Paraquat and psychological stressor interactions as pertains to Parkinsonian co-morbidity
Bibliographic record
Abstract
A number of epidemiological and experimental studies have implicated the non-selective herbicide, paraquat, in the development of sporadic Parkinson's disease (PD). While preclinical research has focused mainly on elucidating the nigrostriatal effects of paraquat, relatively little data are available concerning non-motor brain systems and inflammatory immune processes (which have been implicated in PD). Hence, in the present study, we sought to take a multi-system approach to characterize the influence of paraquat upon extra-nigrostriatal brain regions, as well ascertain whether the impact of the pesticide might be enhanced in the context of chronic intermittent stressor exposure. Our findings support the contention that paraquat itself acted as a systemic stressor, with the pesticide increasing plasma corticosterone, as well as altering neurochemical activity in the locus coeruleus, paraventricular nucleus of the hypothalamus, nucleus accumbens, dorsal striatum, and central amygdala. However, with the important exception striatal dopamine turnover, the stressor treatment did not further augment these effects. Additionally, paraquat altered inter-cytokine correlations and, to a lesser extent, circulating cytokine levels, and concomitant stress exposure modulated some of these effects. Finally, paraquat provoked significant (albeit modest) reductions of sucrose preference and weight gain, hinting at possible anhendonic-like or sickness responses. These data suggest that, in addition to being a well known oxidative stress generator, paraquat can act as a systemic stressor affecting hormonal and neurochemical activity, but largely not interacting with a concomitant stressor regimen.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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".