ArticleCytotechnology2013
Development of novel cell lines of diabetic dysfunction model fit for cell-based screening tests of medicinal materials.
Article in Cytotechnology, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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.
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Who cites it
1 citing paper in PubMed, 6 citations in OpenAlex.
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Authors and funding
4 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Pdx-1 and Irs-1, genes highly associated with diabetes onset, were knocked down in mouse embryonic stem (ES) cells in order to develop cell line models for diabetes. ES cells with different gene knockdown levels were induced to differentiate to the stage of insulin production. Among the cell lines that differentiated, we identified two in which the levels of expression of both genes were 20-40 % of that of control cells. These cell lines showed appreciable deficiencies in three characteristic malfunctions associated with diabetes, namely, insulin production, insulin reception signaling, and glucose-stimulated insulin secretion. These dysfunctions were consistent with results reported elsewhere from in vivo and in vitro studies. Both cell lines did not show any abnormal morphology such as size, shape, color, and surface roughness. No abnormal expression profiles for 17 genes relevant to diabetes were observed. Therefore, these cell lines fulfilled the criteria for a validated cell model for diabetes. The model cell lines developed here are promising biomaterials for cell-based screening tests of new medicines that may be effective in treating diabetes.
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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.