Analysis of Cytokine Gene Expression using a Novel Chromogenic In-situ Hybridization Method in Pulmonary Granulomas of Cattle Infected Experimentally by Aerosolized Mycobacterium bovis
Bibliographic record
Abstract
Mycobacterium bovis is the cause of tuberculosis in most animal species including cattle and is a serious zoonotic pathogen. In man, M. bovis infection can result in disease clinically indistinguishable from that caused by Mycobacterium tuberculosis, the cause of most human tuberculosis. Regardless of host, the typical lesion induced by M. bovis or M. tuberculosis is the tuberculoid granuloma. Tuberculoid granulomas are dynamic structures reflecting the interface between host and pathogen and, therefore, pass through various morphological stages (I to IV). Using a novel in-situ hybridization assay, transcription of various cytokine and chemokine genes was examined qualitatively and quantitatively using image analysis. In experimentally infected cattle, pulmonary granulomas of all stages were examined 150 days after aerosol exposure to M. bovis. Expression of mRNA encoding tumour necrosis factor (TNF)-α, transforming growth factor-β, interferon (IFN)-γ, interleukin (IL)-17A, IL-16, IL-10, CXCL9 and CXCL10 did not differ significantly between granulomas of different stages. However, relative expression of the various cytokines was characteristic of a Th1 response, with high TNF-α and IFN-γ expression and low IL-10 expression. Expression of IL-16 and the chemokines CXCL9 and CXCL10 was high, suggestive of granulomas actively involved in T-cell chemotaxis.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".