Catecholamines Induce Endoplasmic Reticulum Stress Via Both Alpha and Beta Receptors
Bibliographic record
Abstract
Severely burned patients suffer from a hypermetabolic syndrome that can last for years after the injury has resolved. The underlying cause of these metabolic alterations most likely involves the persistent elevated catecholamine levels that follow the surge induced by thermal injury. At the cellular level, endoplasmic reticulum (ER) stress in metabolic tissues is a hallmark observed in patients following burn injury and is associated with several detrimental effects. Therefore, ER stress could be the underlying cellular mechanism of persistent hypermetabolism in burned patients. Here, we show that catecholamines induce ER stress and that adreno-receptor blockers reduce stress responses in the HepG2 hepatocyte cell line. Our results also indicate that norepinephrine (NE) significantly induces ER stress in HepG2 cells and 3T3L1 mouse adipocytes. Furthermore, we demonstrate that the alpha-1 blocker, prazosin, and beta blocker, propranolol, block ER stress induced by NE. We also show that the effects of catecholamines in inducing ER stress are cell type-specific, as NE treatment failed to evoke ER stress in human fibroblasts. Thus, these findings reveal the mechanisms used by catecholamines to alter metabolism and suggest inhibition of the receptors utilized by these agents should be further explored as a potential target for the treatment of ER stress-mediated disease.
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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 | 0.001 |
| 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".