Cord blood natural killer T (NKT) cells
Bibliographic record
Abstract
In cord blood (CB) transplantation, the GVHD rate is low despite HLA-disparity, and the rate of leukemia relapse is identical to that of bone marrow transplantation. In a murine model, NKT cells demonstrate a graft-versus-leukemia activity without causing GVHD. We therefore investigated CB-natural killer-T (NKT) cells, by comparing their phenotypic properties with those of adult blood (AB)-NKT cells. Mononuclear cells from 12 CB and 12 AB samples were analyzed by flow cytometry after triple-staining with MoAb against CD56, CD3 and a third MoAb. NKT cells were defined as CD3+CD56+ cells. The percentage of NKT cells was 5-fold lower in CB than in AB (0.35 vs 1.56%, P = 0.01). CD28, a marker of naive T-cells, was more frequently expressed on CB-NKT cells than on AB-NKT cells (96 vs 85%, P = 0.02). The percentage of CD11c-(integrin aX subunit) positive NKT cells was higher in CB than in AB (85 vs 45 %; P < 0.001 in both). The percentage of NKT cells expressing intracellular perforin and granzyme B, and surface FAS-L was higher in CB than in AB (83 vs 60 %; 88 vs 51% and 71 vs 45%; P < 0.04). No difference between CB and AB-NKT cells was noted for the expression of CD2, CD57, L-selectin, TRAIL, FAS-L, NKG2A, NKB1, and HLA-DR. Because of their scarcity, CB-NKT cells can not be functionally studied without prior expansion. Taken together, our results show that CB-NKT cells are very scarce in CB and that their phenotype resembles that of AB-NKT cells, except that a significantly higher percentage of CB-NKT cells express cytotoxicity-associated proteins.
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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 | 0.000 | 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".