Effects of freezing on ability to detect <i>Mycobacterium avium</i> subsp. <i>paratuberculosis</i> from bovine tissues following culture
Bibliographic record
Abstract
Mycobacterium avium subsp. paratuberculosis (MAP) is the bacterium that causes Johne's disease in cattle. Although infected cattle can be identified by examining fecal, blood, or milk samples, the gold standard is identification of MAP in tissue samples postmortem. Although tissue samples are commonly frozen, the ability to detect MAP in frozen-thawed tissue samples has apparently not been reported. We therefore determined the ability to detect MAP in tissue samples following freezing. Tissue samples were collected from calves that were either inoculated (IN) 3 mo prior, or contact-exposed (CE) for 3 mo. Following autopsy, tissues were immediately processed for culture, followed by DNA extraction and detection by qPCR. Samples were categorized as positive or negative based on the cycle threshold (Ct) value. The remaining unprocessed tissue samples were frozen at -80°C. After 18 mo, 50 tissue samples designated MAP-positive were thawed and processed for detection of MAP. Four (8%) samples were qPCR-negative, and Ct values of the remaining 46 samples were higher after freezing. Given the small numerical change in Ct values for MAP-positive samples after 18 mo of frozen storage, freezing and thawing may have had some deleterious effects on MAP detection in tissues. Although the decrease in ability to detect MAP-positive samples was minor for IN calves, there may be a greater effect for CE calves that should be considered when freezing tissue samples.
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 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 | 0.001 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 teacher head, 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".