Paraquat Exposure Increases Oxidative Stress Within the Dorsal Striatum of Male Mice With a Genetic Deficiency in One-carbon Metabolism
Bibliographic record
Abstract
Paraquat is an herbicide that is commonly used worldwide. Exposure to paraquat results in Parkinson's disease (PD)-like symptoms including dopaminergic cell loss. Nutrition has also been linked in the pathogenesis of PD, such as reduced levels of folic acid, a B-vitamin, and component of one-carbon metabolism. Within one-carbon metabolism, methylenetetrahydrofolate reductase (MTHFR) catalyzes the irreversible conversion of 5, 10-methylenetetrahydrofolate to 5-methyltetrahydrofolate. A polymorphism in MTHFR (677 C&→T) has been reported in 5%-15% of North American and European human populations. The MTHFR polymorphism is also prevalent in PD patients. The goal of this study was to investigate the impact of paraquat-induced PD-like pathology in the context of reduced levels of MTHFR. Three-month-old male Mthfr+/- mice, which model the MTHFR polymorphism observed in humans, were administered intraperitoneal injections of paraquat (10 mg/kg) or saline 6 times over 3 weeks. At the end of paraquat treatment, motor and memory function were assessed followed by collection of brain tissue for biochemical analysis. Mthfr+/- mice treated with paraquat showed impaired motor function. There was increased microglial activation within the substantia nigra (SN) of Mthfr+/- mice treated with paraquat. Additionally, all Mthfr+/- mice that were treated with paraquat showed increased oxidative stress within the dorsal striatum, but not the SN. The present results show that paraquat exposure increases PD-like pathology in mice deficient in one-carbon metabolism.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".