Tissue-Specific Splicing and Dietary Interaction of a Mutant As160 Allele Determine Muscle Metabolic Fitness in Rodents
Bibliographic record
Abstract
Ethnic groups are physiologically and genetically adapted to their diets. Inuit bear a frequent AS160R684X mutation that causes type 2 diabetes. Whether this mutation evolutionarily confers adaptation in Inuit and how it causes metabolic disorders upon dietary changes are unknown due to limitations in human studies. Here, we develop a genetically-modified rat model bearing an orthologous AS160R693X mutation, which mimics human patients exhibiting postprandial hyperglycemia and hyperinsulinemia. Importantly, a sugar-rich diet aggravates metabolic abnormalities in AS160R693X rats. The AS160R693X mutation diminishes a dominant long-variant AS160 without affecting a minor short-variant AS160 in skeletal muscle, which suppresses muscle glucose utilisation but induces fatty acid oxidation. This fuel switch suggests a possible adaptation in Inuit who traditionally had lipid-rich hypoglycemic diets. Finally, induction of the short-variant AS160 restores glucose utilisation in rat myocytes and a mouse model. Our findings have implications for development of precision treatments for patients bearing the AS160R684X mutation.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".