The ULK1 kinase, a necessary component of the pro-regenerative and anti-aging machinery in Hydra
Bibliographic record
Abstract
Hydra vulgaris (Hv) has a high regenerative potential and negligible senescence, as its stem cell populations divide continuously. In contrast, the cold-sensitive H. oligactis (Ho_CS) rapidly develop an aging phenotype under stress, with epithelial stem cells deficient for autophagy, unable to maintain their self-renewal. Here we tested in aging, non-aging and regenerating Hydra the activity and regulation of the ULK1 kinase involved in autophagosome formation. In vitro kinase assays show that human ULK1 activity is activated by Hv extracts but repressed by Ho_CS extracts, reflecting the ability or inability of their respective epithelial cells to initiate autophagosome formation. The factors that keep ULK1 inactive in Ho_CS remain uncharacterized. Hv_Basel1 animals exposed to the ULK1 inhibitor SBI-0206965 no longer regenerate their head, indicating that the sustained autophagy flux recorded in regenerating Hv_AEP2 transgenic animals expressing the DsRed-GFP-LC3A autophagy tandem sensor is necessary. The SBI-0206965 treatment also alters the contractility of intact Hv_Basel1 animals, and leads to a progressive reduction of animal size in Hv_AEP2, similarly to what is observed in ULK1(RNAi) animals. We conclude that the evolutionarily-conserved role of ULK1 in autophagy initiation is crucial to maintain a dynamic homeostasis in Hydra, which supports regeneration efficiency and prevents aging.
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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".