Temperature during embryonic development has persistent effects on thermal acclimation capacity in zebrafish
Bibliographic record
Abstract
Global warming is intensifying interest in the mechanisms enabling ectothermic animals to adjust physiological performance and cope with temperature change. Here we show that embryonic temperature can have dramatic and persistent effects on thermal acclimation capacity at multiple levels of biological organization. Zebrafish embryos were incubated until hatching at control temperature (T(E) = 27 °C) or near the extremes for normal development (T(E) = 22 °C or 32 °C) and were then raised to adulthood under common conditions at 27 °C. Short-term temperature challenge affected aerobic exercise performance (U(crit)), but each T(E) group had reduced thermal sensitivity at its respective T(E). In contrast, unexpected differences arose after long-term acclimation to 16 °C, when performance in the cold was ∼20% higher in both 32 °C and 22 °C T(E) groups compared with 27 °C T(E) controls. Differences in performance after acclimation to cold or warm (34 °C) temperatures were partially explained by variation in fiber type composition in the swimming muscle. Cold acclimation changed the abundance of 3,452 of 19,712 unique and unambiguously identified transcripts detected in the fast muscle using RNA-Seq. Principal components analysis differentiated the general transcriptional responses to cold of the 27 °C and 32 °C T(E) groups. Differences in expression were observed for individual genes involved in energy metabolism, angiogenesis, cell stress, muscle contraction and remodeling, and apoptosis. Therefore, thermal acclimation capacity is not fixed and can be modified by temperature during early development. Developmental plasticity may thus help some ectothermic organisms cope with the more variable temperatures that are expected under future climate-change scenarios.
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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 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".