TESTING A TB VACCINE IN HUMANIZED MICE IN THE CONTEXT OF HIV
Bibliographic record
Abstract
HIV and Tuberculosis (TB) co-infection place an immense burden on health care systems as they act in synergy to worsen disease prognoses. TB is the most common cause of death in people living with HIV (PLWH) and in turn, HIV is the most significant risk factor for progressing from latent to active TB disease. While HIV and TB are endemic in sub-Saharan Africa, they also disproportionately affect marginalized populations in Canada. Unfortunately, the only licensed TB vaccine, BCG, does not protect from adult pulmonary TB and is not recommended for PLWH. Thus, the development of novel TB vaccines, which are safe and effective in PLWH, remains an urgent global necessity. We have found that humanized mice (hu-mice) are ideal models to research this as they can be successfully infected with HIV, TB and HIV/TB and recapitulate human disease pathology. A next-generation respiratory mucosal (RM) trivalent chimpanzee adenoviral-vectored vaccine (Tri:ChAd68) was developed and tested in our naïve and HIV-infected hu-mice. When immunizing naïve hu-mice, a trend of increased M.tb-specific CD4+ T cells producing IFNγ and TNFα in the lungs and spleen was observed. After subsequent M.tb infection, the vaccinated naïve hu-mice also exhibited significantly reduced lung mycobacterial burden, tissue dissemination and lung pathology. We then investigated the vaccine immunogenicity and ability to protect from TB in the context of HIV. Our immunized HIV-infected hu-mice were also able to produce M.tb-specific T cells and when challenged with M.tb, we observed a decreased trend in mycobacterial load in the lungs, indicating that the vaccine may be able to offer protection against TB when a prior HIV infection is present. These findings demonstrate the protective potential of the RM Tri:ChAd68 vaccine against TB disease for PLWH. In the future, we will test this vaccine in antiretroviral treated HIV-infected hu-mice to increase clinical significance.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".