Impact of Changes Over Time in Adipokines and Inflammatory Proteins on Changes in Insulin Sensitivity, β-Cell Function, and Glycemia in Women With Previous Gestational Dysglycemia
Bibliographic record
Abstract
Adipokine dysregulation and subclinical inflammation are putative diabetogenic features of adiposity. However, while alterations in adipokines/inflammatory proteins can predict incident type 2 diabetes in longitudinal studies (1–3), evidence for causality is generally hindered by two limitations. First, there is a relative paucity of human data linking changes in adipokines/inflammatory proteins with changes in insulin sensitivity and β-cell function over time, as might be expected for causal mediators. Second, because obesity-induced changes in circulating proteins do not occur in isolation, the precise elucidation of causal mediators ideally requires consideration of multiple adipokines/inflammatory proteins simultaneously (as opposed to individually, as typically occurs in studies). Thus, to address these limitations, we evaluated changes over 2 years in adipokines (adiponectin, chemerin, retinol-binding protein 4 [RBP-4]) and inflammatory proteins (C-reactive protein [CRP], plasminogen activator inhibitor 1 [PAI-1]) in relation to changes in insulin sensitivity, β-cell function, and glycemia in women with varying degrees of recent gestational dysglycemia …
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".