B Cell-Based Vaccine Transduced With ESAT6-Expressing Vaccinia Virus and Presenting α-Galactosylceramide Is a Novel Vaccine Candidate Against ESAT6-Expressing Mycobacterial Diseases
Bibliographic record
Abstract
Early secretory antigenic target-6 (ESAT6) is a potent immunogenic antigen expressed in Mycobacterium tuberculosis as well as in some non-tuberculous mycobacteria (NTM), such as M. kansasii. M. kansasii is one of the most clinically relevant species of NTM that causes mycobacterial lung disease, which is clinically indistinguishable from tuberculosis. In the current study, we designed a novel cell-based vaccine using B cells that were transduced with vaccinia virus expressing ESAT6 (vacESAT6), and presenting -galactosylceramide (αGC), a ligand of invariant NKT cells. We found that B cells loaded with αGC had increased levels of CD80 and CD86 after in vitro stimulation with NKT cells. Immunization of mice with B/αGC/vacESAT6 induced CD4+ T cells producing TNF-α and IFN-γ in response to heat-killed M. tuberculosis. Immunization of mice with B/αGC/vacESAT6 ameliorated severe lung inflammation caused by M. kansasii infection. We also confirmed that immunization with B/αGC/vacESAT6 reduced M. kansasii bacterial burden in the lungs. In addition, therapeutic administration of B/αGC/vacESAT6 increased IFN-γ+ CD4+ T cells and inhibited the progression of lung pathology caused by M. kansasii infection. Thus, B/αGC/vacESAT6 could be a potent vaccine candidate for the prevention and treatment of ESAT6-expressing mycobacterial infection caused by M. kansasii.
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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) | 0.000 | 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 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".