Acute arsenic treatment alters arachidonic acid and its associated metabolite levels in the brain of C57Bl/6 mice
Bibliographic record
Abstract
The toxic effects of arsenic on the whole brain, as well as the discrete regions, has been previously reported for mice. We investigated the effects of acute arsenite (As(III)) on brain levels of arachidonic acid (AA) and its associated metabolites generated through cytochrome P450 (CYP), cyclooxygenase (COX), and lipoxygenase (LOX) pathways. Our results demonstrated that acute As(III) treatment (12.5 mg·(kg body mass)(-1)) decreases cytosolic phospholipase A2 (cPLA2) with a subsequent decrease in its catalytic activity and brain AA levels. In addition, As(III) differentially altered CYP epoxygenases and CYP ω-hydroxylases, but it did not affect brain Ephx2 mRNA or sEH catalytic activity levels. As(III)-mediated effects on Cyps caused an increase in brain 5,6-epoxyeicosatrienoic acid (5,6-EET) and 16/17-hydroxyeicosatetreinoic acid (16/17-HETE) levels, and a decrease in 18- and 20-HETE levels. Furthermore, As(III) increased cyclooxygenase-2 (COX-2) mRNA while decreasing prostaglandins F2α (PGF2α) and PGJ2. As(III) also increased brain 5-lipoxygenase (5-LOX) and 15-LOX mRNA, but decreased 12-LOX mRNA. These changes in LOX mRNA were associated with a decrease in 8/12-HETE levels only. In conclusion, this is the first demonstration that As(III) decreases AA levels coinciding with alterations to EET, HETE, and PG levels, which affects brain development and neurochemistry.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 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".