Common insecticide affects spatial navigation in bats at environmentally-realistic doses
Bibliographic record
Abstract
Abstract Bats are potentially exposed to pesticides via foraging in croplands. Common pesticides like organophosphates are neurotoxic for vertebrates and even low doses can impair essential processes such as locomotion and cognition. These sublethal effects are usually studied using molecular biomarkers with limited ecological relevance. Behavioral studies, in contrast, represent a more informative yet sensitive approach. Spatial navigation, for example, is an ecologically relevant behavior that is modulated by cellular pathways potentially targeted by neurotoxicants. We evaluated whether bats’ ability to memorize and navigate novel spaces was negatively affected by environmental relevant doses of chlorpyrifos, a common organophosphate insecticide. We also tested how the behavioral response correlated with molecular biomarkers. We orally dosed captive big brown bats ( Eptesicus fuscus ) with chlorpyrifos and studied exploratory behavior in two testing arenas. We evaluated similarity of stereotype flight trajectories in a flight tent, and associative memory in a Y-maze. We quantified brain cholinesterase (ChE) activity as a cellular biomarker and employed non-targeted proteomics as molecular biomarkers. Bats exposed to chlorpyrifos were less explorative and made more incorrect choices in the Y-maze, but the consistency of their flight trajectories was unaffected. Exposed bats had 30% lower ChE activity, showed down-regulation of proteins involved in memory (VP37D), learning and sound perception (NOX3). Other important nervous system processes such as synaptic function, plasticity, oxidative stress, and apoptosis were enriched in chlorpyrifos-exposed bats. These results support the sensitivity of behavior as a biomarker of toxicity and the importance of considering other levels of organization to help explain the mechanisms underlying altered behavior due to human activities.
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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 | 0.001 |
| 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".