trans-Nonachlor and cis-Nonachlor Toxicity in Sprague-Dawley Rats: Comparison with Technical Chlordane
Bibliographic record
Abstract
cis-Nonachlor and trans-nonachlor are bioaccumulating components of the pesticide chlordane, which can be detected in various environmental biota and in humans. Existing studies have focused on the potential adverse health effects of the parent chlordane mixture. Comparable toxicity data are nonexistent for individual chlordane constituents such as trans-nonachlor, cis-nonachlor, or oxychlordane, which are among the most common chlordane-related environmental contaminants and tissue residues. In this study, rats were administered cis-nonachlor, trans-nonachlor, or technical chlordane by gavage for 28 days at doses of 0.25 to 25 mg/kg body weight. Residue analyses indicated that trans-nonachlor accumulation in adipose was greater than cis-nonachlor when rats were administered each chemical under identical conditions of dose and exposure. For all test chemicals, the major metabolite oxychlordane accumulated in adipose tissue. Adipose tissue residue levels of all test chemicals and the major metabolite were higher in female rats. The liver was a target organ in male and female rats, indicated by increased liver weight and histopathological changes consistent with microsomal enzyme induction. Hepatic changes were most pronounced in rats treated with trans-nonachlor. Elevated kidney weights and depressed organic ion transport were observed in males treated with trans-nonachlor and chlordane. Although in general, changes in target organs and clinical chemistry endpoints were similar for all 3 test chemicals, the approximate toxicity ranking from most to least toxic was trans-nonachlor > technical chlordane > cis-nonachlor.
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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) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 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".