Overexpression of Tumor Necrosis Factor-α in the Lungs Alters Immune Response, Matrix Remodeling, and Repair and Maintenance Pathways
Bibliographic record
Abstract
Increased production of tumor necrosis factor (TNF)-α and matrix metalloproteinases (MMPs) is a feature of inflammatory lung diseases, including emphysema and fibrosis, but the divergent pathological characteristics that result indicate involvement of other processes in disease pathogenesis. Transgenic mice overexpressing TNF-α in type II alveolar epithelial cells under the control of the surfactant protein (SP)-C promoter develop pulmonary inflammation and emphysema but are resistant to induction of fibrosis by administration of bleomycin or transforming growth factor-β. To study the molecular mechanisms underlying the development of this phenotype, we used a microarray approach to characterize the pulmonary transcriptome of SP-C/TNF-α mice and wild-type littermates. Four-month-old SP-C/TNF-α mice displayed pronounced pulmonary inflammation, airspace enlargement, increased MMP-2 and MMP-9 levels, and altered expression of 2332 probes. The functional assessment of genes with increased expression revealed enrichment of inflammatory/immune responses and proteases, whereas genes involved in protease inhibition, angiogenesis, cross-linking of basement membrane proteins, and myofibroblast differentiation were predominantly decreased. Comparison with multiple lung disease models identified a set of genes unique to the SP-C/TNF-α model and revealed that lack of extracellular matrix production distinguished SP-C/TNF-α mice from fibrosis models. Activation of inflammatory and proteolytic pathways and disruption of maintenance and repair processes are central features of emphysema in this TNF-overexpression model. Impairment of myofibroblast differentiation and extracellular matrix production may underlie resistance to induction of fibrosis.
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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 | 0.001 | 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) | 0.000 | 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".