Sex differences in regional adipose tissue depots pose different threats for the development of Type 2 diabetes in males and females
Bibliographic record
Abstract
Type 2 diabetes mellitus (T2DM) affects males and females disproportionately. In midlife, more males have T2DM than females. The sex difference in T2DM prevalence is, in part, explained by differences in regional adipose tissue characteristics. With obesity, changes to regional adipokine and cytokine release increases the risk of T2DM in both males and females with males having greater levels of TNFα and females having greater levels of leptin, CRP, and adiponectin. Regional immune cell infiltration appears to be pathogenic in both sexes via different routes as males with obesity have greater VAT ATM and a decrease in the protective Treg cells, whereas females have greater SAT ATM and T cells. Lastly, the ability of female adipose tissue to expand all regions through hyperplasia, rather than hypertrophy, protects them against the development of large insulin-resistant adipocytes that dominate male adipose tissue. The objective of this review is to discuss how sex may affect regional differences in adipose tissue characteristics and how these differences may distinguish the development of T2DM in males and females. In doing so, we will show that the origins of T2DM development differ between males and females.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".