The NE/AAT/CBG axis regulates adipose tissue glucocorticoid exposure
Bibliographic record
Abstract
Corticosteroid binding globulin (CBG; SERPINA6) binds >85% of circulating glucocorticoids but its influence on their metabolic actions is unproven. Targeted proteolytic cleavage of CBG by neutrophil elastase (NE; ELANE) significantly reduces CBG binding affinity, potentially increasing 'free' glucocorticoid levels at sites of inflammation. NE is inhibited by alpha-1-antitrypsin (AAT; SERPINA1). Using complementary approaches in mice and humans to manipulate NE or AAT, we show high-fat diet (HFD) increases the NE:AAT ratio specifically in murine visceral adipose tissue, an effect only observed in males. Notably, HFD-fed male mice lacking NE have reduced glucocorticoid levels and action specifically in visceral adipose tissue, with improved glucose tolerance and insulin sensitivity, independent of systemic changes in free glucocorticoids. The protective effect of NE deficiency is lost when the adrenals are removed. Moreover, human asymptomatic heterozygous carriers of deleterious mutations in SERPINA1 resulting in lower AAT levels have increased adipose tissue glucocorticoid levels and action. However, in contrast to mice, humans present with systemic increases in free circulating glucocorticoid levels, an effect independent of HPA axis activation. These findings show that NE and AAT regulate local tissue glucocorticoid bioavailability in vivo, providing crucial evidence of a mechanism linking inflammation and metabolism.
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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".