Homocysteinylation of Metallothionein Impairs Intracellular Redox Homeostasis
Bibliographic record
Abstract
eart disease and stroke are major causes of death and morbidity in North America, and they exact high personal, community, and health care costs.Most heart attacks and strokes are caused by thrombosis superimposed on disrupted atherosclerotic lesions, a process known as atherothrombosis.1,2 A number of risk factors are known to accelerate atherothrombosis, including hypercholesterolemia, smoking, diabetes, hypertension, and obesity.Numerous clinical and epidemiological studies have established hyperhomocysteinemia as an independent risk factor for cardiovascular disease and stroke.[3][4][5][6][7][8] Patients with inborn errors of methionine metabolism caused by deficiencies in cystathionine -synthase or 5,10-methylenetetrahydrofolate reductase present with severe hyperhomocysteinemia and have a 50% chance of developing a major vascular event by the age of 30 years if untreated.6 This vascular risk is substantially decreased by homocysteine-lowering therapy (dietary supplementation with folic acid, B-vitamins, and/or betaine), even if the treatment does not completely normalize total plasma homocysteine levels.8 Unlike severe hyperhomocysteinemia, mild hyperhomocysteinemia attributable to deficiencies in dietary folic acid and/or B-vitamins is common in the general population.Despite the association between hyperhomocysteinemia and increased cardiovascular risk, several recent clinical trials have failed to show a preventative benefit of homocysteine-lowering therapy in cardiovascular patients with mild hyperhomocysteinemia. 9,10 Although not completely understood, the results of these studies could imply that homocysteine-lowering therapy is ineffective in patients with established cardiovascular disease or that vitamin therapy has other, potentially adverse effects that neutralize its homocysteine-lowering benefit.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".