Protocadherin-αC2 is required for diffuse projections of serotonergic axons
Bibliographic record
Abstract
Serotonergic axons extend diffuse projections throughout various brain areas, and serotonergic system disruption causes neuropsychiatric diseases. Loss of the cytoplasmic region of protocadherin-α (Pcdh-α) family proteins, products of the diverse clustered Pcdh genes, causes unbalanced distributions (densification and sparsification) of serotonergic axons in various target regions. However, which Pcdh-α member(s) are responsible for the phenotype is unknown. Here we demonstrated that Pcdh-αC2 (αC2), a Pcdh-α isoform, was highly expressed in serotonergic neurons, and was required for normal diffusion in single-axon-level analyses of serotonergic axons. The loss of αC2 from serotonergic neurons, but not from their target brain regions, led to unbalanced distributions of serotonergic axons. Our results suggest that αC2 expressed in serotonergic neurons is required for serotonergic axon diffusion in various brain areas. The αC2 extracellular domain displays homophilic binding activity, suggesting that its homophilic interaction between serotonergic axons regulates axonal density via αC2's cytoplasmic domain.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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".