An in vitro method for predicting the efficacy of WBC separation using different starch preparations and anticoagulant ratios
Bibliographic record
Abstract
BACKGROUND: Separation of blood components depends on a number of factors, including the viscosity of the plasma and the number and size of the various cellular elements. To enhance granulocyte collection, it is common practice to alter the plasma environment by the addition of sedimenting agents such as hydroxyethyl starch. Recently, because of its prolonged persistence in the circulation, the higher-molecular-weight form of hydroxyethyl starch, Hespan (HP), has been replaced by the lower-molecular-weight form, pentastarch (PS). However, the yield appears to be lower. A rapid in vitro approach was used to permit comparison of the efficiency of separation of WBCs by the use of PS and HP and different ratios of anticoagulants that also alter the sedimenting characteristics of blood. STUDY DESIGN AND METHOD: Blood from individual persons was collected into sodium citrate at ratios of 1:8, 1:12, and 1:16. Samples were evaluated either before or after the addition of PS or HP and after centrifugation. RESULTS: The addition of HP increased the sedimentation rate to at least four times that of plasma (10.9 vs. 47.9 mm); PS approximately doubled the rate. Viscosity was altered by the introduction of either starch. These changes (ranging from a rate of 4.2 in HP with a 1:16 anticoagulant to 3.6 in PS with a 1:8 ratio of anticoagulant) reflected the anticipated effects of anticoagulant dilution and carbohydrate addition. Granulocyte recovery was highest, with a 1:12 anticoagulant ratio in all tests with HP producing the greatest yield (HP, 101%; PS, 89%; control, 78%). CONCLUSION: HP is far more effective than its lower-molecular-weight substitute PS in the generation of granulocytes in the buffy coat of whole blood. This method provides a simple, rapid, in vitro approach to evaluating the separating efficiency of solutions.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".