared according to manufacturer’s instructions (Illumina Truseq Library Construction). And then, valid sequencing data is mapped to the reference genome (UCSC hg19) by Burrows-Wheeler Aligner (BWA) software. Reads that aligned to genomic regions were collected for mutation identification and subsequent analysis. Samtools mpileup and bcftools are used to do variant calling and identify SNP, indels. Control-free (Boeva V et al.2012) is utilized to do CNV detection. And BreakDancer (Chen K et al.2009) is applied to detect SV information. And, Single nucleotide variant (SNV) and small somatic insertions and deletions (indels) were identified using Strelka2.</p>
FIGURE 2. Schistidium squarrosum. A. Habit. B. Sterile plant. C. Stem section. D–F. Cauline leaves. G–I. Distal leaf sections. J–K. Cauline leaf apices. L. Median marginal laminal cells. M. Basal laminal cells. N. Medial leaf section. O in Two new species of Schistidium (Grimmiaceae, Bryophyta) from western North America
FIGURE 2. Schistidium squarrosum. A. Habit. B. Sterile plant. C. Stem section. D–F. Cauline leaves. G–I. Distal leaf sections. J–K. Cauline leaf apices. L. Median marginal laminal cells. M. Basal laminal cells. N. Medial leaf section. O. Capsule in perichaetium. P. Perichaetial leaf. Q. Capsule. R. Operculum and calyptra. S. Peristome tooth. Scale bar: 4 mm for A; 3 mm for B; 1 mm for O, Q; 100 μm for C, G–N, S; 0.5 mm for D–F, P–R.
FIGURE 1. Schistidium splendens. A. Habit. B. Fertile plant. C. Stem section. D. Cauline leaf. E–F. Leaf sections. G–H. Cauline leaf apices. I. Median marginal laminal cells. J. Basal laminal cells. K in Two new species of Schistidium (Grimmiaceae, Bryophyta) from western North America
FIGURE 1. Schistidium splendens. A. Habit. B. Fertile plant. C. Stem section. D. Cauline leaf. E–F. Leaf sections. G–H. Cauline leaf apices. I. Median marginal laminal cells. J. Basal laminal cells. K. Capsule in perichaetium. L. Perichaetial leaf. M. Capsule, opercula, dry. N. Capsule, wet. O. Cells at capsule mouth. Scale bar: 4 mm for A; 2 mm for B; 0.75 mm for K, M, N; 100 μm for C, E–J, O; 0.5 mm for D, L.
ONT direct RNA sequencing Fast5 files from mouse embryonic stem cell (C57BL/6J x CAST/EiJ) - Rep1 (run3)
<p>We present a novel approach that leverages Oxford Nanopore direct RNA sequencing technology to detect allele-biased patterns of N6-methyladenosine (m6A) modifications in native mRNAs. Our approach utilized human and mouse cells with known genetic variants to ascertain allelic origin of each mRNA molecule. We employed a supervised machine learning model to detect read-level modification ratios, providing a comprehensive understanding of allele-specific m6A modification (ASM) patterns. To analyze the effects of allele specific m6A modification in mouse, we used hybrid mosue embryonic stem cells (C57BL/6J x CAST/EiJ). This page contains replicate 1 (run 3)</p>
ONT direct RNA sequencing Fast5 files from mouse embryonic stem cell (C57BL/6J x CAST/EiJ) - Rep2 (run1)
<p>We present a novel approach that leverages Oxford Nanopore direct RNA sequencing technology to detect allele-biased patterns of N6-methyladenosine (m6A) modifications in native mRNAs. Our approach utilized human and mouse cells with known genetic variants to ascertain allelic origin of each mRNA molecule. We employed a supervised machine learning model to detect read-level modification ratios, providing a comprehensive understanding of allele-specific m6A modification (ASM) patterns. To analyze the effects of allele specific m6A modification in mouse, we used hybrid mosue embryonic stem cells (C57BL/6J x CAST/EiJ). This page contains replicate 2 (run 1).</p>
ONT direct RNA sequencing Fast5 files from mouse embryonic stem cell (C57BL/6J x CAST/EiJ) Mettl3 Knockout
<p>We present a novel approach that leverages Oxford Nanopore direct RNA sequencing technology to detect allele-biased patterns of N6-methyladenosine (m6A) modifications in native mRNAs. Our approach utilized human and mouse cells with known genetic variants to ascertain allelic origin of each mRNA molecule. We employed a supervised machine learning model to detect read-level modification ratios, providing a comprehensive understanding of allele-specific m6A modification (ASM) patterns. To analyze the effects of allele specific m6A modification in mouse, we used hybrid mosue embryonic stem cells (C57BL/6J x CAST/EiJ). </p>
ONT direct RNA sequencing Fast5 files from mouse embryonic stem cell (C57BL/6J x CAST/EiJ) - Rep2 (run3-1)
<p>We present a novel approach that leverages Oxford Nanopore direct RNA sequencing technology to detect allele-biased patterns of N6-methyladenosine (m6A) modifications in native mRNAs. Our approach utilized human and mouse cells with known genetic variants to ascertain allelic origin of each mRNA molecule. We employed a supervised machine learning model to detect read-level modification ratios, providing a comprehensive understanding of allele-specific m6A modification (ASM) patterns. To analyze the effects of allele specific m6A modification in mouse, we used hybrid mosue embryonic stem cells (C57BL/6J x CAST/EiJ). This page contains replicate 2 (run 3-1; the files are splited two two parts because of limitations of file size).</p>
ONT direct RNA sequencing Fast5 files from mouse embryonic stem cell (C57BL/6J x CAST/EiJ) - Rep2 (run2)
<p>We present a novel approach that leverages Oxford Nanopore direct RNA sequencing technology to detect allele-biased patterns of N6-methyladenosine (m6A) modifications in native mRNAs. Our approach utilized human and mouse cells with known genetic variants to ascertain allelic origin of each mRNA molecule. We employed a supervised machine learning model to detect read-level modification ratios, providing a comprehensive understanding of allele-specific m6A modification (ASM) patterns. To analyze the effects of allele specific m6A modification in mouse, we used hybrid mosue embryonic stem cells (C57BL/6J x CAST/EiJ). This page contains replicate 2 (run 2)</p>
ONT direct RNA sequencing Fast5 files from mouse embryonic stem cell (C57BL/6J x CAST/EiJ) - Rep1 (run2)
<p>We present a novel approach that leverages Oxford Nanopore direct RNA sequencing technology to detect allele-biased patterns of N6-methyladenosine (m6A) modifications in native mRNAs. Our approach utilized human and mouse cells with known genetic variants to ascertain allelic origin of each mRNA molecule. We employed a supervised machine learning model to detect read-level modification ratios, providing a comprehensive understanding of allele-specific m6A modification (ASM) patterns. To analyze the effects of allele specific m6A modification in mouse, we used hybrid mosue embryonic stem cells (C57BL/6J x CAST/EiJ). This page contains replicate 1 (run 2). </p>
ONT direct RNA sequencing Fast5 files from mouse embryonic stem cell (C57BL/6J x CAST/EiJ) - Rep1 (run1 and 4)
<p>We present a novel approach that leverages Oxford Nanopore direct RNA sequencing technology to detect allele-biased patterns of N6-methyladenosine (m6A) modifications in native mRNAs. Our approach utilized human and mouse cells with known genetic variants to ascertain allelic origin of each mRNA molecule. We employed a supervised machine learning model to detect read-level modification ratios, providing a comprehensive understanding of allele-specific m6A modification (ASM) patterns. To analyze the effects of allele specific m6A modification in mouse, we used hybrid mosue embryonic stem cells (C57BL/6J x CAST/EiJ). This page contains replicate 1 (run 1 and 4). </p>
ONT direct RNA sequencing Fast5 files from mouse embryonic stem cell (C57BL/6J x CAST/EiJ) - Rep2 (run3-2)
<p>We present a novel approach that leverages Oxford Nanopore direct RNA sequencing technology to detect allele-biased patterns of N6-methyladenosine (m6A) modifications in native mRNAs. Our approach utilized human and mouse cells with known genetic variants to ascertain allelic origin of each mRNA molecule. We employed a supervised machine learning model to detect read-level modification ratios, providing a comprehensive understanding of allele-specific m6A modification (ASM) patterns. To analyze the effects of allele specific m6A modification in mouse, we used hybrid mosue embryonic stem cells (C57BL/6J x CAST/EiJ). This page contains replicate 2 (run 3-2; the files are splited two two parts because of limitations of file size).</p>
ONT direct RNA sequencing Fast5 files from mouse embryonic stem cell (C57BL/6J x CAST/EiJ) - Rep2 (run4-2)
<p>We present a novel approach that leverages Oxford Nanopore direct RNA sequencing technology to detect allele-biased patterns of N6-methyladenosine (m6A) modifications in native mRNAs. Our approach utilized human and mouse cells with known genetic variants to ascertain allelic origin of each mRNA molecule. We employed a supervised machine learning model to detect read-level modification ratios, providing a comprehensive understanding of allele-specific m6A modification (ASM) patterns. To analyze the effects of allele specific m6A modification in mouse, we used hybrid mosue embryonic stem cells (C57BL/6J x CAST/EiJ). This page contains replicate 2 (run 4-2; the files are splited two two parts because of limitations of file size).</p>
ONT direct RNA sequencing Fast5 files from mouse embryonic stem cell (C57BL/6J x CAST/EiJ) - Rep2 (run4-1)
<p>We present a novel approach that leverages Oxford Nanopore direct RNA sequencing technology to detect allele-biased patterns of N6-methyladenosine (m6A) modifications in native mRNAs. Our approach utilized human and mouse cells with known genetic variants to ascertain allelic origin of each mRNA molecule. We employed a supervised machine learning model to detect read-level modification ratios, providing a comprehensive understanding of allele-specific m6A modification (ASM) patterns. To analyze the effects of allele specific m6A modification in mouse, we used hybrid mosue embryonic stem cells (C57BL/6J x CAST/EiJ). This page contains replicate 2 (run 4-1; the files are splited two two parts because of limitations of file size).</p>
FIGURE 2. Marchesinia principensis. A. Lobes. B. Lobules. C. Underleaves. D. Stem cross section. E. Basal lobe cells. F. Mid-lobe cells. G in Marchesinia principensis (Marchantiophyta, Lejeuneaceae), a new liverwort species from Príncipe, West Africa
FIGURE 2. Marchesinia principensis. A. Lobes. B. Lobules. C. Underleaves. D. Stem cross section. E. Basal lobe cells. F. Mid-lobe cells. G. Cells at lobe apex. H. Stem in ventral view, underleaves are detached. All from Shevock 40260. Photos by F. Müller.
Ice recrystallization inhibitors enable efficient cryopreservation of induced pluripotent stem cells: A functional and transcriptomic analysis
<p><span>The successful use of human induced pluripotent stem cells (iPSCs) for research or clinical applications requires the development of robust, efficient, and reproducible cryopreservation protocols. After cryopreservation, the survival rate of iPSCs is suboptimal and cell line dependent. We assessed the use of ice recrystallization inhibitors (IRIs) for cryopreservation of human iPSCs<span>. A toxicity screening study was performed to assess specific small-molecule carbohydrate-based IRI and concentrations for further evaluation.</span> Then, a cryopreservation study compared the cryoprotective efficiency of 15 mM IRIs in 5 % or 10 % DMSO-containing solutions and with CryoStor® CS10. Three iPSC lines were cryopreserved as single-cell suspensions in the cryopreservation solutions and post-thaw characteristics, including pluripotency and differential gene expression, were assessed. </span><span>W</span><span>e demonstrate the fitness-for-purpose of 15 mM IRI in 5 % DMSO as an efficient cryoprotective solution for iPSCs in terms of post-thaw recovery, viability, pluripotency, and transcriptomic changes. Given that this dataset is the first report where mRNA sequencing has been used to identify expression changes resulting from iPSCs cryopreservation, it has the potential to be used for molecular mechanism analysis relating to cryopreservation. IRIs can reduce DMSO concentrations, thereby improving the utility, effectiveness, and efficiency of cryopreservation. </span></p>
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.