Distribution of muscarinic acetylcholine receptor mRNA in the brain of the weakly electric fish <i>Apteronotus leptorhynchus</i>
Bibliographic record
Abstract
Various neuromodulators have been shown to be involved in shaping the sensory information available to the brain. Acetylcholine (ACh) modulation, through muscarinic receptors, is a particularly widespread mechanism of controlling sensory information transmission. The precise effects of ACh modulation depend on the subtype of muscarinic ACh receptors that are activated. In weakly electric fish, previous work suggested a role of ACh, via muscarinic receptors, in the modulation of information transmission in the electrosensory lateral line lobe (ELL) of the hindbrain. In this study, we determined which muscarinic receptor (mAChR) subtypes are present in the brain of Apteronotus leptorhynchus as well as their spatial distribution. We partially cloned three subtypes of muscarinic receptors (mAChR2, -3, and -4) from brain tissue of A. leptorhynchus and used in situ hybridization in transverse sections of the brain to determine their distributions. Sites labeled for the three muscarinic receptor mRNAs were found in various brain regions devoted to the processing of different sensory modalities. The mRNA probes for the three receptor types showed differential distribution but also overlapping presence of two or more receptors in particular nuclei. In addition to the presence of mAChR3 in the ELL region, electrosensory nuclei including the nucleus praeeminentialis, dorsal torus semicircularis and optic tectum showed expression of one or more mAChRs. Thus, the overall pattern of mAChR expression found is in agreement with mAChR expression in other species, with additional presence evident in specialized regions of the electrosensory system, which suggests an important modulating role of ACh in this sensory modality.
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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".