Evaluation of a PCR assay on overgrown environmental samples cultured for <i>Mycobacterium avium</i> subsp. <i>paratuberculosis</i>
Bibliographic record
Abstract
Culture of Mycobacterium avium subsp. paratuberculosis (MAP) is the definitive antemortem test method for paratuberculosis. Microbial overgrowth is a challenge for MAP culture, as it complicates, delays, and increases the cost of the process. Additionally, herd status determination is impeded when noninterpretable (NI) results are obtained. The performance of PCR is comparable to fecal culture, thus it may be a complementary detection tool to classify NI samples. Our study aimed to determine if MAP DNA can be identified by PCR performed on NI environmental samples and to evaluate the performance of PCR before and after the culture of these samples in liquid media. A total of 154 environmental samples (62 NI, 62 negative, and 30 positive) were analyzed by PCR before being incubated in an automated system. Growth was confirmed by acid-fast bacilli stain and then the same PCR method was again applied on incubated samples, regardless of culture and stain results. Change in MAP DNA after incubation was assessed by converting the PCR quantification cycle (Cq) values into fold change using the 2 −ΔCq method (ΔCq = Cq after culture − Cq before culture). A total of 1.6% (standard error [SE] = 1.6) of the NI environmental samples had detectable MAP DNA. The PCR had a significantly better performance when applied after culture than before culture ( p = 0.004). After culture, a 66-fold change (SE = 17.1) in MAP DNA was observed on average. Performing a PCR on NI samples improves MAP culturing. The PCR method used in our study is a reliable and consistent method to classify NI environmental 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 | 0.003 | 0.009 |
| 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 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".