Hardening trumps acclimation in improving cold tolerance of <i>Drosophila melanogaster</i> larvae
Bibliographic record
Abstract
Abstract Chill‐susceptible insects are able to improve their survival of acute cold exposure over both the short term (i.e. hardening at a relatively severe temperature) and longer term (i.e. acclimation responses at milder temperatures over a longer time frame). However, the mechanistic overlap of these responses is not clear. Four larval stages of four different strains of Drosophila melanogaster are used to test whether low temperature acclimation (10 °C for 48 h) improves the acute cold tolerance (LT 90 , ∼2 h) of larvae, and whether acclimated larvae still show hardening responses after brief exposures to nonlethal cold or heat, or a combination of the two. Acclimation results in increased cold tolerance in three of four strains, with variation among instars. However, if acclimation is followed by hardening pre‐treatments, there is no improvement in acute cold survival. It is concluded that short‐term thermal responses (e.g. hardening) may be of more ecological relevance to short‐lived life stages such as larvae, and that the mechanisms of low temperature hardening and acclimation in D. melanogaster may be antagonistic, rather than complementary.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".