ArticleGenomics data2015
Use of multiple time points to model parotid differentiation.
Article in Genomics data, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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
0 citing papers in PubMed, 2 citations in OpenAlex.
No citing paper in PubMed yet.
Corrections and comments
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Authors and funding
4 authors at 1 institution in 1 country.
Funding
Abstract
In order to understand the process of terminal differentiation in salivary acinar cells, mRNA and microRNA expression was measured across the month long process of differentiation in the parotid gland of the rat. Acinar cells were isolated at either nine time points (mRNA) or four time points (microRNA) in triplicate using laser capture microdissection (LCM). One of the values of this dataset comes from the high quality RNA (RIN > 7) that was used in this study, which can be prohibitively difficult to obtain from such an RNaseI-rich tissue. Global mRNA expression was measured by rat genome microarray hybridization (http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE65586), and expression of microRNAs by qPCR array (http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE65324). Comparing expression at different ages, 2656 mRNAs and 64 microRNAs were identified as differentially expressed. Because mRNA expression was sampled at many time points, clustering and regression analysis were able to identify dynamic expression patterns that had not been implicated in acinar differentiation before. Integration of the two datasets allowed the identification of microRNA target genes, and a gene regulatory network. Bioinformatics R code and additional details of experimental methods and data analysis are provided.
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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.