Modulation of IGFBP2 mRNA Expression in White Adipose Tissue upon Aging and Obesity
Bibliographic record
Abstract
The insulin/IGF-1 signaling pathway is a determinant of aging and age-related diseases. IGF-binding protein 2 (IGFBP2) is secreted by white adipocytes and contributes to the prevention of diet-induced obesity and age-related insulin resistance in mice. However, the expression levels of IGFBP2 in insulin resistance disorders have not been evaluated. The present study was aimed at determining IGFBP2 mRNA levels in adipose tissue in conditions of insulin resistance such as aging and obesity. In visceral white adipose tissue (WAT), but not in subcutaneous WAT, IGFBP2 mRNA levels were significantly lower in obese OB/OB, DB/DB and high fat-fed mice compared with those of their respective lean and chow-fed littermates. IGFBP2 mRNA levels were also decreased in visceral WAT of 12 and 24 months old mice compared with those of their 4 months old counterparts. Visceral WAT IGFBP2 expression was significantly associated with IGFBP2 circulating levels in mice, suggesting an important contribution from this tissue. The negative effect of aging on IGFBP2 mRNA levels in visceral WAT was confirmed in obese men. These findings demonstrate that the transcription of the IGFBP2 gene is modulated in a depot-specific fashion in obesity and aging in mice and men. Because IGFBP2 is an adipokine, an altered production from visceral WAT depots could impact on IGF-1 signaling and its downstream targets. This supports the need for further molecular and clinical studies to determine the factors regulating IGFBP2 expression and its relevance to metabolic diseases.
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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 | 0.000 |
| 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".