Enhanced HIV‐1 specific immune response by CpG ODN and HIV‐1 immunogen‐pulsed dendritic cells confers protection in the Trimera murine model of HIV‐1 infection
Bibliographic record
Abstract
We have recently developed a novel small animal model for HIV-1 infection (Ayash-Rashkovsky et al., http://www.fasebj.org/cgi/doi/10.1096/fj.04-3184fje; doi:10.1096/fj.04-3184fje). The mice were successfully infected with HIV-1 for 4-6 wk with different clades of either T- or M-tropic isolates. HIV-1 infection was accompanied by rapid loss of human CD4+ T cells, decrease in CD4/CD8 ratio, and increased T cell activation. HIV specific human humoral and cellular immune responses were observed in all HIV-1 infected animals. In the present study, HIV specific human immune responses, both humoral and cellular, were generated in noninfected Trimera mice, after their immunization with gp120-depleted HIV-1 antigen, presented by autologous human dendritic cells. Addition of CpG ODN to the antigen-pulsed DCs significantly enhanced (by 2- to 30-fold) the humoral and cellular HIV-1 specific immune responses. Only mice immunized with the HIV-1 immunogen and CpG were completely protected from infection with HIV-1 after challenge with high infection titers of the virus. This novel small animal model for HIV-1 infection may thus serve as an attractive platform for rapid testing of candidate HIV-1 vaccines and of adjuvants and may shorten the time needed for the development and final assessment of protective HIV-1 vaccines in human trials.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 | 0.002 |
| 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".