Induction of monocyte tissue factor expression by homocysteine: a possible mechanism for thrombosis
Bibliographic record
Abstract
Moderately elevated plasma homocysteine levels are an important independent risk factor for arterial and venous thrombosis and for atherosclerosis. Some investigators have proposed that homocysteine's effects result from oxidant injury to the vascular endothelium or from an alteration in endothelial function. However, homocysteine may have other cellular targets. We now report that homocysteine, at physiologically relevant concentrations, induces the expression of tissue factor by monocytes. In response to homocysteine, monocytes express procoagulant activity in a dose-dependent and a time-dependent manner. This activity is attributable to tissue factor because it was dependent on factor VII and blocked by anti-tissue factor antibodies. Tissue factor mRNA levels were also increased in monocytes after homocysteine treatment. The effect was found to be specific because analogues of homocysteine (homocystine and homocysteine thiolactone) did not mimic homocysteine's activity, nor did other thiol compounds (cysteine, 2-mercaptoethanol, dithiothreitol). On the other hand, methionine, the metabolic precursor of homocysteine, was active though less potent than homocysteine. Catalase and superoxide dismutase (scavengers of H(2)O(2) and O(2)(-) Radicals, respectively) were unable to block the expression of tissue factor induced by homocysteine, as was a 5-fold excess of the reducing agent 2-mercaptoethanol. We conclude that the induction of tissue factor expression by circulating monocytes is a plausible mechanism by which homocysteine may induce thrombosis and that a nonspecific redox process is not involved.
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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 | 0.001 | 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".