Relationship between DNA Methylation Profiles and Active Tuberculosis Development from Latent Infection: a Pilot Study in Nested Case-Control Design
Bibliographic record
Abstract
Approximately a quarter of the world population had been infected with Mycobacterium tuberculosis, and about 5 to 10% of these individuals might develop active disease in their lifetimes. As a critical component of the "end TB strategies," preventive treatment was shown to protect 60 to 90% of high-risk LTBIs from developing active disease. Developing new TB screening tools based on blood-based biomarkers, which could identify and rule out active TB from LTBI, are prerequisite before initialing intervention. We tried to explore potential DNA methylation diagnostic biomarkers through retrospectively detected DNA methylation profiles pre- and post-TB diagnosis. Eight dmCpGs were identified, and the combination of "cg02206980 + cg02214623 + cg12159502 + cg12321798" showed a sensitivity of 93.33% and a specificity of 86.67%. The preliminary results provided new insight into detecting the DNA methylation level as a potential tool to distinguish TB from LTBI.
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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 | 0.002 | 0.000 |
| 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 | 0.000 |
| 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 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".