Divergent and Synergistic Regulation of Matrix Metalloprotease Production by Cytokines in Combination with C-C Chemokines
Bibliographic record
Abstract
The chemotactic effects of chemokines on cells has long been known, but it is now clear that chemokines also have much broader activities and are also involved in a number of disease pathologies, such as rheumatoid arthritis, cancer metastasis and other inflammatory processes. This study investigates the effects of four C-C chemokines, CCL2, CCL3, CCL4 and CCL5 either alone or in the presence of two regulatory cytokines TNF-alpha and TGF-beta and their effect on secretion of two matrix metalloproteases MMP, MMP-2 and MMP-9, and the expression of one membrane bound MMP, MMP-14, by a monocytic human cell line, MonoMac6. All four C-C chemokines were shown to be chemotactic, but only CCL2 and CCL4 had any significant stimulatory effect on MMP-9 and MMP-2, respectively. Both TNF-alpha and TGF-beta were found to divergently enhance MMP-9 and MMP-2 secretion respectively, with stimulation indexes of two and five respectively. Simultaneous treatment with TNF-alpha and chemokine resulted in up to a fifteen-fold stimulation of MMP-9 secretion and treatment with TGF-beta and chemokine resulted in up to a fifteen-fold stimulation of MMP-2 secretion, while TNF-alpha in combination with CCL4 stimulated MMP-14 expression five-fold. Chemokine receptor expression was also investigated using a calcium-sensitive dye and FACS analysis. CCL2, CCL3, and CCL5 all resulted in a detectable enhancement of cytoplasmic Ca2+concentration. CCL4 was unable to activate Ca2+ mobilization, despite the presence of CCR5, the receptor for CCL4. There appeared to be no correlation between MMP production and chemotaxis. The strong synergy between chemokines and cytokines and the enhanced production of MMP may signify the differential regulatory mechanisms of the two cytokines and chemokines in disease pathology.
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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 | 0.000 | 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) | 0.000 | 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".