Toxicological Effects of Differently Polluted Dam Waters Spiked with Pesticides on Freshwater Snails Lymnaea Natalensis
Bibliographic record
Abstract
<p>Pesticides extensively used in agricultural fields to ensure high quality crop yields indirectly find their way to aquatic bodies where they affect aquatic biota. We investigated the effects of pesticides in different dam waters on esterase enzyme activity of the freshwater snail species<em> Lymnaea natalensis</em>. Groups of adult snails were exposed to 0.006 ppm chlorpyrifos and 0.003 ppm aldicarb in polluted water from Umguza dam and relatively pristine water from Hillside dam for 14 days. Carboxylesterase, acetylcholinesterase and arylesterase activities were measured. Both pesticides caused significant inhibition of esterase activity after the 14 day exposure period, with exposures to Umguza dam water showing higher inhibition as compared to exposures to Hillside dam water. Aldicarb and chlorpyrifos both showed a time-dependent inhibition of enzyme activity, the former causing a higher inhibitory effect as compared to the latter. Acetylcholinesterase was inhibited up to 80% following exposure to aldicarb while exposure to chlorpyrifos in Umguza water caused only 40% inhibition. Carboxylesterases were similarly inhibited with higher inhibition observed in snails exposed to Umguza dam water when compared to snails exposed to Hillside dam water, while arylesterases were inhibited in the range 80-90%, with an exception of chlorpyrifos spiked Hillside dam water which caused 45% inhibition. Contaminated Umguza dam water also appeared to enhance the effects of pesticides when compared to the relatively pristine Hillside dam water. Alteration of esterase activity can be used as an early warning signal indicating exposure to environmental pollutants. The results of this study therefore, highlight the adverse effects of pesticides on non-target aquatic organisms, evidenced by the inhibition of esterase activity.</p>
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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 | 0.000 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".