A novel genetically engineered<i>Mycobacterium smegmatis</i>-based vaccine promotes anti-TB immunity
Bibliographic record
Abstract
Evaluation of: Sweeney KA, Dao DN, Goldberg MF et al. A recombinant Mycobacterium smegmatis induces potent bactericidal immunity against Mycobacterium tuberculosis. Nat. Med. 17, 1261–1268 (2011).Pulmonary TB remains a global health threat. Prophylactic immunization with Mycobacterium bovis BCG is the only key strategy to control TB. Ineffectiveness of BCG immunization in TB-endemic areas and BCG-related safety issues in HIV-positive infants have prompted the development of new TB vaccines. As enhanced understanding of the immune evasion mechanism of Mycobacterium tuberculosis will help develop new vaccines, Sweeney et al. studied the role of the esx-3 locus in mycobacterial pathogenesis. They have identified a previously unappreciated function of the esx-3 locus in innate immune evasion. They further discovered that Mycobacterium smegmatis with the esx-3 genes deleted could function as a novel vaccine vector with an enhanced innate immune-activating property. This vector, when engineered to express M. tuberculosis esx-3, was found to be a potent TB vaccine capable of a level of protection superior to that of BCG when administered via the intravenous route.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.006 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".