What's hot: the enhancing effects of thermal stress on long-term memory formation in <i>Lymnaea stagnalis</i>
Bibliographic record
Abstract
The pond snail, Lymnaea stagnalis, naturally inhabits slow flowing, shallow and stagnant environments in the northern temperate zone. Consequently, it will experience wide temperature fluctuations dependent on prevailing weather conditions. We hypothesize that periods of warming act as a thermal stressor to alter memory formation. Snails were exposed to an acute 1 h period of 30°C pond water and we determined how memory formation following operant conditioning of aerial respiration was affected. In the snails used here (Dutch strain), a single 0.5 h training session (TS) results in intermediate-term (3 h) but not long-term memory (LTM). Applying the thermal stressor during training caused memory enhancement (i.e. LTM lasting 24 h). However, the breathing rate also increased in warm water, which might explain the enhanced memory. Therefore, we applied the thermal stressor (1 h at 30°C) up to 4 h before or 1 h after training. This did not alter baseline breathing rate during the period when snails would experience training. However, the thermal stressor whether experienced prior to or following the single TS, resulted in an enhanced memory that persisted up to 48h (i.e. LTM). We conclude that memory enhancement is due to the stress associated with the thermal stimulus.
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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) | 0.001 | 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".