Functional characterization of a novel serotonin receptor (5‐HT<sub>ap2</sub>) expressed in the CNS of <i>Aplysia californica</i>
Bibliographic record
Abstract
Serotonin has been shown to be a neuromodulator in the Aplysia californica CNS. The diversity of serotonin actions is due to the existence of several different receptor subtypes. In this study we report the cloning of a full-length cDNA, coding for a novel serotonin receptor (5-HTap2). The receptor protein bears the characteristics of G protein-coupled receptors. It shares 68% and 34% of its amino acid sequence identity with the 5-HTlym receptor from Lymnaea stagnalis and the mammalian 5-HT1A receptor, respectively. When transfected in HEK 293 cells, 5-HTap2 was negatively coupled to adenylate cyclase. Ligand binding analysis indicated that the order of potencies of various drugs for the inhibition of [3H]LSD binding was: methiothepin > metergoline > 5-CT > PAPP > 5-HT > ketanserin > NAN-190 > 8-OH-DPAT > clozapine. RT-PCR amplification of RNA isolated from different tissues indicated that this receptor is expressed in the CNS and in bag cells. The expression of 5-HTap2 restricted to the CNS suggests an important role for this receptor in the modulation of neuronal functions in Aplysia. Moreover, the high expression of 5-HTap2 in the bag cells, associated with its pharmacological profile, suggests that this receptor may be implicated in modulating the afterdischarge during the egg-laying behavior.
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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".