IRW improves diet-induced non-alcoholic fatty liver disease by reducing steatosis associated with increased capacity for oxidative phosphorylation
Bibliographic record
Abstract
Non-alcoholic fatty liver disease (NAFLD), the hepatic manifestation of the metabolic syndrome, remains without approved pharmacological treatment. Food-derived bioactive peptides can aid in the management of metabolic conditions including hypertension, obesity and insulin resistance. IRW (isoleucine-arginine-tryptophan) is a tripeptide produced from egg white with angiotensin converting enzyme-inhibitory properties. IRW supplementation elicits antihypertensive effects, improves skeletal muscle insulin signaling and glucose tolerance while reducing body weight gain. In this study, we hypothesized that IRW supplementation would prevent high-fat diet (HFD)-induced NAFLD by modulating hepatic lipid metabolism and increasing mitochondrial content. We found that IRW prevents diet-induced NAFLD, while rosiglitazone (ROSI) treatment worsens it. IRW decreases hepatic triglyceride content and lipid droplet size compared to HFD and ROSI. IRW increases the hepatic mitochondrial complexes and citrate synthase activity, phosphorylation of 5'-AMP-activated protein kinase and microsomal triglyceride transfer protein abundance compared to HFD. Compared with ROSI, IRW increases phosphorylated acetyl CoA carboxylase and mitochondrial complexes. Overall, the hypothesis is supported by these findings.
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".