Identification and characterization of a novel freezing‐inducible gene, li16, in the wood frog Rana sylvatica
Bibliographic record
Abstract
The wood frog Rana sylvatica survives for weeks during winter hibernation with up to 65% body water frozen as ice. Natural freeze tolerance includes both seasonal and freeze-induced molecular adaptations that control ice formation, deal with long-term ischemia, regulate cell volume changes, and protect macromolecules. This report identifies and characterizes a novel freeze-inducible gene, li16, that codes for a protein of 115 amino acids. Northern blot analysis showed that li16 transcript levels rose quickly during freezing to reach levels 3.7-fold higher than control values after 24 h; immunoblotting showed a parallel 2.4-fold rise in Li16 protein. Regulatory influences on gene expression were assessed. Nuclear runoff assays confirmed that freezing initiated an increase in the rate of li16 transcription, and analysis of signal transduction pathways via in vitro incubation of liver slices implicated a cGMP-mediated pathway in li16 expression. Gene and protein expression in liver was also strongly stimulated by anoxia exposure, whereas the gene was less responsive to dehydration stress. The strong response of li16 to both freezing and anoxia, and the rapid down-regulation of the gene when oxygen was reintroduced, suggest that the Li16 protein may play a role in ischemia resistance during freezing.
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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) | 0.000 | 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 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".