Molecular genetic analysis of germline stem cell quiescence in «Caenorhabditis elegans»
Bibliographic record
Abstract
Cell division must be tightly regulated through both developmental programming and environmental conditions.One of the central foci of cancer research over the last decade has been the analysis of stem cells and their corresponding niche and how these specialized cells contribute to tumourigenesis.The germline stem cells of Caenorhabditis elegans, which are quiescent upon induction of dauer, were used here to study genetic responses in cell cycle regulation to environmental conditions during larval development.Global RNAi screening implicated a number of genes involved in regulating polarity and cytoskeletal function in the maintenance of cellular arrest in nonpolarized germ cells.Further, the Notch signaling pathway, which promotes mitotic cell divisions in the germ cells, was shown to be inactive during dauer due to a novel mechanism involving Notch receptor relocalization.Further investigations into these pathways will advance our understanding of how these mechanisms have an impact in human disease.I would also like to thank the members of the Roy Lab for being supportive of me these past two years.Thanks to Chris St-Francois for his friendship and support.A big thanks to Shaolin Li and Yu Lu for their continued technical support.I am grateful to have worked with Julie Mantovani, Emilie Demoinet and Meng Xie and to have learned from their expertise.I am
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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".