Adrenergic Responses to Stress
Bibliographic record
Abstract
Stress effects on adrenergic responses in rats were examined in adrenal medulla, the primary source of circulating epinephrine (Epi). Irrespective of duration, immobilization (IMMO) increased adrenal corticosterone to the same extent. In contrast, Epi changed little, suggesting that Epi synthesis replenishes adrenal pools and sustains circulating levels for the heightened alertness and physiological changes required of the "flight or fight" response. IMMO also induced the Epi-synthesizing enzyme, phenylethanolamine N-methyltransferase (PNMT). The rise in its mRNA and protein was preceded by increases in Egr-1 and Sp1 mRNA, protein, and protein-DNA binding complex formation. With repeated and prolonged stress, PNMT protein did not reflect the magnitude of change in mRNA. The latter suggests that post-transcriptional, in addition to transcriptional mechanisms, regulate PNMT responses to stress. To further reveal molecular mechanisms underlying stress-induced changes in adrenergic function, the effects of hypoxia on PNMT promoter-driven gene expression are being examined in adrenal medulla-derived PC12 cells. Hypoxia activates the PNMT promoter to increase PNMT promoter-driven luciferase reporter gene expression and endogenous PNMT in PC12 cells. Induction of both appear mediated via activation of multiple signaling pathways and downstream activation of hypoxia inducible factor and PNMT transcriptional activators, Egr-1 and Sp1. Hypoxia generates both partially and fully processed forms of PNMT mRNA. The former reportedly is translated into a truncated, nonfunctional protein, and the latter into enzymatically active PNMT. Together, findings suggest that stress increases PNMT gene transcriptional activity but post-transcriptional regulatory mechanisms limit the biological end-point of functional PNMT enzyme and, thereby, Epi.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".