Glucagon does not Affect Catecholamine Release in Primary Cultures of Bovine Adrenal Chromaffin Cells
Bibliographic record
Abstract
OBJECTIVE: Human pheochromocytoma tumor cells express glucagon receptors, and bolus i.v. glucagon injection rapidly increases plasma epinephrine levels, suggesting that glucagon can directly stimulate adrenomedullary secretion. In this study, we tested whether the catecholamine secretory response to glucagon was present in bovine chromaffin cells or exclusive to the tumor cells. DESIGN AND METHODS: Adrenomedullary cells were cultured in 24-well plates (10(6) cells per well). After 48-72 hours, wells were incubated for 1-20 minutes with (1) incubation medium (control), (2) catecholamine secretagogues (nicotine or potassium ion), or (3) glucagon (10(-8) to 10(-5) M). After incubation, catecholamine contents in medium and cells were assayed by high-pressure liquid chromatography with electrochemical detection. Fractional release rates of epinephrine, norepinephrine, and dopamine were calculated and compared to controls. Reverse-transcriptase PCR was performed to compare expression of mRNA of the glucagon receptor in chromaffin cells and pheochromocytoma cells. RESULTS: Nicotine and potassium evoked time-dependent release of epinephrine, norepinephrine, and dopamine. Glucagon did not affect catecholamine secretion at any concentration. Reverse-transcriptase PCR failed to detect mRNA for glucagon receptor in bovine adrenomedullary cells, but did detect it in human pheochromocytoma cells. CONCLUSIONS: In contrast to pheochromocytoma tumor cells, bovine adrenomedullary chromaffin cells do not express the glucagon receptor, and therefore do not secrete catecholamines in response to glucagon.
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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) | 0.002 | 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".