Freeze-tolerant crickets fortify their actin cytoskeleton in fat body tissue
Bibliographic record
Abstract
Animals that overwinter in temperate climates must prevent or repair damage to their cells to survive winter, but we know little about how they protect cellular structure at the cytoskeletal level. Both chilling (no ice formation) and freezing (ice formation) are hypothesized to cause substantial challenges to cell structure and the cytoskeleton. The spring field cricket Gryllus veletis becomes freeze tolerant following a 6 week acclimation to autumn-like conditions, during which they differentially express multiple cytoskeleton-related genes. We tested the hypothesis that G. veletis alter their cytoskeleton during acclimation to support maintenance of cytoskeletal structure during freezing and thawing. We used immunocytochemistry and confocal microscopy to characterize changes in microfilaments (F-actin, a polymer of G-actin) and microtubules (a polymer of α- and β-tubulin) in three tissues. While we saw no effect of acclimation on microtubules, crickets increased the abundance of microfilaments in fat body tissue and Malpighian tubules. When we chilled or froze these freeze-tolerant crickets, there was no apparent damage to the actin or tubulin cytoskeleton in fat body tissue, but there was decreased cytoskeleton abundance in Malpighian tubules. When we froze freeze-intolerant (unacclimated) crickets, microfilament abundance decreased in fat body tissue, while microfilaments were unaffected by chilling to the same subzero temperature. Our study shows that freeze-tolerant crickets are able to prevent or rapidly repair ice-induced damage to the actin cytoskeleton in fat body tissue, likely as a result of preparatory changes in advance of freezing, i.e. during acclimation. We suggest future directions examining the mechanisms that underlie these structural changes.
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 | 0.000 |
| 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".