Male Mice Lacking NLRX1 Are Partially Protected From High-Fat Diet–Induced Hyperglycemia
Bibliographic record
Abstract
Nod-like receptor (NLR)X1 is an NLR family protein that localizes to the mitochondrial matrix and modulates reactive oxygen species production, possibly by directly interacting with the electron transport chain. Recent work demonstrated that cells lacking NLRX1 have higher oxygen consumption but lower levels of adenosine triphosphate, suggesting that NLRX1 might prevent uncoupling of oxidative phosphorylation. We therefore hypothesized that NLRX1 might regulate whole-body energy metabolism through its effect on mitochondria. Male NLRX1 whole-body knockout (KO) mice and wild-type (WT) C57BL/6N controls were fed a low-fat or a high-fat (HF) diet for 16 weeks from weaning. Contrary to this hypothesis, there were no differences in body weight, adiposity, energy intake, or energy expenditure between HF-fed KO and WT mice, but instead HF KO mice were partially protected from the development of diet-induced hyperglycemia. Additionally, HF KO mice did not present with hyperinsulinemia during the glucose tolerance test, as did HF WT mice. There were no genotype differences in insulin tolerance, which led us to consider a pancreatic phenotype. Histology revealed that KO mice were protected from HF-induced pancreatic lipid accumulation, suggesting a potential role for NLRX1 in pancreatic dysfunction during the development diet-induced type 2 diabetes mellitus. Hence, NLRX1 depletion partially protects against postabsorptive hyperglycemia in obesity that may be linked to the prevention of pancreatic lipid accumulation. Although the actual mechanisms restoring glucose and insulin dynamics remain unknown, NLRX1 emerges as a potentially interesting target to inhibit for the prevention of type 2 diabetes mellitus.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".