The Insulin-Like Growth Factor Axis: A New Player in Gestational Diabetes Mellitus?
Bibliographic record
Abstract
Gestational diabetes mellitus (GDM), defined as glucose intolerance of varying severity with first onset and recognition in pregnancy, is a diagnosis that holds relevance for the diabetes epidemic across two generations—that of the mother and her child (1,2). Indeed, despite typically regaining normal glucose tolerance in the immediate postpartum, women with previous GDM have a very high risk of future progression to type 2 diabetes (T2D) (3). Similarly, their offspring have an elevated risk of accruing metabolic abnormalities in childhood that may be partly attributable to the intrauterine environment of the GDM pregnancy (4). As such, enhanced understanding of the pathophysiology of GDM could yield strategies for early identification of at-risk mothers and ideally mitigation of their metabolic risk, to the benefit of both mother and child (2). Current understanding of the pathophysiology of GDM holds that affected women have a defect in pancreatic β-cell function that first manifests clinically as an inability to fully compensate for the marked insulin resistance of the latter half of pregnancy, resulting in characteristic hyperglycemia in late second or third trimester (1,2). Importantly, although this clinical presentation arises in response to the physiologic stress test posed by pregnancy, affected women have chronic β-cell dysfunction and insulin resistance that is readily apparent in the years thereafter and that contributes to their elevated lifetime risk of T2D (5 …
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.013 | 0.019 |
| Insufficient payload (model declined to judge) | 0.004 | 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".