A screen of kinase inhibitors reveals a potential role of Chk1 in regulating <i>Hydra</i> head regeneration and maintenance
Bibliographic record
Abstract
The cnidarian Hydra possesses remarkable regenerative capabilities which allow it to regrow lost or damaged body parts in a matter of days. Given that many key regulators of regeneration and development are evolutionarily conserved, Hydra is a valuable model system for studying the fundamental molecular mechanisms underlying these processes. In the past, kinase inhibitors have been useful tools for determining the role of conserved signaling pathways in Hydra regeneration and patterning. Here, we present a systematic screen of a commercially available panel of kinase inhibitors for their effects on Hydra regeneration. Isolated Hydra gastric segments were exposed to 5 &micro;M of each kinase inhibitor and regeneration of the head and foot regions were scored over a period of 96 hours. Of the 80 kinase inhibitors tested, 28 compounds resulted in abnormal regeneration. We directed our focus to the checkpoint kinase 1 (Chk1) inhibitor, SB 218078, considering the role of Chk1 in G2 checkpoint regulation and the importance of G2-paused cells in Hydra regeneration. We found that Hydra exposed to SB 218078 were unable to regenerate the head and maintain head-specific structures. Furthermore, SB 218078-treated Hydra displayed a reduction in the relative proportion of epithelial cells; however, no differences were seen for interstitial stem cells or their derivatives. Lastly, exposure to SB 218078 appeared to have no impact on the level of mitosis or apoptosis. Overall, our study demonstrates the feasibility of kinase inhibitor screens for studying Hydra regeneration processes and highlights the possible role for Hydra Chk1 in head regeneration and maintenance.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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) | 0.000 | 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".