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early mtec  (Japan Tissue Engineering)

 
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    Japan Tissue Engineering early mtec
    Analyses of mTEC subpopulation structure. ( A ) Principal Component Analysis (PCA) of mTECs using all genes. Batches match colour and age of mice matches shapes (left). The PC2 and PC3 loadings of key genes of interest are highlighted (right). ( B ) Hierarchical clustering of 164 transcriptomes of single-cells, based on the top positively and inversely correlated genes with PC2 and PC3. Three clusters of cells were identified (jTEC, mTEChi and mTEClo). Cell cluster, mice age and batch are depicted. ( C ) Expression of selected marker genes in the jTEC, mTEChi, and mTEClo populations. ***p-value < 0.001, **p-value < 0.01, *p-value < 0.05, NS – not significant, according to Mann-Whitney-Wilcoxon test, p-value adjusted using Bonferroni correction. ( D ) Ordering of single cells in pseudotime by degree of <t>maturation</t> using the pseudogp algorithm. Data points represent single cells, colours denoting cell clusters ( B ). ( E ) Ordering of single cells in pseudotime using the Monocle2 algorithm. Data points represent single cells, colours denoting cell clusters ( B ). ( F ) Distribution of single cells of each cluster ( B ) along Monocle2 pseudotime ( E ).
    Early Mtec, supplied by Japan Tissue Engineering, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/early+mtec/early+mtec/pmc05766627-188-9-16
    Average 90 stars, based on 1 article reviews
    early mtec - by Bioz Stars, 2026-08
    90/100 stars

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    1) Product Images from "Single-cell RNA-sequencing resolves self-antigen expression during mTEC development"

    Article Title: Single-cell RNA-sequencing resolves self-antigen expression during mTEC development

    Journal: Scientific Reports

    doi: 10.1038/s41598-017-19100-4

    Analyses of mTEC subpopulation structure. ( A ) Principal Component Analysis (PCA) of mTECs using all genes. Batches match colour and age of mice matches shapes (left). The PC2 and PC3 loadings of key genes of interest are highlighted (right). ( B ) Hierarchical clustering of 164 transcriptomes of single-cells, based on the top positively and inversely correlated genes with PC2 and PC3. Three clusters of cells were identified (jTEC, mTEChi and mTEClo). Cell cluster, mice age and batch are depicted. ( C ) Expression of selected marker genes in the jTEC, mTEChi, and mTEClo populations. ***p-value < 0.001, **p-value < 0.01, *p-value < 0.05, NS – not significant, according to Mann-Whitney-Wilcoxon test, p-value adjusted using Bonferroni correction. ( D ) Ordering of single cells in pseudotime by degree of maturation using the pseudogp algorithm. Data points represent single cells, colours denoting cell clusters ( B ). ( E ) Ordering of single cells in pseudotime using the Monocle2 algorithm. Data points represent single cells, colours denoting cell clusters ( B ). ( F ) Distribution of single cells of each cluster ( B ) along Monocle2 pseudotime ( E ).
    Figure Legend Snippet: Analyses of mTEC subpopulation structure. ( A ) Principal Component Analysis (PCA) of mTECs using all genes. Batches match colour and age of mice matches shapes (left). The PC2 and PC3 loadings of key genes of interest are highlighted (right). ( B ) Hierarchical clustering of 164 transcriptomes of single-cells, based on the top positively and inversely correlated genes with PC2 and PC3. Three clusters of cells were identified (jTEC, mTEChi and mTEClo). Cell cluster, mice age and batch are depicted. ( C ) Expression of selected marker genes in the jTEC, mTEChi, and mTEClo populations. ***p-value < 0.001, **p-value < 0.01, *p-value < 0.05, NS – not significant, according to Mann-Whitney-Wilcoxon test, p-value adjusted using Bonferroni correction. ( D ) Ordering of single cells in pseudotime by degree of maturation using the pseudogp algorithm. Data points represent single cells, colours denoting cell clusters ( B ). ( E ) Ordering of single cells in pseudotime using the Monocle2 algorithm. Data points represent single cells, colours denoting cell clusters ( B ). ( F ) Distribution of single cells of each cluster ( B ) along Monocle2 pseudotime ( E ).

    Techniques Used: Expressing, Marker, MANN-WHITNEY



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    early mtec  (Japan Tissue Engineering)
    90
    Japan Tissue Engineering early mtec
    Analyses of mTEC subpopulation structure. ( A ) Principal Component Analysis (PCA) of mTECs using all genes. Batches match colour and age of mice matches shapes (left). The PC2 and PC3 loadings of key genes of interest are highlighted (right). ( B ) Hierarchical clustering of 164 transcriptomes of single-cells, based on the top positively and inversely correlated genes with PC2 and PC3. Three clusters of cells were identified (jTEC, mTEChi and mTEClo). Cell cluster, mice age and batch are depicted. ( C ) Expression of selected marker genes in the jTEC, mTEChi, and mTEClo populations. ***p-value < 0.001, **p-value < 0.01, *p-value < 0.05, NS – not significant, according to Mann-Whitney-Wilcoxon test, p-value adjusted using Bonferroni correction. ( D ) Ordering of single cells in pseudotime by degree of <t>maturation</t> using the pseudogp algorithm. Data points represent single cells, colours denoting cell clusters ( B ). ( E ) Ordering of single cells in pseudotime using the Monocle2 algorithm. Data points represent single cells, colours denoting cell clusters ( B ). ( F ) Distribution of single cells of each cluster ( B ) along Monocle2 pseudotime ( E ).
    Early Mtec, supplied by Japan Tissue Engineering, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/early+mtec/early+mtec/pmc05766627-188-9-16
    Average 90 stars, based on 1 article reviews
    early mtec - by Bioz Stars, 2026-08
    90/100 stars
    		  Buy from Supplier

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    Analyses of mTEC subpopulation structure. ( A ) Principal Component Analysis (PCA) of mTECs using all genes. Batches match colour and age of mice matches shapes (left). The PC2 and PC3 loadings of key genes of interest are highlighted (right). ( B ) Hierarchical clustering of 164 transcriptomes of single-cells, based on the top positively and inversely correlated genes with PC2 and PC3. Three clusters of cells were identified (jTEC, mTEChi and mTEClo). Cell cluster, mice age and batch are depicted. ( C ) Expression of selected marker genes in the jTEC, mTEChi, and mTEClo populations. ***p-value < 0.001, **p-value < 0.01, *p-value < 0.05, NS – not significant, according to Mann-Whitney-Wilcoxon test, p-value adjusted using Bonferroni correction. ( D ) Ordering of single cells in pseudotime by degree of maturation using the pseudogp algorithm. Data points represent single cells, colours denoting cell clusters ( B ). ( E ) Ordering of single cells in pseudotime using the Monocle2 algorithm. Data points represent single cells, colours denoting cell clusters ( B ). ( F ) Distribution of single cells of each cluster ( B ) along Monocle2 pseudotime ( E ).

    Journal: Scientific Reports

    Article Title: Single-cell RNA-sequencing resolves self-antigen expression during mTEC development

    doi: 10.1038/s41598-017-19100-4

    Figure Lengend Snippet: Analyses of mTEC subpopulation structure. ( A ) Principal Component Analysis (PCA) of mTECs using all genes. Batches match colour and age of mice matches shapes (left). The PC2 and PC3 loadings of key genes of interest are highlighted (right). ( B ) Hierarchical clustering of 164 transcriptomes of single-cells, based on the top positively and inversely correlated genes with PC2 and PC3. Three clusters of cells were identified (jTEC, mTEChi and mTEClo). Cell cluster, mice age and batch are depicted. ( C ) Expression of selected marker genes in the jTEC, mTEChi, and mTEClo populations. ***p-value < 0.001, **p-value < 0.01, *p-value < 0.05, NS – not significant, according to Mann-Whitney-Wilcoxon test, p-value adjusted using Bonferroni correction. ( D ) Ordering of single cells in pseudotime by degree of maturation using the pseudogp algorithm. Data points represent single cells, colours denoting cell clusters ( B ). ( E ) Ordering of single cells in pseudotime using the Monocle2 algorithm. Data points represent single cells, colours denoting cell clusters ( B ). ( F ) Distribution of single cells of each cluster ( B ) along Monocle2 pseudotime ( E ).

    Article Snippet: With this methodology, we identified three distinct stages of maturation: early mTEC in the cortex-medulla junction (jTEC), Aire -expressing mTECs (mTEChi), and mTECs entering the post- Aire stage (mTEClo) , .

    Techniques: Expressing, Marker, MANN-WHITNEY