LPGAT1/LPLAT7 regulates acyl chain profiles at the sn-1 position of phospholipids in murine skeletal muscles
Bibliographic record
Abstract
Skeletal muscle consists of both fast- and slow-twitch fibers. Phospholipids are important structural components of cellular membranes, and the diversity of their fatty acid composition affects membrane characteristics. Although some studies have shown that acyl chain species in phospholipids differ among various muscle fiber types, the mechanisms underlying these differences are unclear. To investigate this, we analyzed phosphatidylcholine (PC) and phosphatidylethanolamine (PE) molecules in the murine extensor digitorum longus (EDL; fast-twitch) and soleus (slow-twitch) muscles. In the EDL muscle, the vast majority (93.6%) of PC molecules was palmitate-containing PC (16:0-PC), whereas in the soleus muscle, in addition to 16:0-PC, 27.9% of PC molecules was stearate-containing PC (18:0-PC). Most palmitate and stearate were bound at the sn-1 position of 16:0- and 18:0-PC, respectively, and 18:0-PC was found in type I and IIa fibers. The amount of 18:0-PE was higher in the soleus than in the EDL muscle. Peroxisome proliferator-activated receptor γ coactivator-1α (PGC-1α) increased the amount of 18:0-PC in the EDL. Lysophosphatidylglycerol acyltransferase 1 (LPGAT1) was highly expressed in the soleus compared with that in the EDL muscle and was upregulated by PGC-1α. LPGAT1 knockout decreased the incorporation of stearate into PC and PE in vitro and ex vivo and the amount of 18:0-PC and 18:0-PE in murine skeletal muscle with an increase in the level of 16:0-PC and 16:0-PE. Moreover, knocking out LPGAT1 decreased the amount of stearate-containing phosphatidylserine (18:0-PS), suggesting that LPGAT1 regulated the acyl chain profiles of phospholipids, namely, PC, PE, and PS, in the skeletal muscle.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".