Involvement of protein kinase Cζ in interleukin‐1β induction of ADAMTS‐4 and type 2 nitric oxide synthase via NF‐κB signaling in primary human osteoarthritic chondrocytes
Bibliographic record
Abstract
OBJECTIVE: Protein kinase Czeta (PKCzeta), an atypical PKC, has been found to be transcriptionally up-regulated in human osteoarthritic (OA) articular cartilage. This study was undertaken to examine the role of PKCzeta in interleukin-1beta (IL-1beta)-induced NF-kappaB signaling in human OA chondrocytes, and ultimately to better understand its function in the regulation of downstream mediators of cartilage matrix degradation. METHODS: Pharmacologic inhibitors or genetic knockdown techniques were used to investigate the role of PKCzeta. Western blot analysis was used to evaluate phosphorylation of PKCzeta and NF-kappaB. Quantitative polymerase chain reaction (PCR) and activity assays were used to evaluate ADAMTS-4 expression and aggrecanase activity, respectively. Quantitative PCR, biochemical identification, and Western blot analysis were used to evaluate type 2 nitric oxide synthase (NOS2) and NO production. RESULTS: Phosphorylation of PKCzeta and NF-kappaB was induced by IL-1beta treatment in a time-dependent manner, and was specifically inhibited by inhibitors of atypical PKCs. Inhibition of PKCzeta suppressed IL-1beta-induced up-regulation of ADAMTS-4 messenger RNA (mRNA) and aggrecanase activity. Inhibitors of atypical PKCs also inhibited IL-1beta-induced NO production and NOS2 mRNA expression, demonstrating a novel link between PKCzeta and NO production. Furthermore, small interfering RNA- or short hairpin RNA-mediated knockdown of PKCzeta mRNA resulted in significant repression of both ADAMTS-4 and NOS2 mRNA expression. CONCLUSION: Our results show that PKCzeta is involved in the regulation of IL-1beta-induced NF-kappaB signaling in human OA chondrocytes, which in turn regulates downstream expression of ADAMTS-4 and NOS2. Therefore, inhibition of PKCzeta could potentially regulate the production of matrix-degrading enzymes as well as NO production and have a profound effect on disease progression in OA.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".