An ultrasensitive enzymatic method for measuring mevalonic acid in serum
Bibliographic record
Abstract
We have developed a simple, precise, and ultrasensitive enzymatic method for measuring serum mevalonic acid (MVA) concentration, which is thought to be a good indicator of the in vivo cholesterol biosynthesis rate. This assay is based on an enzyme cycling reaction and makes use of HMG-CoA reductase (HMGR), thio-NAD, NADH, and CoA. MVA participates in the HMGR cycling reaction, and its level is measured based on the production of thio-NADH, which is determined from the change in absorbance at 405 nm. To achieve high specificity, we used mevalonate kinase (MVK) in addition to HMGR. Only substrates able to participate in both the HMGR cycling reaction and the MVK reaction are measured as MVA. The detection limit for MVA is 0.4 ng/ml (2.7 nmol/l), and the calibration curve for MVA is linear up to 44 ng/ml (300 nmol/l). Regression analysis with 40 serum samples showed the accuracy of quantifying MVA with this enzymatic assay to be comparable to that using LC-MS/MS (correlation: y = 0.83x + 0.24; r = 0.97). This procedure is simple, precise, and robust. It is also rapid and has a high throughput, making it potentially useful for clinical applications.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".