Microtubule dynamics followed through cell differentiation and tissue biogenesis in<i>C. elegans</i>
Bibliographic record
Abstract
Microtubules (MTs) are cytoskeletal filaments essential for many processes in eukaryotic cells. Assembled of tubulin subunits, MTs are dynamic structures that undergo successive and stochastic phases of polymerization and depolymerization, a behavior called dynamic instability. Dynamic instability has been extensively studied in cultured cells and in vitro using cytoplasmic extracts or reconstituted MTs. However, how MTs behave in intact tissues and how their dynamics are affected by or affect tissue function are poorly understood. Recent advances in high-resolution live imaging have helped overcome technical limitation in order to visualize MTs in intact living organisms including Drosophila or Caenorhabditis elegans. We recently took advantage of the well-characterized development, small size and transparency of C. elegans to monitor MT dynamics throughout tissue biogenesis with high spatial and temporal resolution. Using the sex myoblast lineage that generates the egg-laying muscles from 2 mitotic precursors, we identified selective dynamics in precursor versus differentiated cells, and molecular regulation of MT dynamics changes that occur during cell differentiation. We discuss here how this approach led to novel insights into the regulation of MTs dynamics and organization in vivo.
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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 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".