Faculty Opinions recommendation of Non-apoptotic role of BID in inflammation and innate immunity.
Bibliographic record
Abstract
Innate immunity is a fundamental defence response that depends on evolutionarily conserved pattern recognition receptors for sensing infections or danger signals. Nucleotide-binding and oligomerization domain (NOD) proteins are cytosolic pattern-recognition receptors of paramount importance in the intestine, and their dysregulation is associated with inflammatory bowel disease. They sense peptidoglycans from commensal microorganisms and pathogens and coordinate signalling events that culminate in the induction of inflammation and anti-microbial responses. However, the signalling mechanisms involved in this process are not fully understood. Here, using genome-wide RNA interference, we identify candidate genes that modulate the NOD1 inflammatory response in intestinal epithelial cells. Our results reveal a significant crosstalk between innate immunity and apoptosis and identify BID, a BCL2 family protein, as a critical component of the inflammatory response. Colonocytes depleted of BID or macrophages from Bid(-/-) mice are markedly defective in cytokine production in response to NOD activation. Furthermore, Bid(-/-) mice are unresponsive to local or systemic exposure to NOD agonists or their protective effect in experimental colitis. Mechanistically, BID interacts with NOD1, NOD2 and the IκB kinase (IKK) complex, impacting NF-κB and extracellular signal-regulated kinase (ERK) signalling. Our results define a novel role of BID in inflammation and immunity independent of its apoptotic function, furthering the mounting evidence of evolutionary conservation between the mechanisms of apoptosis and immunity. PMID: 21552281 Funding information This work was supported by: Canadian Institutes of Health Research, Canada Grant ID: MOP 82801
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.407 | 0.219 |
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".