Altered synaptic organization in the mushroom bodies of honey bees exposed as foragers to the pesticide fipronil
Bibliographic record
Abstract
The pesticide fipronil is a GABA receptor antagonist that induces hyperexcitability in the insect nervous system. Its use is controversial because unintentional fipronil exposure may contribute to the ongoing global decline of pollinator populations. Sublethal doses of fipronil have been tentatively linked to reduced colony fitness and impaired learning in the western honey bee, Apis mellifera. The mushroom bodies, insect brain centers important for association learning and memory, contain fipronil-sensitive receptors and may therefore be directly affected by this pesticide. We investigated the synaptic organization of the mushroom bodies in worker honey bees exposed to fipronil using immunolabeling for a pre-synaptic marker and laser scanning confocal microscopy. Exposure of honey bee foragers to fipronil at a feasible field-realistic (1 ppb) concentration decreased the estimated density of immunolabeled microglomerular synaptic complexes in the lip and collar neuropil regions of the mushroom bodies. Effects were also evident after lower (0.1 ppb) and higher (4 ppb) exposures. Other indicators of synaptic organization (bouton number, surface area) were altered by exposure to fipronil in a dose-dependent fashion. These results indicate that sublethal doses of fipronil can result in atypical synaptic organization in the mushroom bodies of honey bees and suggest a mechanism by which fipronil, through perturbation of mushroom body-dependent functions, might diminish honey bee colony survival.
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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".