TNF- increases the carbohydrate sulfation of CD44: induction of 6-sulfo N-acetyl lactosamine on N- and O-linked glycans
Bibliographic record
Abstract
CD44 and sulfation have both been implicated in leukocyte adhesion. In monocytes, the inflammatory cytokine tumor necrosis factor alpha (TNF-alpha) stimulates CD44 sulfation, and this correlates with the induction of CD44-mediated adhesion events. However, little is known about the sulfation of CD44 or its induction by inflammatory cytokines. We determined that TNF-alpha induces the carbohydrate sulfation of CD44. CD44 was established as a major sulfated cell surface protein on myeloid cells. In the SR91 myeloid cell line, the majority of CD44 sulfation was attributed to the glycosaminoglycan chondroitin sulfate. However, TNF-alpha stimulation increased CD44 sulfation two- to threefold, largely attributed to the increased sulfation of N- and O-linked glycans on CD44. Therefore, TNF-alpha induced a decrease in the percentage of CD44 sulfation due to chondroitin sulfate and an increase due to N- and O-linked sulfation. Furthermore, TNF-alpha induced the expression of 6-sulfo N-acetyl lactosamine (LacNAc)/Lewis x on these cells, which was detected by a monoclonal antibody after neuraminidase treatment. This 6-sulfo LacNAc/Lewis x epitope was induced on N-linked and (to a lesser extent) on O-linked glycans present on CD44. This demonstrates that CD44 is modified by sulfated carbohydrates in myeloid cells and that TNF-alpha modifies both the type and amount of carbohydrate sulfation occurring on CD44. In addition, it demonstrates that TNF-alpha can induce the expression of 6-sulfo N-acetyl glucosamine on both N- and O-linked glycans of CD44 in myeloid cells.
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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".