Expression of HIV-1 gag and env genes using the vesicular stomatitis virus vector system
Bibliographic record
Abstract
Traditional vaccine methods have long been employed to control widespread infectious diseases, but so far, all commercially available vaccine strategies have been inadequate in efforts to develop an effective therapeutic HIV vaccine. However, recent advancements in immunological research have led to the generation of novel vaccine strategies, one of which is the recombinant virus vaccine, a method of particular interest that has shown promise in the clearance of HIV infection within HIV-positive patients who have retained immunocompetence. This study examined the stability of expression of HIV-1 genes, gag and env, through a recombinant virus vector, a recombinant vesicular stomatitis virus (VSV), a temperature-sensitive mutant genetically modified to contain the select HIV-1 genes (VSVInd(GML)HIV-1gag-env). For SDS-PAGE, cells infected with VSVInd(GML) temperature-sensitive mutants were incubated at 31 °C and 37 °C, the permissible and semi-permissible growth conditions respectively. Western blot analyses were used to quantitate levels of protein expression of full VSV proteins, Gag, and Env using a primary rabbit antibody of anti-VSV anti-serum and a secondary anti-IgG from rabbit, a primary antibody of anti-p24 anti-serum and a secondary anti-IgG from rabbit, and a primary goat antibody, anti-gp120, and a secondary anti-IgG from goat, respectively. Results indicated that the VSVInd(GML) vector system allowed for high levels of expression of HIV-1 gag and env genes. It is known that the expression of these genes induce the production of major neutralizing antibodies and the stimulation of cytotoxic T lymphocytes, therefore this finding reveals the potential to use a genetically modified recombinant VSV as a universal vector for the development of recombinant virus vaccines. Specifically, the VSVInd(GML) mutant vector is thus an attractive candidate for the viral vector of a therapeutic HIV vaccine system.
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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) | 0.001 | 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".