Transcriptionally Targeted Adenovirus Vectors
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
Adenovirus vectors are the most highly efficient vehicles currently available for gene transfer to mammalian cells. Their ability to transduce both proliferating and non-dividing cells allows in vivo gene delivery, but the wide spectrum of cell types infected by adenovirus necessitates a requirement for targeting, particularly if the transduced gene is detrimental when expressed in inappropriate tissues. Over the past decade, numerous investigators have examined tissue- or tumor-specific enhancer-promoters as a means to transcriptionally target genes delivered by adenovirus vectors. We review here recent developments in adenovirus vectors including improvements in the vector backbone to maintain promoter specificity. In addition, we discuss the regulatory elements directing cell-specific expression of genes encoding telomerase, prostate-specific antigen, probasin, osteocalcin, tyrosinase, alpha-fetoprotein, surfactant B, and mammaglobin. Recent results using these regulatory sequences to target Ad vectors to cancer cells are highlighted.
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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 it