Nucleic Acid-Targeting Pathways Promote Inflammation in Obesity-Related Insulin Resistance
Bibliographic record
Abstract
Obesity-related inflammation of metabolic tissues, including visceral adipose tissue (VAT) and liver, are key factors in the development of insulin resistance (IR), though many of the contributing mechanisms remain unclear. We show that nucleic-acid-targeting pathways downstream of extracellular trap (ET) formation, unmethylated CpG DNA, or ribonucleic acids drive inflammation in IR. High-fat diet (HFD)-fed mice show increased release of ETs in VAT, decreased systemic clearance of ETs, and increased autoantibodies against conserved nuclear antigens. In HFD-fed mice, this excess of nucleic acids and related protein antigens worsens metabolic parameters through a number of mechanisms, including activation of VAT macrophages and expansion of plasmacytoid dendritic cells (pDCs) in the liver. Consistently, HFD-fed mice lacking critical responders of nucleic acid pathways, Toll-like receptors (TLR)7 and TLR9, show reduced metabolic inflammation and improved glucose homeostasis. Treatment of HFD-fed mice with inhibitors of ET formation or a TLR7/9 antagonist improves metabolic disease. These findings reveal a pathogenic role for nucleic acid targeting as a driver of metabolic inflammation in IR.
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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 | 0.001 |
| 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".