Recovery from supercooling, freezing, and cryopreservation stress in larvae of the drosophilid fly, Chymomyza costata
Bibliographic record
Abstract
Abstract Physiological adjustments accompanying insect cold acclimation prior to cold stress have been relatively well explored. In contrast, recovery from cold stress received much less attention. Here we report on recovery of drosophilid fly larvae (Chymomyza costata) from three different levels of cold stress: supercooling to −10 °C, freezing at −30 °C, and cryopreservation at −196 °C. Analysis of larval CO2 production suggested that recovery from all three cold stresses requires access to additional energy reserves to support cold-injury repair processes. Metabolomic profiling (targeting 41 metabolites using mass spectrometry) and custom microarray analysis (targeting 1,124 candidate mRNA sequences) indicated that additional energy was needed to: clear by-products of anaerobic metabolism, deal with oxidative stress, re-fold partially denatured proteins, and remove damaged proteins, complexes and/or organelles. Metabolomic and transcriptomic recovery profiles were closely similar in supercooled and frozen larvae, most of which successfully repaired the cold injury and metamorphosed into adults. In contrast, the majority of cryopreseved larvae failed to proceed in ontogenesis, showed specific metabolic perturbations suggesting impaired mitochondrial function, and failed to up-regulate a set of 116 specific genes potentially linked to repair of cold injury.
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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".