Increased abundance of <i>Frost</i> mRNA during recovery from cold stress is not essential for cold tolerance in adult <i> <scp>D</scp> rosophila melanogaster </i>
Bibliographic record
Abstract
Frost (Fst) is a candidate gene associated with the response to cold in Drosophila melanogaster because Fst mRNA accumulation increases during recovery from low temperature exposure. We investigated the contribution of Fst expression to chill-coma recovery time, acute cold tolerance and rapid cold hardening (RCH) in adult D. melanogaster by knocking down Fst mRNA expression using GAL4/UAS-mediated RNA interference. In this experiment, four UAS-Fst and one tubulin-GAL4 lines were used. We predicted that if Fst is essential for cold tolerance phenotypes, flies with low Fst mRNA levels should be less cold tolerant than flies with normal levels of cold-induced Fst mRNA. Cold-induced Fst abundance and recovery time from chill-coma were not negatively correlated in male or female flies. Survival of 2 h exposures to sub-zero temperatures in Fst knockdown lines was not lower than that in a control line. Moreover, a low temperature pretreatment increased survival of severe cold exposure in flies regardless of Fst abundance level during recovery from cold stress, suggesting that Fst expression is not essential for RCH. Thus, cold-induced Fst accumulation is not essential for cold tolerance measured as chill-coma recovery time, survival to acute cold stress and RCH response in adult D. melanogaster.
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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".