Development of a Rapid and Sensitive Test for Identification of Major Pathogens in Bovine Mastitis by PCR
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Bovine mastitis is the most important source of loss for the dairy industry. A rapid and specific test for the detection of the main pathogens of bovine mastitis is not actually available. Molecular probes reacting in PCR with bacterial DNA from bovine milk, providing direct and rapid detection of Escherichia coli, Staphylococcus aureus, Streptococcus agalactiae, Streptococcus dysgalactiae, Streptococcus parauberis, and Streptococcus uberis, have been developed. Two sets of specific primers were designed for each of these microorganisms and appeared to discriminate close phylogenic bacterial species (e.g., S. agalactiae and S. dysgalactiae). In addition, two sets of universal primers were designed to react as positive controls with all major pathogens of bovine mastitis. The sensitivities of the test using S. aureus DNA extracted from milk with and without a pre-PCR enzymatic lysis step of bacterial cells were compared. The detection limit of the assay was 3.125 x 10(2) CFU/ml of milk when S. aureus DNA was extracted with the pre-PCR enzymatic step compared to 5 x 10(3) CFU/ml of milk in the absence of the pre-PCR enzymatic step. This latter threshold of sensitivity is still compatible with its use as an efficient tool of diagnosis in bovine mastitis, allowing the elimination of expensive reagents. The two PCR tests avoid cumbersome and lengthy cultivation steps, can be performed within hours, and are sensitive, specific, and reliable for the direct detection in milk of the six most prevalent bacteria causing bovine mastitis.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| 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 it