Hot and cold exposure triggers distinct transcriptional and behavioral responses in laboratory-inbred pond snails
Bibliographic record
Abstract
Animals exhibit remarkable behavioral and molecular adaptations to cope with thermal stressors, which are crucial for survival in variable environments that are exacerbated by climate change. Aquatic poikilotherms like our model organism—the pond snail Lymnaea stagnalis —face significant challenges due to their dependence on external temperatures. Our study provides valuable insights into the different behavioral and molecular responses of lab-inbred snails to cold and heat shock stressors (i.e., 4 °C and 30 °C), particularly in the context of learning and memory formation. We found that while short-term (1 h) cold exposure transiently upregulated the expression levels of HSP70 and HSP40 in the snail's central ring ganglia, prolonged cold exposure (24 h) resulted in a significant downregulation of LymMIPII and an upregulation of LymMIPR. These data suggest, albeit at the transcriptional level, the existence of a negative feedback loop necessary for sustaining cellular functions when metabolic demands might shift towards conserving energy during prolonged cold exposure. At the behavioral level, we found that, compared to heat shock, cold exposure did not result in a Garcia effect (i.e., a “special form” of conditioned taste aversion). The difference in memory outcomes was associated with changes in the expression levels of selected targets involved in neuronal plasticity and the stress response. While both cold and heat shock upregulated the HSP levels in the snail's central ring ganglia, cold exposure did not affect the expression levels of the neuroplasticity genes LymGRIN1 and LymCREB1, contrasting with heat shock's neurogenic effects. Overall, this study provides insights into L . stagnalis 's adaptive responses to thermal stressors, emphasizing different molecular strategies for coping with heat versus cold challenges in aquatic environments. These findings contribute to our understanding of thermal biology and stress physiology in aquatic organisms, underscoring the importance of molecular mechanisms in shaping species' resilience in dynamic environments. • Aquatic poikilotherms like L. stagnalis face water temperature changes. • Short-term cold exposure upregulates HSP mRNA levels: an immediate response to maintain cellular homeostasis. • Long-term cold exposure induces an ‘energy-saving’ state by regulating insulin signaling. • Heat stress but not cold stress induces a Garcia effect in inbred snails. • L. stagnalis shows different molecular strategies for coping with heat versus cold challenges.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".