Imaging of cAMP Levels and Protein Kinase A Activity Reveals That Retinal Waves Drive Oscillations in Second-Messenger Cascades
Bibliographic record
Abstract
Recent evidence demonstrates that low-frequency oscillations of intracellular calcium on timescales of seconds to minutes drive distinct aspects of neuronal development, but the mechanisms by which these calcium transients are coupled to signaling cascades are not well understood. Here we test the hypothesis that spontaneous electrical activity activates protein kinase A (PKA). We use live-cell indicators to observe spontaneous and evoked changes in cAMP levels and PKA activity in developing retinal neurons. Expression of cAMP and PKA indicators in neonatal rat retinal explants reveals spontaneous oscillations in PKA activity that are temporally correlated with spontaneous depolarizations associated with retinal waves. In response to short applications of forskolin, dopamine, or high-potassium concentration, we image an increase in cAMP levels and PKA activity, indicating that this second-messenger pathway can be activated quickly by neural activity. Depolarization-evoked increases in PKA activity were blocked by the removal of extracellular calcium, indicating that they are mediated by a calcium-dependent mechanism. These findings demonstrate for the first time that spontaneous activity in developing circuits is correlated with activation of the cAMP/PKA pathway and that PKA activity is turned on and off on the timescale of tens of seconds. These results show a link between neural activity and an intracellular biochemical cascade associated with plasticity, axon guidance, and neural differentiation.
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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".