Whole‐blood leukoreduction filters are a source for cryopreserved cells for phenotypic and functional investigations on peripheral blood lymphocytes
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: Leukoreduction of blood is now widely performed by blood banks, and the possibility of recovering 10(8) to 10(9) white blood cells (WBCs) from leukoreduction filters, which are usually discarded, represents a promising source for normal human cells. Previous studies with these filters to prepare WBCs have performed their experimentation with fresh cells only. Whether these filter-derived cells could also be used to prepare frozen cell banks to facilitate work organization and open new avenues for their utilization as references in physiological studies and clinical investigations was investigated. STUDY DESIGN AND METHODS: Blood samples or whole-blood leukoreduction filters were obtained, after informed consent, from volunteers or blood donors, respectively. The proportions of CD3+, CD14+, CD16+, CD19+, and CD45+ cells within peripheral blood mononuclear cells (PBMNCs) were determined by flow cytometry from all samples. B cells were isolated and their functional responses were evaluated in vitro. RESULTS: The yield of PBMNCs recovered from whole-blood leukoreduction filters was lower (50%) than the one with fresh blood samples but still provided 2 x 10(8) to 4 x 10(8) PBMNCs per unit. After one cycle of freezing-thawing, the proportions of B- and T-cell populations were similar to normal blood values. Purified B cells issued from whole-blood leukoreduction filters displayed normal phenotypes and functions. CONCLUSION: Leukoreduction filters represent a valuable source of PBMNCs. These cells could be easily recovered to prepare frozen cell banks useful in basic phenotypic and functional analyses involving the main subsets of B cells and the global T-cell population.
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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 | 0.000 | 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) | 0.000 | 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 it