Platelet-, leucocyte- and red cell-derived microparticles in stored whole blood, with and without leucofiltration, with and without ionising radiation.
Bibliographic record
Abstract
BACKGROUND: Storage lesion, including microparticle formation, has been partially characterised in whole blood, but not in all combinations of pre-storage leucofiltration and/or irradiation. MATERIALS AND METHODS: Single-donor whole blood products were processed into four subunits: with and without leucofiltration, with and without X-irradiation (25 Gy). Platelet-, leucocyte-, and erythrocyte-derived microparticles and free haemoglobin were measured periodically throughout 42 days of storage. RESULTS: Pre-storage leucofiltration substantially reduced platelet- and leucocyte-derived microparticle counts throughout storage. Irradiation, in contrast, had no significant effect on microparticle counts. A gate for all microparticles showed a substantial time-dependent increase in unfiltered whole blood. A time-dependent increase in free haemoglobin was greatest in unfiltered, irradiated whole blood. DISCUSSION: This study indicates that leucofiltration can prevent the formation of leucocyte- and platelet-derived microparticles, and might reduce haemolysis in irradiated whole blood, either by removing factors that provoke haemolysis, or by selective retention of senescent or effete red cells most prone to haemolysis.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.001 | 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".