Neuronal diversity of neuropeptide signaling, including galanin, in the mouse locus coeruleus
Bibliographic record
Abstract
The locus coeruleus (LC) is a small nucleus in the pons from which ascending and descending projections innervate major parts of the central nervous system. Its major transmitter is norepinephrine (NE). This system is evolutionarily conserved, including in humans, and its functions are associated with wakefulness and related to disorders, such as depression. Here, we performed single-cell ribonucleic acid-sequencing (RNA-seq) to subdivide neurons in the LC (24 clusters in total) into 3 NE, 17 glutamate, and 5 γ-aminobutyric acid (GABA) subtypes, and to chart their neuropeptide, cotransmitter, and receptor profiles. We found that NE neurons expressed at least 19 neuropeptide transcripts, notably galanin ( Gal ) but not Npy , and >30 neuropeptide receptors. Among the galanin receptors, Galr1 was expressed in ~19% of NE neurons, as was also confirmed by in situ hybridization. Unexpectedly, Galr1 was highly expressed in GABA neurons surrounding the NE ensemble. Patch-clamp electrophysiology and cell-type-specific Ca 2+ -imaging using GCaMP6s revealed that a GalR1 agonist inhibits up to ~35% of NE neurons. This effect is direct and does not rely on feed-forward GABA inhibition. Our results define a role for the galanin system in NE functions, and a conceptual framework for the action of many other peptides and their receptors.
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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 | 0.001 | 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".