The Genetics of Axon Guidance and Axon Regeneration in <i>Caenorhabditis elegans</i>
Bibliographic record
Abstract
The correct wiring of neuronal circuits depends on outgrowth and guidance of neuronal processes during development. In the past two decades, great progress has been made in understanding the molecular basis of axon outgrowth and guidance. Genetic analysis in Caenorhabditis elegans has played a key role in elucidating conserved pathways regulating axon guidance, including Netrin signaling, the slit Slit/Robo pathway, Wnt signaling, and others. Axon guidance factors were first identified by screens for mutations affecting animal behavior, and by direct visual screens for axon guidance defects. Genetic analysis of these pathways has revealed the complex and combinatorial nature of guidance cues, and has delineated how cues guide growth cones via receptor activity and cytoskeletal rearrangement. Several axon guidance pathways also affect directed migrations of non-neuronal cells in C. elegans, with implications for normal and pathological cell migrations in situations such as tumor metastasis. The small number of neurons and highly stereotyped axonal architecture of the C. elegans nervous system allow analysis of axon guidance at the level of single identified axons, and permit in vivo tests of prevailing models of axon guidance. C. elegans axons also have a robust capacity to undergo regenerative regrowth after precise laser injury (axotomy). Although such axon regrowth shares some similarities with developmental axon outgrowth, screens for regrowth mutants have revealed regeneration-specific pathways and factors that were not identified in developmental screens. Several areas remain poorly understood, including how major axon tracts are formed in the embryo, and the function of axon regeneration in the natural environment.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".