Faculty Opinions recommendation of Association of muscle lipidomic profile with high-fat diet-induced insulin resistance across five mouse strains.
Bibliographic record
Abstract
Different mouse strains exhibit variation in their inherent propensities to develop metabolic disease.We recently showed that C57BL6, 129X1, DBA/2 and FVB/N mice are all susceptible to high-fat diet-induced glucose intolerance, while BALB/c mice are relatively protected, despite changes in many factors linked with insulin resistance.One parameter strongly linked with insulin resistance is ectopic lipid accumulation, especially metabolically active ceramides and diacylglycerols (DAG).This study examined diet-induced changes in the skeletal muscle lipidome across these five mouse strains.High-fat feeding increased total muscle triacylglycerol (TAG) content, with elevations in similar triacylglycerol species observed for all strains.There were also generally consistent changes across strains in the abundance of different phospholipid (PL) classes and the fatty acid profile of phospholipid molecular species, with the exception being a strain-specific difference in phospholipid species containing two polyunsaturated fatty acyl chains in BALB/c mice (i.e. a diet-induced decrease in the other four strains, but no change in BALB/c mice).In contrast to TAG and PL, the high-fat diet had a minor influence on DAG and ceramide species across all strains.These results suggest that widespread alterations in muscle lipids are unlikely a major contributors to the favourable metabolic profile of BALB/c mice and rather there is a relatively conserved high-fat diet response in muscle of most mouse strains.
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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.225 | 0.121 |
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".