CYTOMEGALOVIRUS INDUCES SIALYL LEWISx AND LEWISx ON HUMAN ENDOTHELIAL CELLS1
Bibliographic record
Abstract
BACKGROUND: Cytomegalovirus (CMV) is the primary viral cause of complications in transplant recipients. We sought to understand the mechanisms of its dissemination and induction of vascular disease, which may lead to transplant complications. Sialyl Lewis(x) (sLe(x)) and Lewis(x) (Le(x)) are known for their roles in mediating cell adhesion and as tumor-associated carbohydrate antigens. Herein we explore whether CMV induces surface expression of these important molecules in endothelial cells (EC). METHODS: Flow cytometry was used to detect surface expression of sLe(x) and Le(x) on CMV-infected human umbilical vein endothelial cells (HUVEC), with or without ultraviolet inactivation of the virus. To elucidate mechanisms of CMV-mediated induction, mRNA coding for predominant HUVEC sialyltransferases (ST) and fucosyltransferases (FT), key enzymes in sLe(x) and Le(x) synthesis, was analyzed by Northern blot. Dual immunohistochemical staining for sLe(x) and Le(x) expression of human colon and placental tissue was performed to investigate in vivo relevance. RESULTS: sLe(x) expression on CMV-infected HUVEC was strongly up-regulated by 8 days after inoculation. Le(x) expression was detectable earlier and increased steadily over time. In contrast, ultraviolet-inactivated CMV did not induce expression of these molecules. Northern blot assays demonstrated higher levels of important EC glycosyltransferases ST-IV, FT-III, and FT-IV in CMV-infected EC. Finally, high levels of sLe(x) and Le(x) were expressed in CMV-infected EC in vivo. CONCLUSIONS: Given the known biologic functions of sLe(x) and Le(x), we suggest that CMV induction of these molecules may have widespread consequences ranging from CMV dissemination to induction of CMV-associated vascular disease, including thrombosis.
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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 | 0.001 |
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".