Bibliographic record
Abstract
With the identification of hyperhomocysteinemia as a risk factor for cardiovascular disease, an understanding of the genetic determinants of plasma homocysteine is important for prevention and treatment. It has been known for some time that homocystinuria, a rare inborn error of metabolism, can be due to genetic mutations that severely disrupt homocysteine metabolism. A more recent development is the finding that milder, but more common, genetic mutations in the same enzymes might also contribute to an elevation in plasma homocysteine. The best example of this concept is a missense mutation (alanine to valine) at base pair (bp) 677 of methylenetetrahydrofolate reductase (MTHFR), the enzyme that provides the folate derivative for conversion of homocysteine to methionine. This mutation results in mild hyperhomocysteinemia, primarily when folate levels are low, providing a rationale (folate supplementation) for overcoming the genetic deficiency. Additional genetic variants in MTHFR and in other enzymes of homocysteine metabolism are being identified as the cDNAs/genes become isolated. These variants include a glutamate to alanine mutation (bp 1298) in MTHFR, an aspartate to glycine mutation (bp 2756) in methionine synthase, and an isoleucine to methionine mutation (bp 66) in methionine synthase reductase. These variants have been identified relatively recently; therefore additional investigations are required to determine their clinical significance with respect to mild hyperhomocysteinemia and vascular disease.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".