Glucocorticoid-Inducible Retrovector for Regulated Transgene Expression in Genetically Engineered Bone Marrow Stromal Cells
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Transplantable bone marrow stromal cells can be utilized for cell therapy of mesenchymal disorders. They can also be genetically engineered to express synthetic transgenes and subsequently serve as a platform for systemic delivery of therapeutic proteins in vivo. Inducible production of therapeutic proteins would markedly enhance the usefulness of stromal cells for cell therapy applications. We determined whether synthetic corticosteroid hormones can be used to tightly control transgene expression via the glucocorticoid response pathway in primary bone marrow stromal cells. This regulatory mechanism does not require the presence of potentially immunogenic prokaryotic or chimeric "Trans-activators." Further, synthetic corticosteroids are pharmaceutical agents that can be readily used in vivo. We designed a self-inactivating retroviral vector in which expression of the green fluorescent protein (GFP) reporter is controlled by a minimal synthetic promoter composed of five tandem glucocorticoid response elements upstream of a TATAA box. Vesicular stomatitis virus G-pseudotyped retroparticles were synthesized and utilized to transduce cultured cell lines and primary rat bone marrow stromal cells. We have shown that primary rat bone marrow stromal cells could be efficiently engineered with our GRE-containing retrovector, basal reporter expression was low in the absence of exogenous synthetic corticosteroids, and GFP expression was dexamethasone inducible and reversible. To summarize, this strategy allows dexamethasone-induced, "on-demand" transgene expression from transplantable genetically engineered bone marrow stromal cells.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.001 | 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 it