Development of a novel immunochromatographic lateral flow assay specific for Mycobacterium bovis cells and its application in combination with immunomagnetic separation to test badger faeces
Bibliographic record
Abstract
The European badger is an important wildlife reservoir of Mycobacterium bovis implicated in the spread of bovine tuberculosis in the United Kingdom and Ireland. Infected badgers are known to shed M. bovis in their urine and faeces, which may contaminate the environment. To aid bovine tuberculosis control efforts novel diagnostic tests for detecting infected and shedding badgers are needed. We proposed development of a novel, rapid immunochromatographic lateral flow device (LFD) as a non-invasive test to detect M. bovis cells in badger faeces. Its application in combination with immunomagnetic separation (IMS) to detect Mycobacterium bovis cells in badger faeces is reported here. A novel prototype LFD for M. bovis cells was successfully developed, with unique specificity for M. bovis and a limit of detection 50% (LOD 50% ) of 1.7 × 10 4 M. bovis cells/ml. When IMS was employed to selectively capture and concentrate M. bovis cells from badger faeces prior to LFD testing, the LOD 50% of the IMS-LFD assay was 2.8 × 10 5 M. bovis cells/ml faecal homogenate. Faeces samples collected from latrines at badger setts in a region of endemic bovine tuberculosis infection were tested; 78 (18%) of 441 samples tested IMS-LFD assay positive, whereas 140 (32%) tested IMS-qPCR positive (Kappa agreement −0.009 ± 0.044, p = 0.838). Subsequently, when 130 faeces samples from live captured, or captive, badgers of known infection status (on the basis of StatPak, interferon-γ and/or culture results) were tested, the IMS-LFD assay had higher relative diagnostic specificity (Sp 0.926), but poorer relative diagnostic sensitivity (Se 0.081), than IMS-qPCR (Sp 0.706, Se 0.581) and IMS-culture (Sp 0.794, Se 0.436). The novel IMS-LFD assay, although very specific for M. bovis , has low analytical sensitivity (indicated by the LOD 50% ) and would only detect badgers shedding high numbers of M. bovis (>10 4–5 cells/g) in their faeces. The novel LFD would, therefore, have limited value as a non-invasive test for badger TB surveillance purposes but it may have value for alternative veterinary diagnostic applications.
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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 | 0.001 | 0.001 |
| 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 | 0.001 | 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".