Gene-expression profiling of calves 6 and 9 months after inoculation with Mycobacterium avium subspecies paratuberculosis
Bibliographic record
Abstract
Early detection of Johne's disease (JD) caused by Mycobacterium avium subspecies paratuberculosis (MAP) is essential to reduce transmission; consequently, new diagnostic techniques and approaches to detect MAP or markers of early MAP infection are being explored. The objective was to identify biomarkers associated with MAP infection at 6 and 9 months after oral inoculation. Therefore, gene expression analysis was done using whole blood cells obtained from MAP-infected calves. All MAP-inoculated calves had a cell-mediated immune response (IFN-γ) to Johnin PPD specific antigens, and 60% had an antibody response to MAP antigens. Gene expression analysis at 6 months after inoculation revealed downregulation of chemoattractants, namely neutrophil beta-defensin-9 like peptide (BNBD9-Like), S100 calcium binding protein A9 (s100A9) and G protein coupled receptor 77 (GPR77) or C5a anaphylatoxin chemotactic receptor (C5a2). Furthermore, BOLA/MHC-1 intracellular antigen presentation gene was downregulated 9 months after inoculation. In parallel, qPCR experiments to evaluate the robustness of some differentially expressed genes revealed consistent downregulation of BOLA/MHC-I, BNBD9-Like and upregulation of CD46 at 3, 6, 9, 12, and 15 months after inoculation. In conclusion, measuring the expression of these genes has potential for implementation in a diagnostic tool for the early detection of MAP infection.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".