The regulation of heat shock proteins in response to dehydration in Xenopus laevis
Bibliographic record
Abstract
African clawed frogs (Xenopus laevis) endure bouts of severe drought in their natural habitats and survive the loss of approximately 30% of total body water due to dehydration. To investigate molecular mechanisms employed by X. laevis during periods of dehydration, the heat shock protein response, a vital component of the cytoprotective stress response, was characterized. Using western immunoblotting and multiplex technology, the protein levels of HSP27, HSP40, HSP60, HSP70, HSC70, and HSP90 were quantified in the liver, skeletal muscle, kidney, lung, and testes from control frogs and those that underwent medium or high dehydration (~16 or ~30% loss of total body water). Dehydration increased HSP27 (1.45-1.65-fold) in the kidneys and lungs, and HSP40 (1.39-2.50-fold) in the liver, testes, and skeletal muscle. HSP60 decreased in response to dehydration (0.43-0.64 of control) in the kidneys and lungs. HSP70 increased in the liver, lungs, and testes (1.39-1.70-fold) during dehydration, but had a dynamic response in the kidneys (levels increased 1.57-fold with medium dehydration, but decreased to 0.56 of control during high dehydration). HSC70 increased in the liver and kidneys (1.20-1.36-fold), but decreased in skeletal muscle (0.27-0.55 of control) during dehydration. Lastly, HSP90 was reduced in the kidney, lung, and skeletal muscle (0.39-0.69 of control) in response to dehydration, but rose in the testes (1.30-fold). Overall, the results suggest a dynamic tissue-specific heat shock protein response to whole body dehydration in X. laevis.
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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 | 0.001 | 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".