Yorkie is required to restrict the injury responses in planarians
Bibliographic record
Abstract
Abstract Regeneration requires the precise integration of cues that initiate proliferation, direct differentiation, and ultimately re-pattern tissues to the proper size and scale. Yet how these processes are integrated with wounding cues remains relatively unknown. The freshwater planarian, Schmidtea mediterranea , is an ideal model to study the stereotyped proliferative and transcriptional responses to injury due to its high capacity for regeneration. Here, we characterize the effector of the Hippo signalling cascade, yorkie , during planarian regeneration and its role in restricting early injury responses. In yki(RNAi) regenerating animals, wound responses are hyper-activated; the bimodal proliferation kinetics are heighted and prolonged, while the transcriptional injury responses are similarly augmented with dysregulated temporal patterns. We also uncovered novel wound-induced genes by RNAseq that are primarily associated with tissue patterning. Indeed, a high proportion of non-wound- and wound-induced patterning molecules are mis-expressed in yki(RNAi) , which we demonstrate is in part due to an expanded muscle cell population. These altered injury responses have consequential effects on regenerative outcomes, specifically sensing the size of a given injury and appropriately scaling organ and tissue sizes. Taken together, our results suggest that yki functions as a key node to integrate the injury responses of proliferation, apoptosis, injury-induced transcription, and patterning to coordinate regeneration.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 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 teacher head, 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".