Stable Marker Gene Transfer into Human Bone Marrow Stromal Cells and Their Progenitors Using Novel Herpesvirus Saimiri-Based Vectors
Bibliographic record
Abstract
We have evaluated the ability of new herpesvirus saimiri (HVS)-based vectors to deliver a marker gene green fluorescent protein (GFP) into human bone marrow (BM) stromal cells and their progenitors. Stromal cells expanded from adherent layers of long-term BM cultures (LTC) were susceptible to HVS-based infection in a dose-dependent manner, and the efficiency of 94.8 +/- 2.0% was achieved using single exposure with HVS/EGFP vector at multiplicity of infection (moi) of approximately 50. Colony-forming unit-fibroblast (CFU-F) assay established the ability of HVS-based vectors to infect progenitors for bone marrow stroma fibroblasts and transfer the marker gene over multiple cell divisions in the absence of selective pressure. HVS was not toxic for stromal cells and progenitors and no viral replication was detected upon growth of modified stroma. On the basis these data, we believe that HVS-based constructs can offer a new opportunity for selective gene delivery into bone marrow stromal cells and progenitors. The ability of HVS to infect nondividing cells can be considered advantageous in the development of both ex vivo and in vivo strategies.
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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 | 0.000 |
| 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 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".