IgCAMs redundantly control axon navigation in Caenorhabditis elegans
Bibliographic record
Abstract
BACKGROUND: Cell adhesion molecules of the immunoglobulin superfamily (IgCAMs) form one of the largest and most diverse families of adhesion molecules and receptors in the nervous system. Many members of this family mediate contact and communication among neurons during development. The Caenorhabditis elegans genome contains a comparatively small number of IgCAMs, most of which are evolutionarily conserved and found across all animal phyla. Only some of these have been functionally characterized so far. RESULTS: We systematically analyzed previously uncharacterized IgCAMs in C. elegans. Green fluorescent protein reporter constructs of 12 IgCAMs revealed that expression generally is not confined to a single tissue and that all tissues express at least one of the IgCAMs. Most IgCAMs were expressed in neurons. Within the nervous system significant overlap in expression was found in central components of the motor circuit, in particular the command interneurons, ventral cord motoneurons as well as motoneurons innervating head muscles. Sensory neurons are underrepresented among the cells expressing these IgCAMs. We isolated mutations for eight of the genes showing neuronal expression. Phenotypic analysis of single mutants revealed limited neuronal defects, in particular axon navigation defects in some of the mutants. Systematic genetic interaction studies uncovered two cases of functional overlap among three and four genes, respectively. A strain combining mutations in all eight genes is viable and shows no additional defects in the neurons that were analyzed, suggesting that genetic interactions among those genes are limited. CONCLUSION: Genetic interactions involving multiple IgCAMs affecting axon outgrowth demonstrate functional overlap among IgCAMs during nervous system development.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".