Genome Sequencing and Analysis of BCG Vaccine Strains
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Although the Bacillus Calmette-Guérin (BCG) vaccine against tuberculosis (TB) has been available for more than 75 years, one third of the world's population is still infected with Mycobacterium tuberculosis and approximately 2 million people die of TB every year. To reduce this immense TB burden, a clearer understanding of the functional genes underlying the action of BCG and the development of new vaccines are urgently needed. METHODS AND FINDINGS: Comparative genomic analysis of 19 M. tuberculosis complex strains showed that BCG strains underwent repeated human manipulation, had higher region of deletion rates than those of natural M. tuberculosis strains, and lost several essential components such as T-cell epitopes. A total of 188 BCG strain T-cell epitopes were lost to various degrees. The non-virulent BCG Tokyo strain, which has the largest number of T-cell epitopes (359), lost 124. Here we propose that BCG strain protection variability results from different epitopes. This study is the first to present BCG as a model organism for genetics research. BCG strains have a very well-documented history and now detailed genome information. Genome comparison revealed the selection process of BCG strains under human manipulation (1908-1966). CONCLUSIONS: Our results revealed the cause of BCG vaccine strain protection variability at the genome level and supported the hypothesis that the restoration of lost BCG Tokyo epitopes is a useful future vaccine development strategy. Furthermore, these detailed BCG vaccine genome investigation results will be useful in microbial genetics, microbial engineering and other research fields.
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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 | 0.000 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 it