Convergent Effects of Acute Stress and Glucocorticoid Exposure upon MAO-A in Humans
Bibliographic record
Abstract
Monoamine oxidase-A (MAO-A), a key brain enzyme which metabolizes monoamines, is implicated in the pathophysiology of stress-related illnesses, including major depressive disorder, addiction, and violent behavior. Chronic stressors and glucocorticoid-administration typically associate with elevated MAO-A levels/activity. However, the relationship of shorter stress or glucocorticoid exposures and MAO-A levels/activity is not well established. Our objectives are to assess effects of acute stress upon MAO-A V(T,) an index of MAO-A density, in human brain and acute glucocorticoid exposure upon MAO-A levels in human neuronal and glial cell lines. Twelve healthy, non-smoking participants aged 18-50 underwent [(11)C]harmine positron emission tomography to measure brain MAO-A V(T) on two different days: One under acute psychosocial stress (via Trier Social Stress and Montreal Imaging Stress Tasks) and one under a non-stress condition. MAO-A density (by Western blot) and activity (by [(14)C]-5-HT metabolism and liquid scintillation spectroscopy) were measured in human neuronal and glial cell lines after 4 h exposure to dexamethasone. We observed a significant reduction in whole-brain MAO-A binding as reflected by reductions in 10 of 11 brain regions. Acute dexamethasone exposure in neuronal and glial cells significantly decreased MAO-A activity and protein levels. We observed a highly consistent relationship between acute stressors and glucocorticoid administration and decreased MAO-A binding, activity and protein levels. Since MAO-A metabolizes monoamines, this phenomenon may explain why acute stressors benefit healthy animals even though chronic stress is associated with illness.
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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".