Antibiotic Sensitivity Pattern of Pathogenic Bacterial Isolates From Diseased Clarias gariepinus From Selected Ibadan And Ikorodu Farms
Bibliographic record
Abstract
This study was carried out to isolate, characterise and identify bacteria from diseased Clarias gariepinusand also assess the occurrence of resistance to antimicrobial in isolated bacteria. Samples of diseased African Catfish were collected for a period of six weeks from consenting farms in Ibadan and Ikorodu in Nigeria and examined for clinical signs of disease. Pond water samples along with organs such as gills, skin, intestine, kidney and lungs from these fish were analyzed microbiologically using differential and selective media. Bacteria enumeration, identification and biochemical characterization were carried out and the physiochemical parameters of the water samples determined. All isolates were subjected to antibiotic sensitivity test using the standard Kirby-Bauer disc diffusion method. The total bacterial load for the organs ranged between 3.0 x 104 (lungs sample) and 6.0 x 107cfu/g (gill sample). The gills had the highest average total bacterial count, while lungs had the least. Morphologically unique bacterial isolates obtained included Salmonella (14 isolates), Pseudomonas (4 isolates), Aeromonas (2 isolates), Edwardsiella (3 isolates) and Shigella (3 isolates). These isolates displayed antibiotic resistance profile to the following: Ceftazidime (38%), Cefuroxime (77%), Gentamicin (37%), Cefixime (73%), Ofloxacin (23%), Augmentin (66%), Nitrofurantoin (58%) and Ciprofloxacin (15%). Two Salmonella isolates had multi-drug resistance pattern. This study showed that indiscriminate use of unlicensed or unapproved antibiotics for aquaculture portends significant hazards to public health therefore disease prevention is preferable through good culture and health management to ensure optimum yields and wholesome products.
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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 | 0.001 | 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".