Systemic Immunization with an ALVAC-HIV-1/Protein Boost Vaccine Strategy Protects Rhesus Macaques from CD4<sup>+</sup>T-Cell Loss and Reduces both Systemic and Mucosal Simian-Human Immunodeficiency Virus SHIV<sub>KU2</sub>RNA Levels
Bibliographic record
Abstract
Transmission of human immunodeficiency virus type 1 (HIV-1) occurs primarily via the mucosal route, suggesting that HIV-1 vaccines may need to elicit mucosal immune responses. Here, we investigated the immunogenicity and relative efficacy of systemic immunization with two human ALVAC-HIV-1 recombinant vaccines expressing Gag, Pol, and gp120 (vCP250) or Gag, Pol, and gp160 (vCP1420) in a prime-boost protocol with their homologous vaccine native Env proteins. The relative efficacy was measured against a high-dose mucosal exposure to the pathogenic neutralization-resistant variant SHIV(KU2) (simian-human immunodeficiency virus). Systemic immunization with both vaccine regimens decreased viral load levels not only in blood but unexpectedly also in mucosal sites and protected macaques from peripheral CD4+ T-cell loss. This protective effect was stronger when the gp120 antigen was included in the vaccine. Inclusion of recombinant Tat protein in the boosting phase along with the Env protein did not contribute further to the preservation of CD4+ T cells. Thus, systemic immunization with ALVAC-HIV-1 vaccine candidates elicits anti-HIV-1 immune responses able to contain virus replication also at mucosal sites in macaques.
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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) | 0.001 | 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 | 0.000 |
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 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".