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ventricular cardiomyocyte kit  (Axol Bioscience)


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    Structured Review

    Axol Bioscience ventricular cardiomyocyte kit
    KO schematic in <t>cardiomyocytes</t> B-D: Oxygen consumption rate (OCR) is significantly increased in siSMN-treated cardiomyocytes compared with siScramble controls and extracellular acidification rate (ECAR) is significantly decreased in siSMN-treated cardiomyocytes. n = 16 technical replicates. * p <0.05. **p < 0.01. Mitochondrial and glycolytic ATP production rates show no significant difference between siSMN and siScramble conditions (ns). E: Volcano plot of differential gene expression following SMN knockdown. F: Heatmap and hierarchical clustering of differentially expressed genes demonstrate distinct transcriptional profiles between siSMN and siScramble cardiomyocytes. G: Pathway enrichment analysis of differentially expressed genes identifies significant perturbation of multiple signaling pathways, including enrichment of PTEN signaling.
    Ventricular Cardiomyocyte Kit, supplied by Axol Bioscience, used in various techniques. Bioz Stars score: 94/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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    Images

    1) Product Images from "Cardiac defects in spinal muscular atrophy and the role of SMN in cardiomyocyte homeostasis"

    Article Title: Cardiac defects in spinal muscular atrophy and the role of SMN in cardiomyocyte homeostasis

    Journal: bioRxiv

    doi: 10.64898/2026.03.20.713246

    KO schematic in cardiomyocytes B-D: Oxygen consumption rate (OCR) is significantly increased in siSMN-treated cardiomyocytes compared with siScramble controls and extracellular acidification rate (ECAR) is significantly decreased in siSMN-treated cardiomyocytes. n = 16 technical replicates. * p <0.05. **p < 0.01. Mitochondrial and glycolytic ATP production rates show no significant difference between siSMN and siScramble conditions (ns). E: Volcano plot of differential gene expression following SMN knockdown. F: Heatmap and hierarchical clustering of differentially expressed genes demonstrate distinct transcriptional profiles between siSMN and siScramble cardiomyocytes. G: Pathway enrichment analysis of differentially expressed genes identifies significant perturbation of multiple signaling pathways, including enrichment of PTEN signaling.
    Figure Legend Snippet: KO schematic in cardiomyocytes B-D: Oxygen consumption rate (OCR) is significantly increased in siSMN-treated cardiomyocytes compared with siScramble controls and extracellular acidification rate (ECAR) is significantly decreased in siSMN-treated cardiomyocytes. n = 16 technical replicates. * p <0.05. **p < 0.01. Mitochondrial and glycolytic ATP production rates show no significant difference between siSMN and siScramble conditions (ns). E: Volcano plot of differential gene expression following SMN knockdown. F: Heatmap and hierarchical clustering of differentially expressed genes demonstrate distinct transcriptional profiles between siSMN and siScramble cardiomyocytes. G: Pathway enrichment analysis of differentially expressed genes identifies significant perturbation of multiple signaling pathways, including enrichment of PTEN signaling.

    Techniques Used: Gene Expression, Knockdown, Protein-Protein interactions

    Ingenuity pathway analysis of differentially expressed genes after SMN2 knockdown in human cardiomyocytes, showing the top 20 significantly enriched canonical pathways ranked by –log(p value). Bar color denotes predicted directionality based on z-score: black indicates negative z-score (predicted pathway inhibition), red indicates positive z-score (predicted pathway activation), and gray indicates no consistent activation pattern.
    Figure Legend Snippet: Ingenuity pathway analysis of differentially expressed genes after SMN2 knockdown in human cardiomyocytes, showing the top 20 significantly enriched canonical pathways ranked by –log(p value). Bar color denotes predicted directionality based on z-score: black indicates negative z-score (predicted pathway inhibition), red indicates positive z-score (predicted pathway activation), and gray indicates no consistent activation pattern.

    Techniques Used: Knockdown, Inhibition, Activation Assay



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    KO schematic in <t>cardiomyocytes</t> B-D: Oxygen consumption rate (OCR) is significantly increased in siSMN-treated cardiomyocytes compared with siScramble controls and extracellular acidification rate (ECAR) is significantly decreased in siSMN-treated cardiomyocytes. n = 16 technical replicates. * p <0.05. **p < 0.01. Mitochondrial and glycolytic ATP production rates show no significant difference between siSMN and siScramble conditions (ns). E: Volcano plot of differential gene expression following SMN knockdown. F: Heatmap and hierarchical clustering of differentially expressed genes demonstrate distinct transcriptional profiles between siSMN and siScramble cardiomyocytes. G: Pathway enrichment analysis of differentially expressed genes identifies significant perturbation of multiple signaling pathways, including enrichment of PTEN signaling.
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    A Gene Set Enrichment Analysis (GSEA) of RNA-seq data showing the transcriptional perturbations induced by H3L on cardiac genes in hESCs. RNA-seq data was from Fig. . B RNA-seq analysis of cardiac lineage cells on day 3 (d3) of differentiation. Two biological replicates were applied. DEGs, differentially expressed genes. C Volcano plots showing differentially expressed genes (DEGs) induced by H3L. P < 0.05 and |log 2 (fold change) | > 0 were set as the threshold for DEGs. D Gene Ontology (GO) analysis of downregulated genes induced by H3L. E Heatmap showing H3L-downregulated genes involved in heart morphogenesis and cardiac development. FC, fold change. F RT-qPCR showing gene expression changes in cardiac lineage cells of day 3. *p < 0.05 (vs. Control). G Immunostaining of TBXT + cells in cardiac lineage cells of day 3. Green showed TBXT. Blue showed DAPI. Scale bar, 100 µm. H Flow cytometry quantification of TBXT + cells in cardiac lineage cells of day 3 from ( G ). *p < 0.05 (vs. Control). I Immunostaining of TNNT2 + cells in cardiac lineage cells of day 7. Red showed TNNT2. Blue showed DAPI. Scale bar, 200 µm. J Flow cytometry quantification of TNNT2 + cells in cardiac lineage cells of day 7 from ( I ). *p < 0.05 (vs. Control). K Flow cytometry quantification of TBXT + cells in cardiac lineage cells of day 3. IL1A was added from day 0 to day 3 during cardiac differentiation. IL1A final concentration was 0.5 ng/ml. *p < 0.05 (vs. 0 ng/ml Control). L Flow cytometry quantification of TNNT2 + cells in cardiac lineage cells of day 7. IL1A was added from day 0 to day 7 during cardiac differentiation. IL1A final concentration was 0.5 ng/ml. *p < 0.05 (vs. 0 ng/ml Control). M RT-qPCR showing relative expression of cardiogenic genes in cardiac lineage cells of day 7. IL1A was added from day 0 to day 7 during cardiac differentiation. IL1A final concentration was 0.5 ng/ml. Control, no IL1A. *p < 0.05 (vs. Control). N Gene Ontology (GO) analysis of upregulated genes induced by H3L. O GSEA analysis showing senescence and DNA damage signaling pathways. P Immunostaining of γ-H2AX + cells in cardiac lineage cells of day 3. Red showed γ-H2AX. Blue showed DAPI. Scale bar, 200 µm. Q Flow cytometry quantification of γ-H2AX + cells in cardiac lineage cells of day 3 from ( P ). *p < 0.05 (vs. Control) ( R ) Immunostaining of TUNEL + cells in cardiac lineage cells of day 3. Green showed TUNEL. Blue showed DAPI. Scale bar, 200 µm. S Flow cytometry quantification of TUNEL + cells in cardiac lineage cells of day 3. *p < 0.05 (vs. Control). T Human <t>cardiomyocytes</t> derived from hESCs were infected with lentiviruses to overexpress H3L, followed with quantification of γ-H2AX + and TUNEL + cells on 48 h later. Blank virus infection was used as Control. Flow cytometry quantification of γ-H2AX + ( U ) and TUNEL + ( V ) cardiomyocytes. *p < 0.05 (vs. Control). W H3L induces cellular injuries in human cardiac lineages via IL1A.
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    Image Search Results


    KO schematic in cardiomyocytes B-D: Oxygen consumption rate (OCR) is significantly increased in siSMN-treated cardiomyocytes compared with siScramble controls and extracellular acidification rate (ECAR) is significantly decreased in siSMN-treated cardiomyocytes. n = 16 technical replicates. * p <0.05. **p < 0.01. Mitochondrial and glycolytic ATP production rates show no significant difference between siSMN and siScramble conditions (ns). E: Volcano plot of differential gene expression following SMN knockdown. F: Heatmap and hierarchical clustering of differentially expressed genes demonstrate distinct transcriptional profiles between siSMN and siScramble cardiomyocytes. G: Pathway enrichment analysis of differentially expressed genes identifies significant perturbation of multiple signaling pathways, including enrichment of PTEN signaling.

    Journal: bioRxiv

    Article Title: Cardiac defects in spinal muscular atrophy and the role of SMN in cardiomyocyte homeostasis

    doi: 10.64898/2026.03.20.713246

    Figure Lengend Snippet: KO schematic in cardiomyocytes B-D: Oxygen consumption rate (OCR) is significantly increased in siSMN-treated cardiomyocytes compared with siScramble controls and extracellular acidification rate (ECAR) is significantly decreased in siSMN-treated cardiomyocytes. n = 16 technical replicates. * p <0.05. **p < 0.01. Mitochondrial and glycolytic ATP production rates show no significant difference between siSMN and siScramble conditions (ns). E: Volcano plot of differential gene expression following SMN knockdown. F: Heatmap and hierarchical clustering of differentially expressed genes demonstrate distinct transcriptional profiles between siSMN and siScramble cardiomyocytes. G: Pathway enrichment analysis of differentially expressed genes identifies significant perturbation of multiple signaling pathways, including enrichment of PTEN signaling.

    Article Snippet: Human cardiomyocytes (Axol Bioscience Limited, Cambridgeshire, England; Cat. No. ax2520; Lot No. 2520310317) were cultured and differentiated in coated plates using supplemented media from the Human iPSC-Derived Ventricular Cardiomyocyte Kit (Axol Bioscience Limited, Cambridgeshire, England).

    Techniques: Gene Expression, Knockdown, Protein-Protein interactions

    Ingenuity pathway analysis of differentially expressed genes after SMN2 knockdown in human cardiomyocytes, showing the top 20 significantly enriched canonical pathways ranked by –log(p value). Bar color denotes predicted directionality based on z-score: black indicates negative z-score (predicted pathway inhibition), red indicates positive z-score (predicted pathway activation), and gray indicates no consistent activation pattern.

    Journal: bioRxiv

    Article Title: Cardiac defects in spinal muscular atrophy and the role of SMN in cardiomyocyte homeostasis

    doi: 10.64898/2026.03.20.713246

    Figure Lengend Snippet: Ingenuity pathway analysis of differentially expressed genes after SMN2 knockdown in human cardiomyocytes, showing the top 20 significantly enriched canonical pathways ranked by –log(p value). Bar color denotes predicted directionality based on z-score: black indicates negative z-score (predicted pathway inhibition), red indicates positive z-score (predicted pathway activation), and gray indicates no consistent activation pattern.

    Article Snippet: Human cardiomyocytes (Axol Bioscience Limited, Cambridgeshire, England; Cat. No. ax2520; Lot No. 2520310317) were cultured and differentiated in coated plates using supplemented media from the Human iPSC-Derived Ventricular Cardiomyocyte Kit (Axol Bioscience Limited, Cambridgeshire, England).

    Techniques: Knockdown, Inhibition, Activation Assay

    A Similarities of the molecular descriptions of HF between pairs of bulk or single-nucleus (SN) transcriptomics studies were approximated with the performance of disease classifiers built with each study of our core curation. The disease classifier from bulk studies used the changes in expression of each gene, while the classifiers of SN-studies were built with cell-type compositions or multicellular programs. B Area under the receiver operating characteristic curve (AUROC) of pairwise predictions of disease classifiers built from all individual bulk studies included in our core collection using the top 500 differentially expressed genes. Red labels mark the study expansion. C Gene ranking of conservation of gene deregulation events in HF across bulk transcriptomics studies based on the adjusted p value of a Fisher combined analysis. The dotted line shows the top-500 genes. D Hierarchical clustering of all SN-transcriptomics tissue samples based on the composition of the seven major cell-types used in our ontology. E T-statistics (heatmap) and estimate of difference between failing and non-failing hearts from the differential compositional analysis using t-tests and linear mixed models, respectively. Stars denote an adj. p value < 0.05. F AUROC of pairwise predictions from disease classifiers built from all core SN studies using cell-type compositions. G Uniform Manifold Approximation and Projections (UMAP) of the multicellular programs describing the variability of the respective tissue samples of each core SN study. Tissue samples of the rest of the studies are projected into each latent space and distinguished with the shape of the dot. Colors highlight different HF etiologies. All plots include 132 patients. H AUROC of pairwise predictions from disease classifiers built from all core SN-studies using multicellular programs. In all panels Cardiomyocytes (CM), fibroblasts (Fib), pericytes, endothelial (Endo), and vascular smooth muscle (vSMCs) cells. Heart failure (HF), and non-failing (NF) hearts. Source data are provided as a Source Data file.

    Journal: Nature Communications

    Article Title: A cross-study transcriptional patient map of heart failure defines conserved multicellular coordination in cardiac remodeling

    doi: 10.1038/s41467-025-62219-6

    Figure Lengend Snippet: A Similarities of the molecular descriptions of HF between pairs of bulk or single-nucleus (SN) transcriptomics studies were approximated with the performance of disease classifiers built with each study of our core curation. The disease classifier from bulk studies used the changes in expression of each gene, while the classifiers of SN-studies were built with cell-type compositions or multicellular programs. B Area under the receiver operating characteristic curve (AUROC) of pairwise predictions of disease classifiers built from all individual bulk studies included in our core collection using the top 500 differentially expressed genes. Red labels mark the study expansion. C Gene ranking of conservation of gene deregulation events in HF across bulk transcriptomics studies based on the adjusted p value of a Fisher combined analysis. The dotted line shows the top-500 genes. D Hierarchical clustering of all SN-transcriptomics tissue samples based on the composition of the seven major cell-types used in our ontology. E T-statistics (heatmap) and estimate of difference between failing and non-failing hearts from the differential compositional analysis using t-tests and linear mixed models, respectively. Stars denote an adj. p value < 0.05. F AUROC of pairwise predictions from disease classifiers built from all core SN studies using cell-type compositions. G Uniform Manifold Approximation and Projections (UMAP) of the multicellular programs describing the variability of the respective tissue samples of each core SN study. Tissue samples of the rest of the studies are projected into each latent space and distinguished with the shape of the dot. Colors highlight different HF etiologies. All plots include 132 patients. H AUROC of pairwise predictions from disease classifiers built from all core SN-studies using multicellular programs. In all panels Cardiomyocytes (CM), fibroblasts (Fib), pericytes, endothelial (Endo), and vascular smooth muscle (vSMCs) cells. Heart failure (HF), and non-failing (NF) hearts. Source data are provided as a Source Data file.

    Article Snippet: Neonatal rat ventricular cardiomyocytes (NRVCMs) were isolated from 1- to 2-day-old Sprague-Dawley rat pups using a modified protocol adapted from Miltenyi Biotec’s Neonatal Heart Dissociation Kit (mouse/rat, 130-098-373) and Neonatal Cardiomyocyte Isolation Kit (rat, 130-105-420).

    Techniques: Expressing

    A Multicellular factor analysis was used to integrate the patients' profiles across the single-nucleus core studies. The integrative model represents each sample in terms of latent variables, referred here as multicellular programs (MCP), that capture gene expression variability across cell types, patients, and studies. Each MCP can be understood as a collection of genes whose expression is coordinated across cell types. B Patient map built from MCP1 and MCP2 with samples ( n = 132) colored by their disease status, etiology, and study of origin. C Mean standardized gene expression of the top 5 genes in MCP1 whose expression was captured in all studies. Data were grouped by disease status and study of origin. D Functional dissection of the patient map built from MCP1 and MCP2 from a multicellular (left) or cell-type (right) perspective. Each functional vector represents the level of enrichment of a function in the location of the map where the arrow points to. The larger the arrow, the more enriched the function. Gene sets were manually selected for representation from a set of gene sets enriched in either MCP1 and/or MCP2 (adj. two-sided p value < 0.1, hypergeometric test). E Multicellular coordination network of HF processes captured by MCP1, where each arrow describes how important the expression of a given cell-type is to predict the expression profile of another one (Methods). Predictive importances come from linear mixed models of cell-type signatures of MCP1. Importances below 0.2 were not included. F Association between the predictive importance of a pair of cell-types (sender and target) and the number of potential ligand-receptor coexpression events. Pairs of cells are colored by their target cell-type and highlighted when fibroblasts (Fibs) are the sender cell-type. Pearson’s correlation coefficient and its p value is displayed. G Regulatory potential score, as estimated by NicheNet, represents the potential of fibroblasts’ ligands in contributing to the regulation of cardiomyocyte genes (MCP1 gene loading < −0.2). In all panels, Cardiomyocytes (CM), fibroblasts (Fib), pericytes (PC), endothelial (Endo), vascular smooth muscle (vSMCs) cells. Heart failure (HF), and non-failing (NF) hearts. Source data are provided as a Source Data file.

    Journal: Nature Communications

    Article Title: A cross-study transcriptional patient map of heart failure defines conserved multicellular coordination in cardiac remodeling

    doi: 10.1038/s41467-025-62219-6

    Figure Lengend Snippet: A Multicellular factor analysis was used to integrate the patients' profiles across the single-nucleus core studies. The integrative model represents each sample in terms of latent variables, referred here as multicellular programs (MCP), that capture gene expression variability across cell types, patients, and studies. Each MCP can be understood as a collection of genes whose expression is coordinated across cell types. B Patient map built from MCP1 and MCP2 with samples ( n = 132) colored by their disease status, etiology, and study of origin. C Mean standardized gene expression of the top 5 genes in MCP1 whose expression was captured in all studies. Data were grouped by disease status and study of origin. D Functional dissection of the patient map built from MCP1 and MCP2 from a multicellular (left) or cell-type (right) perspective. Each functional vector represents the level of enrichment of a function in the location of the map where the arrow points to. The larger the arrow, the more enriched the function. Gene sets were manually selected for representation from a set of gene sets enriched in either MCP1 and/or MCP2 (adj. two-sided p value < 0.1, hypergeometric test). E Multicellular coordination network of HF processes captured by MCP1, where each arrow describes how important the expression of a given cell-type is to predict the expression profile of another one (Methods). Predictive importances come from linear mixed models of cell-type signatures of MCP1. Importances below 0.2 were not included. F Association between the predictive importance of a pair of cell-types (sender and target) and the number of potential ligand-receptor coexpression events. Pairs of cells are colored by their target cell-type and highlighted when fibroblasts (Fibs) are the sender cell-type. Pearson’s correlation coefficient and its p value is displayed. G Regulatory potential score, as estimated by NicheNet, represents the potential of fibroblasts’ ligands in contributing to the regulation of cardiomyocyte genes (MCP1 gene loading < −0.2). In all panels, Cardiomyocytes (CM), fibroblasts (Fib), pericytes (PC), endothelial (Endo), vascular smooth muscle (vSMCs) cells. Heart failure (HF), and non-failing (NF) hearts. Source data are provided as a Source Data file.

    Article Snippet: Neonatal rat ventricular cardiomyocytes (NRVCMs) were isolated from 1- to 2-day-old Sprague-Dawley rat pups using a modified protocol adapted from Miltenyi Biotec’s Neonatal Heart Dissociation Kit (mouse/rat, 130-098-373) and Neonatal Cardiomyocyte Isolation Kit (rat, 130-105-420).

    Techniques: Gene Expression, Expressing, Functional Assay, Dissection, Plasmid Preparation

    A Cell-type specific transcriptional processes associated with MCP1 and MCP2 are enriched in every patient tissue sample from the bulk core study collection ( n = 1392). Upper panels show AUROC distributions ( n = 21) evaluating how well cell-type-specific responses classify non-failing hearts in each study. B Schematic of potential tissue-level regulatory mechanisms underlying observed gene expression changes in bulk data. Upregulation in HF may reflect increased abundance of cell types expressing the gene (Compositional regulation, Comp.), increased gene expression within cells (Molecular, Mol.), or both (Comp/Mol). Downregulation follows similar principles. C Consensus gene-level statistics of HF-associated expression changes from bulk ( x axis) and compositional (upper) or molecular (lower) regulation from single-nucleus data ( y axis). Genes shown are from the top 8942 in the consensus bulk ranking (adj. Fisher p value < 0.05) (Fig. ). D Annotation of deregulation events derived from the combination of bulk and single-nucleus transcriptomics studies. The annotation comes from the top 8942 genes of the consensus ranking (adj. two-sided Fisher p value < 0.05). E Root mean square error and Pearson correlation of pseudobulk deconvolution results (core and supporting single-nucleus data). Each dot is one dataset, stratified by tissue type (HF, n = 10; NF, n = 8) and signature gene set used ( x axis). Unreg, unregulated; dereg, deregulated; dereg mol, molecularly deregulated; dereg comp, compositionally deregulated. Two-sided paired Wilcoxon test. F Hierarchical clustering of bulk RNA-seq samples (N = 697) based on deconvoluted composition using a healthy reference (subset to compositionally regulated genes and seven major cell types). G Heatmap of t -statistics and estimated differences between HF and NF hearts from differential compositional analysis using t tests and linear mixed models. Stars: adj. two-sided p value < 0.05. In all panels cardiomyocytes (CM), fibroblasts (Fib), pericytes (PC), endothelial (Endo), vascular smooth muscle (vSMCs) cells. Heart failure (HF), and non-failing (NF) hearts. Boxplots in ( A , E ) display the minimum, first quartile (Q1), median, third quartile (Q3), and maximum; outliers lie beyond 1.5 times the interquartile range (IQR) from Q1 or Q3 and are shown as points. Source data are provided as a Source Data file.

    Journal: Nature Communications

    Article Title: A cross-study transcriptional patient map of heart failure defines conserved multicellular coordination in cardiac remodeling

    doi: 10.1038/s41467-025-62219-6

    Figure Lengend Snippet: A Cell-type specific transcriptional processes associated with MCP1 and MCP2 are enriched in every patient tissue sample from the bulk core study collection ( n = 1392). Upper panels show AUROC distributions ( n = 21) evaluating how well cell-type-specific responses classify non-failing hearts in each study. B Schematic of potential tissue-level regulatory mechanisms underlying observed gene expression changes in bulk data. Upregulation in HF may reflect increased abundance of cell types expressing the gene (Compositional regulation, Comp.), increased gene expression within cells (Molecular, Mol.), or both (Comp/Mol). Downregulation follows similar principles. C Consensus gene-level statistics of HF-associated expression changes from bulk ( x axis) and compositional (upper) or molecular (lower) regulation from single-nucleus data ( y axis). Genes shown are from the top 8942 in the consensus bulk ranking (adj. Fisher p value < 0.05) (Fig. ). D Annotation of deregulation events derived from the combination of bulk and single-nucleus transcriptomics studies. The annotation comes from the top 8942 genes of the consensus ranking (adj. two-sided Fisher p value < 0.05). E Root mean square error and Pearson correlation of pseudobulk deconvolution results (core and supporting single-nucleus data). Each dot is one dataset, stratified by tissue type (HF, n = 10; NF, n = 8) and signature gene set used ( x axis). Unreg, unregulated; dereg, deregulated; dereg mol, molecularly deregulated; dereg comp, compositionally deregulated. Two-sided paired Wilcoxon test. F Hierarchical clustering of bulk RNA-seq samples (N = 697) based on deconvoluted composition using a healthy reference (subset to compositionally regulated genes and seven major cell types). G Heatmap of t -statistics and estimated differences between HF and NF hearts from differential compositional analysis using t tests and linear mixed models. Stars: adj. two-sided p value < 0.05. In all panels cardiomyocytes (CM), fibroblasts (Fib), pericytes (PC), endothelial (Endo), vascular smooth muscle (vSMCs) cells. Heart failure (HF), and non-failing (NF) hearts. Boxplots in ( A , E ) display the minimum, first quartile (Q1), median, third quartile (Q3), and maximum; outliers lie beyond 1.5 times the interquartile range (IQR) from Q1 or Q3 and are shown as points. Source data are provided as a Source Data file.

    Article Snippet: Neonatal rat ventricular cardiomyocytes (NRVCMs) were isolated from 1- to 2-day-old Sprague-Dawley rat pups using a modified protocol adapted from Miltenyi Biotec’s Neonatal Heart Dissociation Kit (mouse/rat, 130-098-373) and Neonatal Cardiomyocyte Isolation Kit (rat, 130-105-420).

    Techniques: Gene Expression, Expressing, Derivative Assay, RNA Sequencing

    A Gene Set Enrichment Analysis (GSEA) of RNA-seq data showing the transcriptional perturbations induced by H3L on cardiac genes in hESCs. RNA-seq data was from Fig. . B RNA-seq analysis of cardiac lineage cells on day 3 (d3) of differentiation. Two biological replicates were applied. DEGs, differentially expressed genes. C Volcano plots showing differentially expressed genes (DEGs) induced by H3L. P < 0.05 and |log 2 (fold change) | > 0 were set as the threshold for DEGs. D Gene Ontology (GO) analysis of downregulated genes induced by H3L. E Heatmap showing H3L-downregulated genes involved in heart morphogenesis and cardiac development. FC, fold change. F RT-qPCR showing gene expression changes in cardiac lineage cells of day 3. *p < 0.05 (vs. Control). G Immunostaining of TBXT + cells in cardiac lineage cells of day 3. Green showed TBXT. Blue showed DAPI. Scale bar, 100 µm. H Flow cytometry quantification of TBXT + cells in cardiac lineage cells of day 3 from ( G ). *p < 0.05 (vs. Control). I Immunostaining of TNNT2 + cells in cardiac lineage cells of day 7. Red showed TNNT2. Blue showed DAPI. Scale bar, 200 µm. J Flow cytometry quantification of TNNT2 + cells in cardiac lineage cells of day 7 from ( I ). *p < 0.05 (vs. Control). K Flow cytometry quantification of TBXT + cells in cardiac lineage cells of day 3. IL1A was added from day 0 to day 3 during cardiac differentiation. IL1A final concentration was 0.5 ng/ml. *p < 0.05 (vs. 0 ng/ml Control). L Flow cytometry quantification of TNNT2 + cells in cardiac lineage cells of day 7. IL1A was added from day 0 to day 7 during cardiac differentiation. IL1A final concentration was 0.5 ng/ml. *p < 0.05 (vs. 0 ng/ml Control). M RT-qPCR showing relative expression of cardiogenic genes in cardiac lineage cells of day 7. IL1A was added from day 0 to day 7 during cardiac differentiation. IL1A final concentration was 0.5 ng/ml. Control, no IL1A. *p < 0.05 (vs. Control). N Gene Ontology (GO) analysis of upregulated genes induced by H3L. O GSEA analysis showing senescence and DNA damage signaling pathways. P Immunostaining of γ-H2AX + cells in cardiac lineage cells of day 3. Red showed γ-H2AX. Blue showed DAPI. Scale bar, 200 µm. Q Flow cytometry quantification of γ-H2AX + cells in cardiac lineage cells of day 3 from ( P ). *p < 0.05 (vs. Control) ( R ) Immunostaining of TUNEL + cells in cardiac lineage cells of day 3. Green showed TUNEL. Blue showed DAPI. Scale bar, 200 µm. S Flow cytometry quantification of TUNEL + cells in cardiac lineage cells of day 3. *p < 0.05 (vs. Control). T Human cardiomyocytes derived from hESCs were infected with lentiviruses to overexpress H3L, followed with quantification of γ-H2AX + and TUNEL + cells on 48 h later. Blank virus infection was used as Control. Flow cytometry quantification of γ-H2AX + ( U ) and TUNEL + ( V ) cardiomyocytes. *p < 0.05 (vs. Control). W H3L induces cellular injuries in human cardiac lineages via IL1A.

    Journal: Cell Death & Disease

    Article Title: Monkeypox virus protein H3L induces injuries in human and mouse

    doi: 10.1038/s41419-024-06990-2

    Figure Lengend Snippet: A Gene Set Enrichment Analysis (GSEA) of RNA-seq data showing the transcriptional perturbations induced by H3L on cardiac genes in hESCs. RNA-seq data was from Fig. . B RNA-seq analysis of cardiac lineage cells on day 3 (d3) of differentiation. Two biological replicates were applied. DEGs, differentially expressed genes. C Volcano plots showing differentially expressed genes (DEGs) induced by H3L. P < 0.05 and |log 2 (fold change) | > 0 were set as the threshold for DEGs. D Gene Ontology (GO) analysis of downregulated genes induced by H3L. E Heatmap showing H3L-downregulated genes involved in heart morphogenesis and cardiac development. FC, fold change. F RT-qPCR showing gene expression changes in cardiac lineage cells of day 3. *p < 0.05 (vs. Control). G Immunostaining of TBXT + cells in cardiac lineage cells of day 3. Green showed TBXT. Blue showed DAPI. Scale bar, 100 µm. H Flow cytometry quantification of TBXT + cells in cardiac lineage cells of day 3 from ( G ). *p < 0.05 (vs. Control). I Immunostaining of TNNT2 + cells in cardiac lineage cells of day 7. Red showed TNNT2. Blue showed DAPI. Scale bar, 200 µm. J Flow cytometry quantification of TNNT2 + cells in cardiac lineage cells of day 7 from ( I ). *p < 0.05 (vs. Control). K Flow cytometry quantification of TBXT + cells in cardiac lineage cells of day 3. IL1A was added from day 0 to day 3 during cardiac differentiation. IL1A final concentration was 0.5 ng/ml. *p < 0.05 (vs. 0 ng/ml Control). L Flow cytometry quantification of TNNT2 + cells in cardiac lineage cells of day 7. IL1A was added from day 0 to day 7 during cardiac differentiation. IL1A final concentration was 0.5 ng/ml. *p < 0.05 (vs. 0 ng/ml Control). M RT-qPCR showing relative expression of cardiogenic genes in cardiac lineage cells of day 7. IL1A was added from day 0 to day 7 during cardiac differentiation. IL1A final concentration was 0.5 ng/ml. Control, no IL1A. *p < 0.05 (vs. Control). N Gene Ontology (GO) analysis of upregulated genes induced by H3L. O GSEA analysis showing senescence and DNA damage signaling pathways. P Immunostaining of γ-H2AX + cells in cardiac lineage cells of day 3. Red showed γ-H2AX. Blue showed DAPI. Scale bar, 200 µm. Q Flow cytometry quantification of γ-H2AX + cells in cardiac lineage cells of day 3 from ( P ). *p < 0.05 (vs. Control) ( R ) Immunostaining of TUNEL + cells in cardiac lineage cells of day 3. Green showed TUNEL. Blue showed DAPI. Scale bar, 200 µm. S Flow cytometry quantification of TUNEL + cells in cardiac lineage cells of day 3. *p < 0.05 (vs. Control). T Human cardiomyocytes derived from hESCs were infected with lentiviruses to overexpress H3L, followed with quantification of γ-H2AX + and TUNEL + cells on 48 h later. Blank virus infection was used as Control. Flow cytometry quantification of γ-H2AX + ( U ) and TUNEL + ( V ) cardiomyocytes. *p < 0.05 (vs. Control). W H3L induces cellular injuries in human cardiac lineages via IL1A.

    Article Snippet: Cardiac differentiation was induced by STEMdiffTM Ventricular Cardiomyocyte Differentiation Kit (STEMCELL Technologies) according to the manual.

    Techniques: RNA Sequencing, Quantitative RT-PCR, Gene Expression, Control, Immunostaining, Flow Cytometry, Concentration Assay, Expressing, Protein-Protein interactions, TUNEL Assay, Derivative Assay, Infection, Virus

    A Scheme of in vivo mouse model to study the effects of H3L in heart. Lentiviruses with control and H3L OE were intraperitoneally injected into one month old mouse. Two months later, heart tissues were collected for bulk RNA-seq. B ELISA assay showing protein expression level of IL1A in blood plasma from mouse heart. *p < 0.05 (vs. Control). Relative level in the Y-axis meant the read count on the absorption at 450 nm by the equipment. C Principal component analysis (PCA) of RNA-seq on mouse heart tissues. Three biological replicates were applied for RNA-seq. D Volcano plots showing differentially expressed genes (DEGs) in heart tissues induced by H3L. P < 0.05 and | log 2 (fold change) | > 0 were set as the threshold for DEGs. E Signaling pathway analysis of differentially expressed genes induced by H3L. The top 20 of highest ranked GO terms were presented. Pathway analysis was run on Reactome. Padj, adjusted p value. F Heatmap showing differentially expressed genes (DEGs) induced by H3L, which were involved in the Citric acid cycle and Respiratory electron transport. G Evaluation of ATP amount in mouse neonatal cardiomyocytes overexpressed with control lentivirus (Control) or H3L lentivirus (H3L OE ). *p < 0.05 (vs. Control). Heatmap showing differentially expressed genes induced by H3L, which were involved in the atrial/ventricle morphogenesis ( H ) and aorta development ( I ). J RNA-seq read counts showing the expression levels of cardiac hypertrophy marker Nppb in Control and H3L OE mouse heart tissues.

    Journal: Cell Death & Disease

    Article Title: Monkeypox virus protein H3L induces injuries in human and mouse

    doi: 10.1038/s41419-024-06990-2

    Figure Lengend Snippet: A Scheme of in vivo mouse model to study the effects of H3L in heart. Lentiviruses with control and H3L OE were intraperitoneally injected into one month old mouse. Two months later, heart tissues were collected for bulk RNA-seq. B ELISA assay showing protein expression level of IL1A in blood plasma from mouse heart. *p < 0.05 (vs. Control). Relative level in the Y-axis meant the read count on the absorption at 450 nm by the equipment. C Principal component analysis (PCA) of RNA-seq on mouse heart tissues. Three biological replicates were applied for RNA-seq. D Volcano plots showing differentially expressed genes (DEGs) in heart tissues induced by H3L. P < 0.05 and | log 2 (fold change) | > 0 were set as the threshold for DEGs. E Signaling pathway analysis of differentially expressed genes induced by H3L. The top 20 of highest ranked GO terms were presented. Pathway analysis was run on Reactome. Padj, adjusted p value. F Heatmap showing differentially expressed genes (DEGs) induced by H3L, which were involved in the Citric acid cycle and Respiratory electron transport. G Evaluation of ATP amount in mouse neonatal cardiomyocytes overexpressed with control lentivirus (Control) or H3L lentivirus (H3L OE ). *p < 0.05 (vs. Control). Heatmap showing differentially expressed genes induced by H3L, which were involved in the atrial/ventricle morphogenesis ( H ) and aorta development ( I ). J RNA-seq read counts showing the expression levels of cardiac hypertrophy marker Nppb in Control and H3L OE mouse heart tissues.

    Article Snippet: Cardiac differentiation was induced by STEMdiffTM Ventricular Cardiomyocyte Differentiation Kit (STEMCELL Technologies) according to the manual.

    Techniques: In Vivo, Control, Injection, RNA Sequencing, Enzyme-linked Immunosorbent Assay, Expressing, Clinical Proteomics, Marker

    A Immunostaining showing mouse P0 neonatal cardiomyocytes. TNNT2 is a specific marker of cardiomyocyte. Scale bar, 100 µm. B Statistic analysis of cell size of mouse P0 cardiomyocytes from ( A ). *p < 0.05. C Western blot showing the protein expression of NPPB in mouse cardiomyocytes. *p < 0.05. D Western blot showing the protein expression of COL1A1 in mouse cardiomyocytes. *p < 0.05. E Western blot showing the protein expression of COL3A1 in mouse cardiomyocytes. *p < 0.05.

    Journal: Cell Death & Disease

    Article Title: Monkeypox virus protein H3L induces injuries in human and mouse

    doi: 10.1038/s41419-024-06990-2

    Figure Lengend Snippet: A Immunostaining showing mouse P0 neonatal cardiomyocytes. TNNT2 is a specific marker of cardiomyocyte. Scale bar, 100 µm. B Statistic analysis of cell size of mouse P0 cardiomyocytes from ( A ). *p < 0.05. C Western blot showing the protein expression of NPPB in mouse cardiomyocytes. *p < 0.05. D Western blot showing the protein expression of COL1A1 in mouse cardiomyocytes. *p < 0.05. E Western blot showing the protein expression of COL3A1 in mouse cardiomyocytes. *p < 0.05.

    Article Snippet: Cardiac differentiation was induced by STEMdiffTM Ventricular Cardiomyocyte Differentiation Kit (STEMCELL Technologies) according to the manual.

    Techniques: Immunostaining, Marker, Western Blot, Expressing