Hypoxia-inducible Factor Mediates Hypoxic and Tumor Necrosis Factor α-induced Increases in Tumor Necrosis Factor-α Converting Enzyme/ADAM17 Expression by Synovial Cells
Bibliographic record
Abstract
Chronic hypoxia and inflammatory cytokines are hallmarks of inflammatory joint diseases like rheumatoid arthritis (RA), suggesting a link between this microenvironment and central pathological events. Because TACE/ADAM17 is the predominant protease catalyzing the release of tumor necrosis factor alpha (TNFalpha), a cytokine that triggers a cascade of events leading to RA, we examined the regulation of this metalloprotease in response to hypoxia and TNFalpha itself. We report that low oxygen concentrations and TNFalpha enhance TACE mRNA levels in synovial cells through direct binding of hypoxia-inducible factor-1 (HIF-1) to the 5' promoter region. This is associated with elevated TACE activity as shown by the increase in TNFalpha shedding rate. By the use of HIF-1-deficient cells and by obliterating NF-kappaB activation, it was determined that the hypoxic TACE response is mediated by HIF-1 signaling, whereas the regulation by TNFalpha also requires NF-kappaB activation. As a support for the in vivo relevance of the HIF-1 axis for TACE regulation, immunohistological analysis of TACE and HIF-1 expression in RA synovium indicates that TACE is up-regulated in both fibroblast- and macrophage-like synovial cells where it localizes with elevated expression of both HIF-1 and TNFalpha. These findings suggest a mechanism by which TACE is increased in RA-affected joints. They also provide novel mechanistic clues on the influence of the hypoxic and inflammatory microenvironment on joint diseases.
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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) | 0.001 | 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".