Health care use and risk of ovarian cancer: Is there a link?
Bibliographic record
Abstract
CD44 is a ubiquitous molecule also known as hyaluronic acid or homing receptor. However, the cellular functions and its role in inflammation, for example, rheumatoid synovitis, are currently unknown. In this study, we propose a novel function for CD44. Using synovial cells from rheumatoid arthritis (RA) patients, we demonstrated that CD44 cross-linking and binding to hyaluronan augmented VCAM-1 expression and subsequently VCAM-1-mediated cell adhesion. Briefly, we found that 1) rheumatoid synovial cells highly expressed CD44; 2) cross-linking of CD44 markedly but transiently augmented VCAM-1 expression and its mRNA transcription much more than did IL-1β and TNF-α; 3) hyaluronan, especially when fragmented, also up-regulated VCAM-1; 4) CD44 activated the transcription factor AP-1; and 5) the integrin-dependent adhesive function of RA synovial cells to T cells was also amplified by CD44 cross-linking. These results indicate that the adhesion of RA synovial cells to matrices such as hyaluronic acid through CD44 could up-regulate VCAM-1 expression and VCAM-1-mediated adhesion to T cells, which might in turn cause activation of T cells and synovial cells in RA synovitis. We therefore propose that such cross-talking among distinct adhesion molecules may be involved in the pathogenesis of inflammation, including RA synovitis.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 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".