Impact of oxytetracycline exposure on the digestive system microbiota of Daphnia magna
Bibliographic record
Abstract
Antibiotics are used to treat serious illness, but may also be used extraneously or as a preventative measure in many farm animals. This usage increases the potential for unintentional exposure to a variety of organisms. When antibiotics enter aquatic environments, Daphnia magna are especially vulnerable as they filter-feed in freshwater environments. Oxytetracycline (OTC) is a commonly-used broad-spectrum antibiotic used to treat a variety of mammalian diseases. In this study, the impact of OTC on D. magna mortality and gut biota were studied using both cultivation and sequencing-based approaches. Mortality rates were extremely low with the LD50 >2,000ppm. However, OTC impacted abundance and species diversity of intestinal microorganisms in the gut of the D. magna in abundance as well as species diversity. In control organisms, Pseudomonas putida and Aeromonas hydrophila were both present while only P. putida was found in OTC-exposed organisms. Disruption of the intestinal biota in D. magna could have implications on long-term survival, energy expenditure, and reproduction.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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 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".