Mechanisms of action of islet neogenesis-associated protein: comparison of the full-length recombinant protein and a bioactive peptide
Bibliographic record
Abstract
Islet neogenesis-associated protein (INGAP) was discovered in the partially duct-obstructed hamster pancreas as a factor inducing formation of new duct-associated islets. A bioactive portion of INGAP, INGAP(104-118) peptide (INGAP-P), has been shown to have neogenic and insulin-potentiating activity in numerous studies, including recent phase 2 clinical trials that demonstrated improved glucose homeostasis in both type 1 and type 2 diabetic patients. Aiming to improve INGAP-P efficacy and to understand its mechanism of action, we cloned the full-length protein (rINGAP) and compared the signaling events induced by the protein and the peptide in RIN-m5F cells that respond to INGAP with an increase in proliferation. Here, we show that, although both rINGAP and INGAP-P signal via the Ras/Raf/ERK pathway, rINGAP is at least 100 times more efficient on a molar basis than INGAP-P. For either ligand, ERK1/2 activation appears to be pertussis toxin sensitive, suggesting involvement of a G protein-coupled receptor(s). However, there are clear differences between the peptide and the protein in interactions with the cell surface and in the downstream signaling. We demonstrate that fluorescent-labeled rINGAP is characterized by clustering on the membrane and by slow internalization (≤5 h), whereas INGAP-P does not cluster and is internalized within minutes. Signaling by rINGAP appears to involve Src, in contrast to INGAP-P, which appears to activate Akt in addition to the Ras/Raf/ERK1/2 pathway. Thus our data suggest that interactions of INGAP with the cell surface are important to consider for further development of INGAP as a pharmacotherapy for diabetes.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".