Roles of leptin, adiponectin and resistin in the transcriptional regulation of steroidogenic genes contributing to decreased Leydig cells function in obesity
Bibliographic record
Abstract
The increase in obesity rate is a major public health issue associated with increased pathological conditions such as type 2 diabetes or cardiovascular diseases. Obesity also contributes to decreased testosterone levels in men. Indeed, the adipose tissue is an endocrine organ which produces hormones such as leptin, adiponectin and resistin. Obesity results in pathological accumulations of leptin and resistin, whereas adiponectin plasma levels are markedly reduced, all having a negative impact on testosterone synthesis. This review focuses on current knowledge related to transcriptional regulation of Leydig cells' steroidogenesis by leptin, adiponectin and resistin. We show that there are crosstalks between the regulatory mechanisms of these hormones and androgen production which may result in a dramatic negative influence on testosterone plasma levels. Indeed leptin, adiponectin and resistin can impact expression of different steroidogenic genes such as Star, Cyp11a1 or Sf1. Further investigations will be required to better define the implications of adipose derived hormones on regulation of steroidogenic genes expression within Leydig cells under physiological as well as pathological conditions.
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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 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".