Transduction of Human CD34+CD38- Bone Marrow and Cord Blood-Derived SCID-Repopulating Cells with Third-Generation Lentiviral Vectors
Bibliographic record
Abstract
The major limitations of Moloney murine leukemia virus (MoMLV)-based vectors for human stem cell applications, particularly those requiring bone marrow (BM) stem cells, include their requirement for mitosis and retroviral receptor expression. New vectors based upon lentiviruses such as HIV-1 exhibit properties that may circumvent these problems. We report that novel third-generation, self-inactivating lentiviral vectors, expressing enhanced green fluorescent protein (EGFP) and pseudotyped with vesicular stomatitis virus G glycoprotein (VSV-G), can efficiently transduce primitive human repopulating cells derived from human BM and cord blood (CB) tested by the SCID-repopulating cell (SRC) assay. Highly purified CD34+ CD38- CB or BM cells were efficiently transduced (4-69%) and stably expressed in EGFP for 40 days in culture following infection for only 24 h without fibronectin, polybrene, or cytokines. Nonobese diabetic/severe combined immune-deficient (NOD/SCID) mice transplanted with transduced cells from either CB or BM donors were well engrafted, demonstrating maintenance of SRC during the infection procedure. Serially obtained femoral BM samples indicated that the proportion of EGFP+ cells within both myeloid and lymphoid lineages was maintained or even increased over time, averaging 42.3 +/- 6.6% for BM donors and 23.3 +/- 7.2% for CB at 12 weeks. Thus, the third-generation lentivectors readily transduce human CB and BM stem cells, under minimal conditions of ex vivo culture, where MoMLV-based vectors are ineffective. Since CB is inappropriate for most therapeutic applications, the efficient maintenance and transduction of BM-derived SRC during the short infection procedure are notable advantages of lentivectors.
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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) | 0.002 | 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".