ArticleAging2013
How to measure RNA expression in rare senescent cells expressing any specific protein such as p16Ink4a.
Article in Aging, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
10 citing papers in PubMed, 11 citations in OpenAlex.
- Review
- Dysregulated megakaryocyte distribution associated with nestinBlood advances · 2019Article
- Maintaining RNA Integrity for Transcriptomic Profiling of Ex Vivo Cultured Limbal Epithelial Stem Cells after Fluorescence-Activated Cell Sorting (FACS).Biological procedures online · 2017Article
- H3K27me3 Does Not Orchestrate the Expression of Lineage-Specific Markers in hESC-Derived Hepatocytes In Vitro.Stem cell reports · 2016Article
- Novel method for the high-throughput production of phosphorylation site-specific monoclonal antibodies.Scientific reports · 2016Article
- Reorganization of chromosome architecture in replicative cellular senescence.Science advances · 2016Article
- Gerosuppression in confluent cells.Aging · 2014Article
- A comparison of oncogene-induced senescence and replicative senescence: implications for tumor suppression and aging.Age (Dordrecht, Netherlands) · 2014Article
- Article
- Geroconversion: irreversible step to cellular senescence.Cell cycle (Georgetown, Tex.) · 2014Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors at 1 institution in 1 country.
Funding
Abstract
Here we describe a carefully optimized method for the preparation of high quality RNA by flow sorting of formaldehyde fixed senescent cells immunostained for any intracellular antigen. Replicative cellular senescence is a phenomenon of irreversible growth arrest triggered by the accumulation of a discrete number of cell divisions. The underlying cause of senescence due to replicative exhaustion is telomere shortening. We document here a spontaneous and apparently stochastic process that continuously generates senescent cells in cultures fully immortalized with telomerase. In the course of studying this phenomenon we developed a preparative fluorescence activated flow sorting method based on immunofluorescent staining of intracellular antigens that can also deliver RNA suitable for quantitative analysis of global gene expression. The protocols were developed using normal human diploid fibroblasts (HDF) and up to 5x107 cells could be conveniently processed in a single experiment. The methodology is based on formaldehyde crosslinking of cells, followed by permeabilization, antibody staining, flow sorting, reversal of the crosslinks, and recovery of the RNA. We explored key parameters such as crosslink reversal that affect the fragmentation of RNA. The recovered RNA is of high quality for downstream molecular applications based on short range sequence analysis, such qPCR, hybridization microarrays, and next generation sequencing. The RNA was analyzed by Affymetrix Gene Chip expression profiling and compared to RNA prepared by the direct lysis of cells. The correlation between the data sets was very high, indicating that the procedure does not introduce systematic changes in the mRNA transcriptome. The methods presented in this communication should be of interest to many investigators working in diverse model systems.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.