Protective Efficacy of Subunit Vaccine Expressing Rv0976c Against Tuberculosis
Bibliographic record
Abstract
Objectives: The construction of subunit vaccines based on antigens that can induce strong cellular immunity is a widely accepted strategy to develop new tuberculosis vaccines. This study screens immunogens with potential for subunit vaccine development from seven candidate antigens and then verifies their vaccine efficacy. Design: C57BL/6 mice were immunized subcutaneously with purified PPE19, PPE50, FadD21, Rv1505c, Rv1506c, Rv2035, and Rv0976c proteins formulated with Freund’s adjuvant to evaluate both the antigen-specific Th1 cellular immune responses and IgG level. After the vaccination of mice with recombined pcDNA3.1 expressing Rv0976c, intravenous or aerosol infection with M. tb were further challenged to assess protective efficacy. Results: Purified PPE19, PPE50, FadD21, and Rv0976c proteins generated strong antigen-specific Th1 cellular immune responses in mice. Compared to Ag85A, Rv0976c also stimulated higher IgG antibody level in mice. In particular, Rv0976c stimulated high and specific IgG antibody levels in serum from TB patients. The vaccination of mice with DNA vaccines expressing Rv0976c, followed by intravenous challenge with Bacillus Calmette–Guerin (BCG) Pasteur or M. tb, resulted in significant levels of protection that are comparable to or better than that afforded by the two leading antigens, Ag85A and PPE18. Conclusions: These results indicated that Rv0976c was a better protective antigen. Future studies to combine Rv0976c with other antigens and evaluate its effectiveness as a booster of BCG or as a therapeutic vaccine are warranted.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 teacher head, 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".