Depletion of Red Blood Cells from Cord Blood Using a Simple and Rapid Immunomagnetic Separation Method
Bibliographic record
Abstract
Abstract Cord blood (CB) banks and transplantation centers routinely use various assays to measure the number and quality of hematopoietic stem and progenitor cells (HSPC) in hematopoietic cell samples before or after cryopreservation and/or transplantation. Such assays, to measure colony-forming units (CFU) and CD34+/ALDHbright cells, for example, are typically performed on small samples, such as attached segments from frozen CB units. Unfortunately, the accuracy and reliability of these assays are highly sensitive to the presence of contaminating red blood cells (RBCs) in the sample. Current methods for depleting RBCs for downstream analysis include sedimentation by gravity or by centrifugation through density gradient solutions, and hemolysis using ammonium chloride. These procedures are, however, time consuming and may be associated with reduced yield of HSPCs. To address these issues, we have developed a simple and rapid immunomagnetic method (ErythroClear) for depleting RBCs in fresh and thawed CB. RBCs in small (≤100 µL) CB samples are labeled with anti-Glycophorin-A (GlyA) antibodies immobilized on magnetic particles, and removed by magnetic separation. The method allows the handling of multiple samples at one time and takes only 2 minutes per sample. Compared to sedimentation methods using either HetaSep or PrepaCyte, which take 20 minutes per sample, ErythroClear is significantly more effective in depleting RBCs from CB, producing a final purity of 78% GlyAB-CD45+ cells compared to 11% with HetaSep and 9% with PrepaCyte (paired t-test, p<2.9x10-9 and p<3.6x10-9 respectively; n=8). To determine the effect of ErythroClear on the frequency of progenitors, CD34+/ALDHbright cells and CFUs were enumerated in CB samples before and after RBC depletion. The frequencies of CD34+, ALDHbright, and CD34+ALDHbright progenitors in fresh CB remained essentially unchanged following RBC depletion (p=0.75; n=6). Similarly, the frequency of CFUs measured by colony formation in MethoCult H4434 medium was not significantly altered after RBC depletion of fresh (p=0.16; n=11) and previously frozen CB (p=0.21; n=10) samples. RBC depletion using ErythroClear facilitated accurate counting of colonies using STEMvision, an imaging system for automated identification, classification, and enumeration of CFU assays of human blood or bone marrow cells. While automated colony counts differed significantly from manual counts for CFU assays with a high background of RBCs (p<0.02 for frozen-thawed CB [n=10]; p<0.01 for fresh CB [n=11]), very similar CFU numbers were obtained with both colony counting methods for samples in which RBCs were removed using ErythroClear (p=0.32 for thawed CB [n=10]; p=0.24 for fresh CB [n=11]). Taken together, these findings demonstrate that RBCs can be effectively removed from small CB samples by immunomagnetic removal of GlyA+ cells without affecting the frequency of HSPCs, and highlight the importance of depleting RBCs to ensure accurate and reliable enumeration of progenitors in CB samples. Disclosures Lam: STEMCELL Technologies Inc.: Employment. Wognum:STEMCELL Technologies Inc.: Employment. Thomas:STEMCELL Technologies Inc.: Employment. Eaves:STEMCELL Technologies Inc.: CEO and Owner Other. Szilvassy:STEMCELL Technologies Inc.: Employment.
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) | 0.001 | 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 | 0.001 |
| Research integrity | 0.000 | 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".