frozen osteolytic murine sarcoma cells Search Results


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Calico Labs scrna-seq calico murine cell atlas
scAgeCom was built by applying scDiffCom to 58 public <t>scRNA-seq</t> aging datasets encompassing 23 tissues ( y axis) from both male and female mice and different experimental techniques ( x axis). The number of cell types detected per dataset is indicated in each rectangle. Information regarding the ages of the mice is indicated along the x axis and applies to all datasets of a given column unless specified otherwise in specific rectangles. Empty areas indicate unavailable data. Data are available in Supplementary Table . m, months.
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scAgeCom was built by applying scDiffCom to 58 public <t>scRNA-seq</t> aging datasets encompassing 23 tissues ( y axis) from both male and female mice and different experimental techniques ( x axis). The number of cell types detected per dataset is indicated in each rectangle. Information regarding the ages of the mice is indicated along the x axis and applies to all datasets of a given column unless specified otherwise in specific rectangles. Empty areas indicate unavailable data. Data are available in Supplementary Table . m, months.
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scAgeCom was built by applying scDiffCom to 58 public <t>scRNA-seq</t> aging datasets encompassing 23 tissues ( y axis) from both male and female mice and different experimental techniques ( x axis). The number of cell types detected per dataset is indicated in each rectangle. Information regarding the ages of the mice is indicated along the x axis and applies to all datasets of a given column unless specified otherwise in specific rectangles. Empty areas indicate unavailable data. Data are available in Supplementary Table . m, months.
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Figure 6: TXNIP upregulation upon depletion of PK activity in different model systems. (A) RT-qPCR quantification of Pklr (left) and Txnip (right) transcripts upon transient siRNA-mediated knockdown of Pklr in mouse primary <t>hepatocytes.</t> Each datapoint represents an average value of 4 technical replicates. Paired samples were derived from the same mouse and treated with non-targeting control or Pklr targeting siRNA; n ¼ 3, Paired samples Student’s t-test. (B) RT-qPCR quantification of PKLR (left), PKM (middle) and TXNIP (right) transcripts upon transient sequential siRNA-mediated knockdown of PKLR and/or PKM in HepaRG cells; n ¼ 4, pairwise Student’s t-test, p values adjusted with Bonferroni method, ns p 0.05, *p < 0.05, **p < 0.01, ***p < 0.001. (C) RT-qPCR quantification of transcripts encoding pkm and txnip variants in wt and pkma/b double knocked out zebrafish embryos (day 5); n ¼ 3, Student’s t-test, ns p 0.05, *p < 0.05, **p < 0.01.
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imaGenes GmbH cdna murine naip5
Figure 6: TXNIP upregulation upon depletion of PK activity in different model systems. (A) RT-qPCR quantification of Pklr (left) and Txnip (right) transcripts upon transient siRNA-mediated knockdown of Pklr in mouse primary <t>hepatocytes.</t> Each datapoint represents an average value of 4 technical replicates. Paired samples were derived from the same mouse and treated with non-targeting control or Pklr targeting siRNA; n ¼ 3, Paired samples Student’s t-test. (B) RT-qPCR quantification of PKLR (left), PKM (middle) and TXNIP (right) transcripts upon transient sequential siRNA-mediated knockdown of PKLR and/or PKM in HepaRG cells; n ¼ 4, pairwise Student’s t-test, p values adjusted with Bonferroni method, ns p 0.05, *p < 0.05, **p < 0.01, ***p < 0.001. (C) RT-qPCR quantification of transcripts encoding pkm and txnip variants in wt and pkma/b double knocked out zebrafish embryos (day 5); n ¼ 3, Student’s t-test, ns p 0.05, *p < 0.05, **p < 0.01.
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ApexBio rnase inhibitor, murine
Figure 6: TXNIP upregulation upon depletion of PK activity in different model systems. (A) RT-qPCR quantification of Pklr (left) and Txnip (right) transcripts upon transient siRNA-mediated knockdown of Pklr in mouse primary <t>hepatocytes.</t> Each datapoint represents an average value of 4 technical replicates. Paired samples were derived from the same mouse and treated with non-targeting control or Pklr targeting siRNA; n ¼ 3, Paired samples Student’s t-test. (B) RT-qPCR quantification of PKLR (left), PKM (middle) and TXNIP (right) transcripts upon transient sequential siRNA-mediated knockdown of PKLR and/or PKM in HepaRG cells; n ¼ 4, pairwise Student’s t-test, p values adjusted with Bonferroni method, ns p 0.05, *p < 0.05, **p < 0.01, ***p < 0.001. (C) RT-qPCR quantification of transcripts encoding pkm and txnip variants in wt and pkma/b double knocked out zebrafish embryos (day 5); n ¼ 3, Student’s t-test, ns p 0.05, *p < 0.05, **p < 0.01.
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Image Search Results


scAgeCom was built by applying scDiffCom to 58 public scRNA-seq aging datasets encompassing 23 tissues ( y axis) from both male and female mice and different experimental techniques ( x axis). The number of cell types detected per dataset is indicated in each rectangle. Information regarding the ages of the mice is indicated along the x axis and applies to all datasets of a given column unless specified otherwise in specific rectangles. Empty areas indicate unavailable data. Data are available in Supplementary Table . m, months.

Journal: Nature Aging

Article Title: scDiffCom: a tool for differential analysis of cell–cell interactions provides a mouse atlas of aging changes in intercellular communication

doi: 10.1038/s43587-023-00514-x

Figure Lengend Snippet: scAgeCom was built by applying scDiffCom to 58 public scRNA-seq aging datasets encompassing 23 tissues ( y axis) from both male and female mice and different experimental techniques ( x axis). The number of cell types detected per dataset is indicated in each rectangle. Information regarding the ages of the mice is indicated along the x axis and applies to all datasets of a given column unless specified otherwise in specific rectangles. Empty areas indicate unavailable data. Data are available in Supplementary Table . m, months.

Article Snippet: are provided with this paper Datasets used in this study: • scRNA-seq Tabula Muris Senis: https://s3.console.aws.amazon.com/s3/buckets/czb-tabula-muris-senis • scRNA-seq Calico murine cell atlas: https://mca.research.calicolabs.com/ • LRIs from CellChat: available from their R package • LRIs from NicheNet: available from their R package • LRIs from SingleCellSignalR: available from their R package • LRIs from CellPhoneDB: https://www.cellphonedb.org/ • LRIs from CellTalkDB: https://github.com/ZJUFanLab/CellTalkDB • LRIs from connectomeDB2020: https://asrhou.github.io/NATMI/ • LRIs from ICELLNET: https://github.com/soumelis-lab/ICELLNET • General gene information: https://mygene.info/ and https://omnipathdb.org/ • GO terms: Ensembl (version 102), https://useast.ensembl.org/index.html • KEGG: accessed via the R package KEGGREST • gene2pubmed table: ftp://ftp.ncbi.nlm.nih.gov/gene/DATA/gene2pubmed.gz • GenAge (build 20): https://genomics.senescence.info/genes/index.html • LongevityMap (build 3): https://genomics.senescence.info/longevity/ • Microarray meta-analysis of Ageing Gene Expression database: https://genomics.senescence.info/gene_expression/ • CellAge (build 2): Supplementary Material of 10.1093/molbev/msab369 • Secretomics data for mBMM: Supplementary Material of 10.1126/science.1232578 • Secretomics data for mNeuron: Supplementary Material of 10.15252/embj.2020105693 • Secretomics data for mMSC-AT: Supplementary Material of 10.18632/aging.202423 • Secretomics data for rCM: Supplementary Material of 10.1161/circulationaha.119.044914 • Secretomics data for hUVEC: Supplementary Material of 10.1016/j.ajpath.2019.10.007 • Secretomics data for hPDE: Supplementary Material of 10.1002/pmic.202100320 Datasets created in this study: • scDiffCom LRIs: available from the R package scDiffCom ( https://github.com/CyrilLagger/scDiffCom/tree/master/data ) • Aging and sex scAgeCom results: 10.6084/m9.figshare.17074964 • Data to run the app scAgeComShiny and scagecom.org: https://figshare.com/articles/dataset/scAgeComShiny_data/17075375

Techniques:

Figure 6: TXNIP upregulation upon depletion of PK activity in different model systems. (A) RT-qPCR quantification of Pklr (left) and Txnip (right) transcripts upon transient siRNA-mediated knockdown of Pklr in mouse primary hepatocytes. Each datapoint represents an average value of 4 technical replicates. Paired samples were derived from the same mouse and treated with non-targeting control or Pklr targeting siRNA; n ¼ 3, Paired samples Student’s t-test. (B) RT-qPCR quantification of PKLR (left), PKM (middle) and TXNIP (right) transcripts upon transient sequential siRNA-mediated knockdown of PKLR and/or PKM in HepaRG cells; n ¼ 4, pairwise Student’s t-test, p values adjusted with Bonferroni method, ns p 0.05, *p < 0.05, **p < 0.01, ***p < 0.001. (C) RT-qPCR quantification of transcripts encoding pkm and txnip variants in wt and pkma/b double knocked out zebrafish embryos (day 5); n ¼ 3, Student’s t-test, ns p 0.05, *p < 0.05, **p < 0.01.

Journal: Molecular metabolism

Article Title: Depletion of pyruvate kinase (PK) activity causes glycolytic intermediate imbalances and reveals a PK-TXNIP regulatory axis.

doi: 10.1016/j.molmet.2023.101748

Figure Lengend Snippet: Figure 6: TXNIP upregulation upon depletion of PK activity in different model systems. (A) RT-qPCR quantification of Pklr (left) and Txnip (right) transcripts upon transient siRNA-mediated knockdown of Pklr in mouse primary hepatocytes. Each datapoint represents an average value of 4 technical replicates. Paired samples were derived from the same mouse and treated with non-targeting control or Pklr targeting siRNA; n ¼ 3, Paired samples Student’s t-test. (B) RT-qPCR quantification of PKLR (left), PKM (middle) and TXNIP (right) transcripts upon transient sequential siRNA-mediated knockdown of PKLR and/or PKM in HepaRG cells; n ¼ 4, pairwise Student’s t-test, p values adjusted with Bonferroni method, ns p 0.05, *p < 0.05, **p < 0.01, ***p < 0.001. (C) RT-qPCR quantification of transcripts encoding pkm and txnip variants in wt and pkma/b double knocked out zebrafish embryos (day 5); n ¼ 3, Student’s t-test, ns p 0.05, *p < 0.05, **p < 0.01.

Article Snippet: 2.1.3. siRNA transfection of murine hepatocytes Primary murine hepatocytes from 8 to 12-weeks-old C57BL6/N mice (Janvier Labs) were isolated using collagenase perfusion [48,49].

Techniques: Activity Assay, Quantitative RT-PCR, Knockdown, Derivative Assay, Control