Circulating NOD1 Activators and Hematopoietic NOD1 Contribute to Metabolic Inflammation and Insulin Resistance
Bibliographic record
Abstract
Insulin resistance is a chronic inflammatory condition accompanying obesity or high fat diets that leads to type 2 diabetes. It is hypothesized that lipids and gut bacterial compounds in particular contribute to metabolic inflammation by activating the immune system; however, the receptors detecting these "instigators" of inflammation remain largely undefined. Here, we show that circulating activators of NOD1, a receptor for bacterial peptidoglycan, increase with high fat feeding in mice, suggesting that NOD1 could be a critical sensor leading to metabolic inflammation. Hematopoietic depletion of NOD1 did not prevent weight gain but protected chimeric mice against diet-induced glucose and insulin intolerance. Mechanistically, while macrophage infiltration of adipose tissue persisted, notably these cells were less pro-inflammatory, had lower CXCL1 production, and consequently, lower neutrophil chemoattraction into the tissue. These findings reveal macrophage NOD1 as a cell-specific target to combat diet-induced inflammation past the step of macrophage infiltration, leading to insulin resistance.
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 | 0.000 | 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 | 0.001 |
| 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 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".