Involvement of Protein Kinase A in Patterning of the Mouse Somatosensory Cortex
Bibliographic record
Abstract
Patterning of the mouse somatosensory cortex is unusually evident because of the presence of a "barrel field." Presynaptic serotonin and postsynaptic glutamate receptors regulate barrel formation, but little is known of the intracellular signaling pathways through which they act. To determine whether protein kinase A (PKA) plays a role in the development of the barrel field, we examined five viable PKA subunit-specific knock-out (KO) mouse lines for barrel field abnormalities. Barrels are present in these mice, but those lacking the RIIbeta subunit display significantly reduced contrast between the cell densities of barrel hollows and sides compared with wild-type animals. Thalamocortical afferent segregation in the posterior medial barrel subfield appeared normal, suggesting a postsynaptic site of gene action for the RIIbeta protein. Immunoelectron microscopy confirmed that RIIbeta was selectively localized to dendrites and dendritic spines. Mice lacking RIIbeta show reduced glutamate receptor A (GluRA) subunit insertion into the postsynaptic density in postnatal day 7 somatosensory cortex; however, GluRA KO mice developed normal barrels. Our results clearly demonstrate a role for postsynaptic PKA signaling pathways in barrel differentiation. They also demonstrate a clear dissociation between the regulation of GluRA trafficking by PKA and its role in barrel formation. Finally, although a role for PKA downstream of cAMP cannot be ruled out, these data suggest that PKA may not be the principle downstream target because none of the mutants showed a barrelless phenotype similar to that observed in adenylate cyclase type 1 KO mice. These results give insight into activity-dependent mechanisms that regulate barrel formation.
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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 | 0.001 | 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) | 0.001 | 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".