Opposing effects of phorbol‐12‐myristate‐13‐acetate, an activator of protein kinase C, on the signaling of structurally related human dopamine D1 and D5 receptors
Bibliographic record
Abstract
The 'cross-talk' between different types of neurotransmitters through second messenger pathways represents a major regulatory mechanism in neuronal function. We investigated the effects of activation of protein kinase C (PKC) on cAMP-dependent signaling by structurally related human D1-like dopaminergic receptors. Human embryonic kidney 293 (HEK293) cells expressing D1 or D5 receptors were pretreated with phorbol-12-myristate-13-acetate (PMA), a potent activator of PKC, followed by analysis of dopamine-mediated receptor activation using whole cell cAMP assays. Unpredictably, PKC activation had completely opposite effects on D1 and D5 receptor signaling. PMA dramatically augmented agonist-evoked D1 receptor signaling, whereas constitutive and dopamine-mediated D5 receptor activation were rapidly blunted. RT-PCR and immunoblotting analyses showed that phorbol ester-regulated PKC isozymes (conventional: alpha, betaI, betaII, gamma; novel: delta, epsilon, eta, theta) and protein kinase D (PKCmicro) are expressed in HEK293 cells. PMA appears to mediate these contrasting effects through the activation of Ca2+-independent novel PKC isoforms as revealed by specific inhibitors, bisindolylmaleimide I, Gö6976, and Gö6983. The finding that cross-talk between PKC and cAMP pathways can produce such opposite outcomes following the activation of structurally similar D1-like receptor subtypes is novel and further strengthens the view that D1 and D5 receptors serve distinct functions in the mammalian nervous and endocrine systems.
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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".