Metabolomic and Transcript Analysis Revealed a Sex-Specific Effect of Glyphosate in Zebrafish Liver
Bibliographic record
Abstract
Glyphosate is a component of commonly used herbicides for controlling weeds in crops, gardens and municipal parks. There is increasing awareness that glyphosate-based herbicides, in addition to acting on plants, may also exert toxicity in wildlife and humans. In this study, male and female adult zebrafish were exposed to 700 µg/L of glyphosate (GLY), for 28 days. We used the metabolomic approach and UHPLC-ESI-MS to analyze liver samples to investigate the adverse effects of glyphosate on hepatic metabolism. The impact of GLY was found to be sex-specific. In female, GLY exposure affected purine metabolism by decreasing the levels of AMP, GMP and inosinic acid, consequently increasing uric acid levels with respect to the control (CTRL). Exposure to GLY also caused a decrease of UMP levels in the pyrimidine metabolism pathway. In male, GLY exposure decreased the aminoadipic acid within the lysine degradation pathway. Transcript analysis of genes involved in stress response, oxidative stress and the immune system were also performed. Results demonstrated an increased stress response in both sexes, as suggested by higher nr3c1 expression. However, the hsp70.2 transcript level was increased in female but decreased in male. The results demonstrated reduced sod1, sod2, and gpx1a in male following exposure to GLY, indicating an impaired oxidative stress response. At the same time, an increase in the cat transcript level in female was observed. mRNA levels of the pro-inflammatory interleukins litaf and cxcl8b.1 were increased in female. Taken together, the results provide evidence of disrupted nucleotide hepatic metabolism, increased stress inflammatory response in female and disruption of oxidative stress response in male.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 teacher head, 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".