The adiponectin‐derived peptide <scp>ALY688</scp> protects against the development of metabolic dysfunction‐associated steatohepatitis
Bibliographic record
Abstract
Metabolic dysfunction-associated steatohepatitis (MASH) is the severe form of non-alcoholic fatty liver disease which has a high potential to progress to cirrhosis and hepatocellular carcinoma, yet adequate effective therapies are lacking. Hypoadiponectinemia is causally involved in the pathogenesis of MASH. This study investigated the pharmacological effects of adiponectin replacement therapy with the adiponectin-derived peptide ALY688 (ALY688-SR) in a mouse model of MASH. Human induced pluripotent stem (iPS) cell-derived hepatocytes were used to test cytotoxicity and signaling of unmodified ALY688 in vitro. High-fat diet with low methionine and no added choline (CDAHF) was used to induce MASH and test the effects of ALY688-SR in vivo. Histological MASH activity score (NAS) and fibrosis score were determined to assess the effect of ALY688-SR. Transcriptional characterization of mice through RNA sequencing was performed to indicate potential molecular mechanisms involved. In cultured hepatocytes, ALY688 efficiently induced adiponectin-like signaling, including the AMP-activated protein kinase and p38 mitogen-activated protein kinase pathways, and did not elicit cytotoxicity. Administration of ALY688-SR in mice did not influence body weight but significantly ameliorated CDAHF-induced hepatic steatosis, inflammation, and fibrosis, therefore effectively preventing the development and progression of MASH. Mechanistically, ALY688-SR treatment markedly induced hepatic expression of genes involved in fatty acid oxidation, whereas it significantly suppressed the expression of pro-inflammatory and pro-fibrotic genes as demonstrated by transcriptomic analysis. ALY688-SR may represent an effective approach in MASH treatment. Its mode of action involves inhibition of hepatic steatosis, inflammation, and fibrosis, possibly via canonical adiponectin-mediated signaling.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".