Induction of Neutralizing Antibodies and Gag-Specific Cellular Immune Responses to an R5 Primary Isolate of Human Immunodeficiency Virus Type 1 in Rhesus Macaques
Bibliographic record
Abstract
The ability to generate antibodies that cross-neutralize diverse primary isolates is an important goal for human immunodeficiency virus type 1 (HIV-1) vaccine development. Most of the candidate HIV-1 vaccines tested in humans and nonhuman primates have failed in this regard. Past efforts have focused almost entirely on the envelope glycoproteins of a small number of T-cell line-adapted strains of the virus as immunogens. Here we assessed the immunogenicity of noninfectious virus-like particles (VLP) consisting of Gag, Pro (protease), and Env from R5 primary isolate HIV-1(Bx08). Immunogens were delivered to rhesus macaques in the form of either purified VLP, recombinant DNA and canarypox (ALVAC) vectors engineered to express VLP, or a combination of these products. Seroconversion to Gag and Pro was detected in all of the immunized animals. Antibodies that could neutralize HIV-1(Bx08) were detected in animals that received (i) coinoculations with DNA(Bx08) and VLP(Bx08), (ii) DNA(Bx08) followed by ALVAC(Bx08) boosting, and (iii) VLP(Bx08) alone. The neutralizing antibodies were highly strain specific despite the fact that they did not appear to be directed to linear epitopes in the V3 loop. Virus-specific cellular immune responses also were generated, as judged by the presence of Gag-specific gamma interferon (IFN-gamma)-producing cells. These cellular immune responses required the inclusion of DNA(Bx08) in the immunization modality, since few or no IFN-gamma-producing cells were detected in animals that received either VLP(Bx08) or ALVAC(Bx08) alone. The results demonstrate the feasibility of generating neutralizing antibodies and cellular immune responses that target an R5 primary HIV-1 isolate by vaccination in primates.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 teacher head, 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".