Enrofloxacin pharmacokinetics in yellow catfish (<i>Pelteobagrus fulvidraco</i>): A comparative analysis of oral, intramuscular, and bath administration
Bibliographic record
Abstract
Enrofloxacin (ENR) residues in yellow catfish (Pelteobagrus fulvidraco) often exceed the standard due to excessive use. This study explored the pharmacokinetics of ENR and its metabolite ciprofloxacin (CIP) in yellow catfish following a single dose of 10 mg/kg body weight via intramuscular injection (IM), oral gavage (PO), or a 5-h drug bath at 10 mg/L and 25°C. High-performance liquid chromatography-mass spectrometry was used to determine the ENR and CIP concentrations in various tissues. The highest ENR concentration occurred with IM administration, peaking at 4.124 mg/L in the plasma, 8.359 mg/kg in the kidney, 6.272 mg/kg in the liver, and 5.192 mg/kg in the muscle. However, PO administration resulted in the longest metabolic time, with elimination half-lives of 56.47 h in plasma, 86.43 h in the kidney, 76.25 h in the liver, and 64.75 h in muscle. Additionally, the area under the concentration-time curve values for IM, PO, and bath administration in yellow catfish plasma were 108.36, 88.96, and 22.08 mg·h/L, respectively. These results indicate the effectiveness of all three administration methods in treating bacterial diseases in yellow catfish. The selection of an appropriate administration method depends on the minimal inhibitory concentration of ENR against pathogenic bacteria. Yellow catfish subjected to PO and IM administration require longer resting periods before they can be marketed than those receiving drug bath administration.
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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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".