Construction and Characterization of 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
INTRODUCTION Genetically modified adenoviruses (Ads) make attractive vectors for the delivery of exogenous DNA to mammalian cells for basic science and gene therapy applications. Ad vector production consists of (1) cloning a transgene into an infectious plasmid by in vivo recombination in bacteria, (2) rescuing and propagating the vector in complementing cells, and (3) purifying the vector. All of this can be accomplished using commercially available reagents, plasmids, and cell lines. First-generation Ads have a large cloning capacity (5-14 kbp) and efficiently transduce a wide range of both quiescent and proliferating cell types. They are readily propagated to produce high-titer stocks (10 11 -10 13 vector particles from a 3-L culture). Furthermore, Ads rarely integrate into the host genome and are relatively safe. However, Ad vector production typically takes 4-6 wk, and promiscuous host-cell transduction can occur in vivo. Furthermore, immune responses against viral proteins encoded by the vector backbone can occur, which limits the duration of transgene expression in vivo. Regardless of these limitations, Ad remains one of the more versatile and efficient gene delivery systems. Here, we discuss methods for the generation, propagation, purification, and characterization of first-generation Ad vectors.
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) | 0.000 | 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 it