Sensory Ciliogenesis in<i>Caenorhabditis elegans</i>: Assignment of IFT Components into Distinct Modules Based on Transport and Phenotypic Profiles
Bibliographic record
Abstract
Sensory cilium biogenesis within Caenorhabditis elegans neurons depends on the kinesin-2-dependent intraflagellar transport (IFT) of ciliary precursors associated with IFT particles to the axoneme tip. Here we analyzed the molecular organization of the IFT machinery by comparing the in vivo transport and phenotypic profiles of multiple proteins involved in IFT and ciliogenesis. Based on their motility in wild-type and bbs (Bardet-Biedl syndrome) mutants, IFT proteins were classified into groups with similar transport profiles that we refer to as "modules." We also analyzed the distribution and transport of fluorescent IFT particles in multiple known ciliary mutants and 49 new ciliary mutants. Most of the latter mutants were snip-SNP mapped and one, namely dyf-14(ks69), was cloned and found to encode a conserved protein essential for ciliogenesis. The products of these ciliogenesis genes could also be assigned to the aforementioned set of modules or to specific aspects of ciliogenesis, based on IFT particle dynamics and ciliary mutant phenotypes. Although binding assays would be required to confirm direct physical interactions, the results are consistent with the hypothesis that the C. elegans IFT machinery has a modular design, consisting of modules IFT-subcomplex A, IFT-subcomplex B, and a BBS protein complex, in addition to motor and cargo modules, with each module contributing to distinct functional aspects of IFT or ciliogenesis.
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 | 0.001 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".