Effect of Hemolyzed Plasma on the Batch Measurement of Nitrate by Nitric Oxide Chemiluminescence
Bibliographic record
Abstract
Nitric oxide (NO) is a potent vasodilator and regulator of vascular tone, a neurotransmitter, and a cytotoxic agent (1)(2). In aqueous aerobic environments, the primary decomposition product of NO is nitrite (NO2−) (3), with further oxidation to nitrate (NO3−) being dependent on the presence of additional oxidizing species such as oxyhemoproteins (3). Collectively, these NO oxidation products are referred to as NOx−. Several analytical techniques have been used to quantify NOx− species, including spectrophotometric assays based on the Griess reaction (4)(5) and enzymatic reduction of NO3− (6), gas chromatography–mass spectrometry (7), chromatographic flow systems (8), and chemiluminescence (9)(10)(11). NOx− may be important in sepsis (12)(13)(14)(15)(16). Of possible analytical importance is intravascular hemolysis during sepsis (17)(18)(19). The effect of hemolysis on NOx− analysis is unknown. Other potential causes of intravascular hemolysis include drug-induced hemolytic anemia, hemolytic transfusion reactions, and artificial heart valves (20), and hemolysis can also occur during blood collection (21) and inappropriate blood storage. The objectives of our study were (a) to determine whether hemolysis interferes with the determination of plasma NO3− by NO chemiluminescence batch methodology and (b) to determine whether the interference could be eliminated by sample pretreatment. We purchased helium and oxygen from Praxair. Other chemicals were from Sigma-Aldrich. All chemicals were reagent-grade quality. Deionized water was used to prepare all solutions. Blood samples were obtained from healthy human volunteers by venipuncture with heparin as anticoagulant. Aqueous NO3− calibrators (25 μmol/L) were prepared in deionized water. Digitonin in phosphate-buffered saline (PBS), at final concentrations of 0, 20, 45, and 90 μmol/L, was used to control the …
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.005 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".