Kirrel2 is differentially required in populations of olfactory sensory neurons for the targeting of axons in the olfactory bulb
Bibliographic record
Abstract
The formation of olfactory maps in the olfactory bulb (OB) is crucial for the control of innate and learned mouse behaviors. Olfactory sensory neurons (OSNs) expressing a specific odorant receptor project axons into spatially conserved glomeruli within the OB and synapse onto mitral cell dendrites. Combinatorial expression of members of the Kirrel family of cell adhesion molecules has been proposed to regulate OSN axonal coalescence; however, loss-of-function experiments have yet to establish their requirement in this process. We examined projections of several OSN populations in mice that lacked either Kirrel2 alone, or both Kirrel2 and Kirrel3. Our results show that Kirrel2 and Kirrel3 are dispensable for the coalescence of MOR1-3-expressing OSN axons to the most dorsal region (DI) of the OB. In contrast, loss of Kirrel2 caused MOR174-9- and M72-expressing OSN axons, projecting to the DII region, to target ectopic glomeruli. Our loss-of-function approach demonstrates that Kirrel2 is required for axonal coalescence in subsets of OSNs that project axons to the DII region and reveals that Kirrel2/3-independent mechanisms also control OSN axonal coalescence in certain regions of the OB.
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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 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".