Expression of heat‐shock protein 70 during limb development and regeneration in the axolotl
Bibliographic record
Abstract
Urodele amphibians (e.g., axolotls) have the unique ability, among vertebrates, to regenerate perfectly many parts of their body after amputation. The limb has been the most widely studied regenerating structure in these organisms and provides an ideal model in which to understand how vertebrates can regenerate complex tissues. The present study focuses on Hsp-70, a member of the stress-related heat-shock protein family. This protein is normally induced after a stress or trauma such as heat-shock, ultraviolet irradiation, or wounding. Thus, studying its expression during axolotl limb regeneration, a response to an important traumatic event (amputation), is of great interest to further understand how the regenerative process is mediated. Using molecular biology and biochemical techniques, we have characterized both the spatiotemporal and quantitative expression patterns of Hsp-70 in axolotl development and regeneration. Our results show that Hsp-70 is expressed and regulated during axolotl development as in other vertebrates. Our data also demonstrate an up-regulation of the RNA transcript for Hsp-70 during limb regeneration as early as 24 hr after amputation that is maintained up to early differentiation. We also demonstrate a similar pattern of expression for the protein during regeneration. Finally, we show that axolotl Hsp-70 is induced threefold after heat-shock as observed in other vertebrates.
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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".