Impact of sample volume and handling time during analysis on the in vitro quality measurements of platelet concentrates held in syringes
Bibliographic record
Abstract
INTRODUCTION: The determination of quality parameters is a necessity for monitoring the efficacy of platelet concentrates. During consolidated quality control studies, there may be a large number of samples to be analyzed at the same time. This common workflow setup triggered the question whether there is an influence of the number of samples to be analyzed on the accuracy of the test results. METHODS: Two different sample volumes of platelet concentrates, 1 ml and 50 ml, were analyzed for a set of standard in vitro parameters including pCO(2), pO(2), pH, glucose, and lactate as well as platelet activation via CD62P expression and responsiveness to adinosine diphosphate in an extent-of-shape-change assay. To assess apoptotic mechanisms triggered by the hold time, changes in the phosphatidylserine exposure were monitored. RESULTS: In total, eleven time points were assessed over a 3-h period as well as an overnight point for assay evaluation. Except for pCO(2) and pO(2), all in vitro parameters analyzed were unaffected by a sample hold time of up to 3-h. CONCLUSION: Sampling for pO(2) determination should be carried out in small volumes and assessed within 30 min of collection to obtain reliable and comparable results.
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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 | 0.005 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".