Bibliographic record
Abstract
The genus Mycobacterium comprises a variety of highly successful intracellular pathogens. Mycobacterium tuberculosis is the causative agent of tuberculosis (TB) in humans and currently infects one third of the world's population. Mycobacterium avium ssp. paratuberculosis is the established cause of Johne's disease in ruminants and is epidemiologically associated with Crohn's disease (CD) in humans. Both TB and CD are complex genetic diseases for which immunological pathways associated with disease susceptibility or resistance have been identified based on human genetic studies. Common polymorphisms in NOD2 have recently been described to predispose to CD. NOD2 encodes a receptor of the Nod-like receptor (NLR) family involved in mediating innate immunity upon recognition of fragments of bacterial peptidoglycan (PGN), a structural component of most bacterial cell wall. CD-associated NOD2 polymorphisms were shown to abrogate this response. While recent studies have uncovered an important role of NOD2 for the recognition of mycobacterial species, the consequences and significance of this recognition remain obscure. The first part of the work presented in this thesis investigates the consequences of NOD2-mediated recognition on innate responses, adaptive immunity and resistance to mycobacterial infection. Using Nod2-deficient mice as a model to study CD-associated NOD2 mutations in humans, we show that the NOD2 pathway is critical for both innate and acquired anti-mycobacterial immunity. Impaired mycobacterial recognition at early time points following infection altered the immunopathology in the lungs and resulted in decreased survival of Nod2-deficient mice when virulent M. tuberculosis was given by aerosol. The second part of this thesis focuses on the biochemical basis of mycobacterial recognition by NOD2. The bacterial N-acetylmuramic acid hydroxylase (NamH) enzyme introduces a specific modification in PGN. We correlated the presence of this enzyme in mycobacteri
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".