A novel insulin receptor-signaling platform and its link to insulin resistance and type 2 diabetes
Bibliographic record
Abstract
Insulin-induced insulin receptor (IR) tyrosine kinase activation and insulin cell survival responses have been reported to be under the regulation of a membrane associated mammalian neuraminidase-1 (Neu1). The molecular mechanism(s) behind this process is unknown. Here, we uncover a novel Neu1 and matrix metalloproteinase-9 (MMP-9) cross-talk in alliance with neuromedin B G-protein coupled receptor (GPCR), which is essential for insulin-induced IR activation and cellular signaling. Neu1, MMP-9 and neuromedin B GPCR form a complex with IRβ subunit on the cell surface. Oseltamivir phosphate (Tamiflu®), anti-Neu1 antibodies, broad range MMP inhibitors piperazine and galardin (GM6001), MMP-9 specific inhibitor (MMP-9i), and GPCR neuromedin B specific antagonist BIM-23127 dose-dependently inhibited Neu1 activity associated with insulin stimulated rat hepatoma cells (HTCs) that overly express human IRs (HTC-IR). Tamiflu, anti-Neu1 antibodies and MMP-9i attenuated phosphorylation of IRβ and insulin receptor substrate-1 (IRS1) associated with insulin-stimulated cells. Olanzapine, an antipsychotic agent associated with insulin resistance, induced Neu3 sialidase activity in WG544 or 1140F01 human sialidosis fibroblast cells genetically defective in Neu1. Neu3 antagonist 2-deoxy-2,3-didehydro-N-acetylneuraminic acid (DANA) and anti-Neu3 antibodies inhibited sialidase activity associated with olanzapine treated murine Neu4 knockout macrophage cells. Olanzapine attenuated phosphorylation of IGF-R and IRS1 associated with insulin-stimulated human wild-type fibroblast cells. Our findings identify a novel insulin receptor-signaling platform that is critically essential for insulin-induced IRβ tyrosine kinase activation and cellular signaling. Olanzapine-induced Neu3 sialidase activity attenuated insulin-induced IGF-R and IRS1 phosphorylation contributing to insulin resistance.
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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) | 0.002 | 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".