A Defined Window for Efficient Gene Marking of Severe Combined Immunodeficient-Repopulating Cells Using a Gibbon Ape Leukemia Virus-Pseudotyped Retroviral Vector
Bibliographic record
Abstract
We have investigated the minimal time required for efficient transduction of human hematopoietic repopulating cells using a surrogate nonobese diabetic (NOD)/severe combined immunodeficient (SCID) xenoengraftment assay. Cord blood CD34+ cells were transduced to high levels over 24-48 hr in the presence of Flt-3 ligand, stem cell factor, interleukin 3, and interleukin 6. Under these conditions, high levels of NOD/SCID repopulating activity were preserved, but the levels of gene marking in engrafting cell populations measured by expression of a reporter transgene were low. Extension of the transduction period by 24 hr (total culture period, 72 hr) under the same cytokine conditions resulted in high levels of gene marking, but on closer analysis expression was limited predominantly to the myeloid population. Efficient transduction of both lymphoid and myeloid lineages could be achieved only if the transduction protocol was extended by a further 24 hr (total culture period, 96 hr), suggesting that myeloid lineage-committed precursors are capable of repopulation, and that over shorter time periods transduction is largely restricted to this population. This adds to the emerging evidence of heterogeneity within the SRC compartment, and has important implications for the interpretation of this assay in stem cell transplantation and gene transfer studies.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".