Network medicine-travelling with the insulin receptor: Encounter of the second type
Bibliographic record
Abstract
Important progress has been made in understanding many aspects of insulin action in the last 10 years. Attention will be focused here on the physical protein interaction network of the internalized insulin receptor (IR) and its relationships with the genetic architecture of type 2 diabetes mellitus (T2D). The IR recognizes signals from the outside (circulating insulin) and engages the insulin signaling response. Within seconds, the IR is also involved in insulin internalization and its subsequent degradation in endosomes (physiological clearance of insulin). A T2D disease module sharing functional similarities with insulin secretion in pancreatic islets was recently identified in the close neighborhood of the internalized IR in liver. This module brought a new light on the apparent functional heterogeneity of numerous genes at risk to T2D by linking them to a few noncanonical layers of signaling feedback loops. These findings should be translated into a better understanding of the primary mechanisms of the disease and consequently a more precise sub-classification of T2D, ultimately leading to precision medicine and the development of new therapeutical drugs.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".