Identification of a novel dehydration responsive gene, <i>drp10</i>, from the African clawed frog, <i>Xenopus laevis</i>
Bibliographic record
Abstract
During periods of environmental stress a number of different anuran species employ adaptive strategies to promote survival. Our study found that in response to dehydration (i.e., loss of total body water content), the African clawed frog (Xenopus laevis) increased the expression of a novel gene (drp10) that encodes a structural homolog of the freeze-responsive FR10 protein found in wood frogs. Similar to FR10, the DRP10 protein was found to also contain a highly conserved N-terminal cleavable signal peptide. Furthermore, DRP10 was found to have high structural homology to the available crystal structures of type A and E apolipoproteins in Homo sapiens, and a type IV LS-12 anti-freeze protein in the longhorn sculpin, Myoxocephalus octodecemspinosis. In response to dehydration, the transcript expression of drp10 was found to increase 1.52 ± 0.16-fold and 1.97 ± 0.11-fold in response to medium (15%) and high (30%) dehydration stresses in the liver tissue of X. laevis, respectively, while drp10 expression increased 2.12 ± 0.12-fold and 1.46 ± 0.16-fold in kidney tissue. Although the molecular function of both dehydration-responsive DRP10 and the freeze-responsive FR10 have just begun to be elucidated, it is likely that both are frog-specific proteins that likely share a similar purpose during water-related stresses.
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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".