Interleukin‐17 regulates matrix metalloproteinase activity in human pulmonary tuberculosis
Bibliographic record
Abstract
Abstract Tuberculosis (TB) is characterized by extensive pulmonary matrix breakdown. Interleukin‐17 (IL‐17) is key in host defence in TB but its role in TB‐driven tissue damage is unknown. We investigated the hypothesis that respiratory stromal cell matrix metalloproteinase (MMP) production in TB is regulated by T‐helper 17 (T H ‐17) cytokines. Biopsies of patients with pulmonary TB were analysed by immunohistochemistry (IHC), and patient bronchoalveolar lavage fluid (BALF) MMP and cytokine concentrations were measured by Luminex assays. Primary human airway epithelial cells were stimulated with conditioned medium from human monocytes infected with Mycobacterium tuberculosis (Mtb) and T H ‐17 cytokines. MMP secretion, activity, and gene expression were determined by ELISA, Luminex assay, zymography, RT‐qPCR, and dual luciferase reporter assays. Signalling pathways were examined using phospho‐western analysis and siRNA. IL‐17 is expressed in TB patient granulomas and MMP‐3 is expressed in adjacent pulmonary epithelial cells. IL‐17 had a divergent, concentration‐dependent effect on MMP secretion, increasing epithelial secretion of MMP‐3 ( p < 0.001) over 72 h, whilst decreasing that of MMP‐9 ( p < 0.0001); mRNA levels were similarly affected. Both IL‐17 and IL‐22 increased fibroblast Mtb‐dependent MMP‐3 secretion but IL‐22 did not modulate epithelial MMP‐3 expression. Both IL‐17 and IL‐22, but not IL‐23, were significantly up‐regulated in BALF from TB patients. IL‐17‐driven MMP‐3 was dependent on p38 MAP kinase and the PI3K p110α subunit. In summary, IL‐17 drives airway stromal cell‐derived MMP‐3, a mediator of tissue destruction in TB, alone and with monocyte‐dependent networks in TB. This is regulated by p38 MAP kinase and PI3K pathways. © 2017 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of Pathological Society of Great Britain and Ireland.
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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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".