Isolation and characterization of bacteriophages specific to hydrogen-sulfide-producing bacteria
Bibliographic record
Abstract
The objectives of this study were to isolate and characterize bacteriophages specific to hydrogen-sulfide-producing bacteria (SPB) from raw animal materials, and to develop a SPB-specific bacteriophage cocktail for rendering application. Meat, chicken offal, and feather samples collected from local supermarkets and rendering processing plants were used to isolate SPB (n = 142). Bacteriophages (n = 52) specific to SPB were isolated and purified from the above samples using 18 of those isolated SPB strains as hosts. The host ranges of bacteriophages against 5 selected SPB strains (Escherichia coli, Citrobacter freundii, and Hafnia alvei) were determined. Electron microscopy observation of 9 phages selected for the phage cocktail revealed that 6 phages belonged to the family of Siphoviridae and 3 belonged to the Myoviridae family. Restriction enzyme digestion analysis with endonuclease DraI detected 6 distinguished patterns among the 9 phages. Phage treatment prevented the growth of SPB for up to 10 h with multiplicity of infection ratios of 1, 10, 100, and 1000 in tryptic soy broth at 30 °C, and extended the lag phase of SPB growth for 2 h at 22 °C with multiplicities of infection of 10, 100, and 1000. These results suggest that the selected bacteriophage cocktail has a high potential for phage application to control SPB in raw animal materials destined for the rendering process.
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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".