Short-Term Stabilities of 21 Amino Acids in Dried Blood Spots
Bibliographic record
Abstract
To the Editor: Dried blood spot (DBS)1 sampling is used in disease diagnosis, epidemiological surveillance, and newborn screening, and enables sample collection far from analytical laboratories and shipment via mail services. Amino acids (AAs) measured in DBS are routinely used for the diagnosis of inborn errors of metabolism (1) and childhood malnutrition (2), but environmental stresses incurred during sampling, transportation, and storage can impact the short-term (3) and long-term (4) stabilities of some AAs. Here, we systematically investigated the stabilities of 21 routinely analyzed AAs in DBS under environmental conditions simulating a global health work flow. DBSs were prepared by precisely blotting 30 μL of whole blood onto cellulose-based Whatman 903, FTA DMPK-C, and cotton-based PerkinElmer 226 cards. The optimized sample preparation used 200 μL of 0.02% trifluoroacetic acid in water to completely resuspend the entire DBS spot, followed by ultrasonic extraction with 800 μL of methanol/acetonitrile (1:1, v/v) containing 0.02% trifluoroacetic acid. The AAs were dansylated (5) at pH 9.2 and analyzed by C18 reversed-phase liquid chromatography/positive electrospray ionization/multiple-reaction monitoring mass spectrometry, with 21 13C- or 2H-labeled internal standards, for precise measurements of their molar concentrations (CVs ≤ 7.9% and recoveries of 88.4%–112.8%). Four sets of stability-testing experiments were conducted, and the molar concentrations of each AA were measured from 4 biological replicates of each DBS set. Stabilities were expressed as percentages of the measured AA concentrations in control DBSs that had been stored in the dark at −80 °C.
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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 | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".