Modulation of epitope-specific antibody response by HIV Env immune-complex vaccines
Bibliographic record
Abstract
Abstract HIV-1 envelope (Env) antigen is an important target for both neutralizing and non-neutralizing antibodies (Ab) against the virus. In the RV144 vaccine trial, correlate for reduced risk of HIV acquisition is the presence of binding but non-neutralizing Ab to V1V2 and V3 loops of HIV Env gp120. However, induction of high titer, durable, and cross-reactive Ab responses against these Env regions by vaccination is still an elusive goal. Our past studies have shown that V3 immunogenicity can be significantly enhanced by vaccination with gp120/mAb immune complexes (IC) vs gp120 alone. Current study further examined parameters that confer enhanced immunogenicity to IC by testing in mice IC vaccines made with different HIV Env gp120 (clade B vs clade E) and mAb of different specificities (V3, V2, or CD4 binding site (CD4bs)). In addition, IC made of clade C gp140 and CD4bs mAb were also tested. The data showed that Greater titers of cross-reactive V3-binding Ab were induced by IC made of clade B gp120 and mAb to V2 or CD4bs as compare with gp120 alone, although the gp120/CD4bs IC was more potent in eliciting neutralizing V3 Ab. IC made with clade E gp120 or clade C gp140 did not show the same effects. Greater Ab responses to V1V2 were induced by IC made of clade E gp120 vs gp120 alone, regardless of the mAb used for IC, but the Ab were not neutralizing. IC made with clade B gp120 and clade C gp140 did not enhance V1V2 Ab titers. These results demonstrate the capacity of Env/mAb IC vaccines to modulate induction of Ab responses to V1V2 and V3, and this activity is dependent on both Env proteins and mAb used to form IC. Further exploration using a cocktail of IC is proposed to improve Ab repertoires generated upon vaccination.
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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 | 0.000 |
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".