The level of synovial human VEGFA, IL-8 and MIP-1α correlate with truncation of lubricin glycans in osteoarthritis
Bibliographic record
Abstract
Abstract Osteoarthrithis (OA) is an endemic disease due to the increase of the world’s elderly population. Previously thought to be a consequence of an imbalance between cartilage degradation and biosynthesis, it is now recognized as a disease also involving inflammation, hence influencing the level of inflammatory cytokines, growth factors and chemokines. Lubricin is a mucin type molecule where its OA induced glycosylation truncation propels a deteriorating lubrication of the articular cartilage. The objective of this study was to explore the OA driven truncation of O -linked glycosylation of synovial lubricin and its cross talk with systemic and local (synovial fluid, SF) inflammation. We compared the systemic level of cytokines/chemokine in OA patients’ and controls’ plasma with their local level in SF using a 44 plex screen. The level of 27 cytokines and chemokines was consistently measured in both plasma and SF. The data showed that the levels of cytokines and chemokines in OA plasma display limited correlation to their counterpart in SF. The level of synovial IL-8 and MIP-1α and VEGFA in OA patients, but not their plasma level, where the only cytokines that displayed a significant correlation to the observed lubricin O -linked glycosylation truncation. These cytokines were also shown to be upregulated exposing fibroblast like synoviocytes from healthy and OA patients to recombinant lubricin with truncated glycans mainly consisting of Tn-antigens, while lubricin with sialylated and non-sialylated T anigens did not have any effect. The data suggest that truncated glycans of lubricin, as found in OA, promotes the synovial cytokine production and exerebate the local synovial inflammation.
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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) | 0.002 | 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 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".