ArticleThe Analyst2017
Bottom-up proteomics analysis of the secretome of murine islets of Langerhans in elevated glucose levels.
Article in The Analyst, 2017. 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
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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
1 citing paper in PubMed, 3 citations in OpenAlex.
- Automated and online LC-MS/MS for multiplexed monitoring of hormone secretion from murine islets.Analytical and bioanalytical chemistry · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 3 institutions in 3 countries.
Funding
Abstract
Glucotoxicity is a causative agent of type-2 diabetes, where high glucose levels damage the islets of Langerhans resulting in oxidative damage and endoplasmic reticulum stress. We evaluated the secretomes of healthy CD-1 murine islets. Three experimental conditions were investigated in biological triplicate: a control incubated with 11 mM glucose, 1-day incubation with 25 mM glucose, and 2-day incubation with 25 mM glucose. An SDS-based, filter-aided sample preparation protocol was used to prepare secretomes for analysis. A total of 428 protein groups were identified across the nine samples. Each condition generated between 328-349 protein IDs and intracondition protein overlap was between 66-90% for the biological triplicates. 232 protein groups were identified in all three conditions with 184 quantified at least once in each condition. Significant expression changes were observed for proteins associated with the unfolded protein response, such as proteases, chaperones, and elongation factors, as well as proteins associated with peptide hormone processing and small molecule metabolism.
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Registered trials
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