Mice lacking NOX2 are hyperphagic and store fat preferentially in the liver
Bibliographic record
Abstract
Chronic low-grade inflammation is an important contributor to the development of insulin resistance, a hallmark of type 2 diabetes mellitus (T2DM). Obesity and high-fat feeding lead to infiltration of immune cells into metabolic tissues, promoting inflammation and insulin resistance. We hypothesized that macrophages from mice lacking NOX2 (Cybb), an essential component of the NADPH oxidase complex highly expressed in immune cells and associated with their inflammatory response, would be less inflammatory and that these mice would be protected from the development of high-fat-induced insulin resistance. Bone marrow-derived macrophages from NOX2 knockout (NOX2-KO) mice expressed lower levels of inflammatory markers (Nos2, Il6); however, NOX2-KO mice were hyperphagic and gained more weight than wild-type (WT) mice when fed either a chow or a high-fat (HF) diet. Surprisingly, NOX2-KO mice stored less lipid in epididymal white adipose tissue but more lipid in liver and had higher indexes of liver inflammation and macrophage infiltration than WT mice. Contrary to our hypothesis, HF-fed NOX2-KO mice were hyperinsulinemic and more insulin resistant than HF-fed WT mice, likely as a result of their higher hepatic steatosis and inflammation. In summary, NOX2 depletion promoted hyperphagia, hepatic steatosis, and inflammation with either normal or high-fat feeding, exacerbating insulin resistance. We propose that NOX2 participates in food intake control and lipid distribution in mice.
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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 | 0.000 |
| 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".