What Effects do Silver Nanoparticles Have on Drosophila melanogaster Larvae with Respect to Stress Response and Microbial Intestinal Composition?
Bibliographic record
Abstract
Silver nanoparticles (AgNPs) have been shown to be highly toxic to certain organisms and can induce stress in cells. The purpose of this study is twofold: first, to examine the stress response to AgNP exposure on Drosophila melanogaster (fruit fly) larvae, and secondly, to determine if exposure to AgNPs alters the intestinal bacterial composition. To answer these questions, fruit flies were grown on food mixed with AgNPs. Larvae were monitored for their ability to escape from heat stress and their climbing ability before metamorphosis into pupae. Larval wandering behaviour was examined by devising a test to determine if they could crawl their way back to food. In order to examine the flora in the digestive tract, DNA was isolated from dissected larval intestines, purified and then a relatively conserved portion of the bacterial DNA was amplified. These samples were then sent for pyrosequencing, which is a technique that will allow us to examine the composition of the intestinal microbial population. Preliminary results have been mixed. There has been some suggestion of a stress response, but this has not been very consistent. Therefore, more experiments need to be done. However, the bacterial population of the gut does seem to change after the treatment, indicating that AgNP exposure results in altered microbial composition in D. melanogaster intestines. It is hoped that this research will help elucidate our understanding of the impact NPs have on organisms, which is highly relevant because of the high prevalence of NPs in consumer and medicinal materials.
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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) | 0.000 | 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 | 0.001 | 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 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".