Building bridges for oocyte growth: regulation of C. elegans germline architecture and function by oriented cell divisions
Bibliographic record
Abstract
In most animals, the growth of oocytes depends on the delivery of cytoplasm from other germ cells ("nurse" cells) via cytoplasmic bridges. In some cases, such as in mice and Drosophila, these bridges are formed via incomplete cytokinesis and connect the germ cells to the oocyte directly. In other animals, like the nematode Caenorhabditis elegans (C. elegans), germ cells are connected to an anucleate core of cytoplasm, termed the rachis, that supplies materials to the oocyte. This difference in germline architecture poses an interesting challenge for tissue development. Whereas in the first case, stabilization of the cytokinetic ring between dividing germ cells produces the final organization, with the total number of cytoplasmic bridges being one fewer than the total number of germ cells; in the second scenario, germ cell division must produce two daughter cells each with their own connection to the rachis, with the total number of cytoplasmic bridges being equal to the number of germ cells. The cellular and molecular mechanisms that enable germ cells to form and maintain this latter type of architecture are incompletely understood but have been under increasing scrutiny over the last years. Here we review the recent progress in understanding C. elegans germline development from a tissue architecture perspective.
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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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".