Human Alveolar Macrophage Gene Responses to <i>Mycobacterium tuberculosis</i> Strains H37Ra and H37Rv
Bibliographic record
Abstract
H37Rv and H37Ra have been widely used as models of virulent and avirulent strains, respectively, of Mycobacterium tuberculosis. Since the sequencing of H37Rv, microarrays have been used to investigate gene expression of M. tuberculosis strains under various conditions, and to compare gene expression of specific isolates of the organism. Because differences in the virulence of these organisms could also be manifest via their differential induction of host genes, we used Affymetrix Human Genome Arrays U133A and U133B to evaluate human alveolar macrophage (AM) responses to infection with H37Rv and H37Ra. H37Rv altered expression of far more genes than did H37Ra. Moreover, the genes induced by H37Rv to a greater extent than by H37Ra were predominantly associated with the development of effective immunity. H37Rv markedly increased expression of IL-23 p19, whereas neither organism significantly induced IL-12 p35 expression. Quantitative PCR confirmed that H37Rv induced significantly more AM p19 expression than did H37Ra. After low-level infection of both AM and peripheral blood monocytes (MN) with H37Rv, neither cell type produced IL-12 (by ELISA). In contrast, AM displayed significant IL-23 production in response to H37Rv, whereas MN did not. Our findings thus suggest an important role for IL-23 in human host responses to pulmonary infection with M. tuberculosis, and are consistent with epidemiologic and genetic studies that imply that H37Rv may not have unusual capacity to cause human disease.
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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 | 0.000 | 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) | 0.002 | 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".