Nod proteins link bacterial sensing and autophagy
Bibliographic record
Abstract
Autophagy is one of the main cellular degradation systems in eukaryotes, responsible for the elimination of long-lived proteins and damaged organelles. Besides its well-documented role as a housekeeping mechanism, autophagy has recently caught the attention of groups working in the fields of microbiology and immunology, especially those working in innate immunity. In particular, the highly specific segregation and degradation of intracellular bacteria by the autophagic machinery was a matter of great interest. However, it was still unclear how the autophagy machinery could target intracellular bacteria with such specificity. We have recently analyzed the role of the intracellular peptidoglycan (PG) receptors Nod1 and Nod2 as a link between intracellular bacterial sensing and the induction of autophagy. Our results demonstrated that Nod2 recruits the critical autophagy protein ATG16L1 to the plasma membrane during bacterial invasion and that cells expressing mutations in these proteins--two of the most important associated with Crohn disease--autophagy is defective upon infection or stimulation with the bacterial peptidoglycan fragment MDP. Thus, our findings put together two genes previously reported as independent risk factors for the development of Crohn disease and open a venue in the study of new therapies to cure the disease.
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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 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".