Comparative localization of two serotonin receptors and sensorin in the central nervous system ofAplysia californica
Bibliographic record
Abstract
Aplysia californica is a powerful model for understanding the cellular and molecular mechanisms underlying modulation of neuronal plasticity and learning. In the central nervous system of Aplysia, serotonin is associated with various behaviors. For example, it induces short-, intermediate-, and long-term synaptic changes in sensory neurons during learning and inhibits the afterdischarge of the bag cells that initiate egg-laying behavior. Little is known about the nature and contribution of serotonin receptors involved in the numerous serotonin-mediated physiological responses in Aplysia. Recently, two G(i)-coupled serotonin receptors (5-HT(ap1) and 5-HT(ap2)) were cloned. We now report that, by using in situ hybridization to express the profile of these receptors, we are able to gain critical insight into their roles in the behavior of Aplysia. We compared their distribution to that of sensorin-A, a peptide specifically found in sensory neurons. We wished to determine their involvement in some simple forms of behavioral modifications. 5-HT(ap1) and 5-HT(ap2) mRNAs are expressed in all ganglia of the Aplysia central nervous system. Stronger signal was observed with the 5-HT(ap2) antisense probe than with the 5-HT(ap1) antisense probe. Notably, mRNA coding for the receptors was found in several identified neurons, in the bag cells, in characterized serotonergic neurons, and in neurons of the mechanosensory clusters that expressed sensorin. We also observed heterogeneity of receptor expression between R2 and LPl1 and among neurons of a single cluster of sensory neurons. These results suggest that 5-HT(ap1) and 5-HT(ap2) receptors may regulate the response to serotonin and/or its release in several neurons.
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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) | 0.000 | 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".