STAT3, p38 MAPK, and NF-κB Drive Unopposed Monocyte-Dependent Fibroblast MMP-1 Secretion in Tuberculosis
Bibliographic record
Abstract
Tissue destruction characterizes infection with Mycobacterium tuberculosis (Mtb). Type I collagen provides the lung's tensile strength, is extremely resistant to degradation, but is cleaved by matrix metalloproteinase (MMP)-1. Fibroblasts potentially secrete quantitatively more MMP-1 than other lung cells. We investigated mechanisms regulating Mtb-induced collagenolytic activity in fibroblasts in vitro and in patients. Lung fibroblasts were stimulated with conditioned media from Mtb-infected monocytes (CoMTb). CoMTb induced sustained increased MMP-1 (74 versus 16 ng/ml) and decreased tissue inhibitor of metalloproteinase (TIMP)-1 (8.6 versus 22.3 ng/ml) protein secretion. CoMTb induced a 2.7-fold increase in MMP-1 promoter activation and a 2.5-fold reduction in TIMP-1 promoter activation at 24 hours (P = 0.01). Consistent with this, TIMP-1 did not co-localize with fibroblasts in patient granulomas. MMP-1 up-regulation and TIMP-1 down-regulation were p38 (but not extracellular signal-regulated kinase or c-Jun N-terminal kinase) mitogen-activated protein kinase-dependent. STAT3 phosphorylation was detected in fibroblasts in vitro and in tuberculous granulomas. STAT3 inhibition reduced fibroblast MMP-1 secretion by 60% (P = 0.046). Deletion of the MMP-1 promoter NF-κB-binding site abrogated promoter induction in response to CoMTb. TNF-α, IL-1β, or Oncostatin M inhibition in CoMTb decreased MMP-1 secretion by 65, 63, and 25%, respectively. This cytokine cocktail activated the same signaling pathways in fibroblasts and induced MMP-1 secretion similar to that induced by CoMTb. This study demonstrates in a cellular model and in patients with tuberculosis that in addition to p38 and NF-κB, STAT3 has a key role in driving fibroblast-dependent unopposed MMP-1 production that may be key in tissue destruction in patients.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".