Lipocalin-2 in Fructose-Induced Fatty Liver Disease
Bibliographic record
Abstract
The intake of excess dietary fructose most often leads to non-alcoholic fatty liver disease (NAFLD). Fructose is metabolized mainly in the liver and its chronic consumption results in lipogenic gene expression in this organ. However, precisely how fructose is involved in NAFLD progression is still not fully understood, limiting therapy. Lipocalin-2 (LCN2) is a small secreted transport protein that binds to fatty acids, phospholipids, steroids, retinol, and pheromones. LCN2 regulates lipid and energy metabolism in obesity and is upregulated in response to insulin. We previously discovered that LCN2 has a hepatoprotective effect during hepatic insult, and that its upregulation is a marker of liver damage and inflammation. To investigate if LCN2 has impact on the metabolism of fructose and thereby arising liver damage, we fed wild type and Lcn2-/- mice for 4 or 8 weeks on diets that were enriched in fructose either by adding this sugar to the drinking water (30% w/v), or by feeding a chow containing 60% (w/w) fructose. Body weight and daily intake of food and water of these mice was then measured. Fat content in liver sections was visualized using Oil Red O stain, and expression levels of genes involved in fat and sugar metabolism were measured by qRT-PCR and Western blot analysis. We found that fructose-induced steatosis and liver damage was more prominent in female than in male mice, but that the most severe hepatic damage occurred in female mice lacking LCN2. Unexpectedly, consumption of elevated fructose did not induce de novo lipogenesis or fat accumulation. We conclude that LCN2 acts in a lipid-independent manner to protect the liver against fructose-induced damage.
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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) | 0.002 | 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".