Isolation of Sarcolemmal Plasma Membranes by Mechanically Skinning Rat Skeletal Muscle Fibers for Phospholipid Analysis
Bibliographic record
Abstract
Membrane phospholipid (PL) composition has been shown to affect cellular function by altering membrane physical structure. The sarcolemma plasma membrane (SLpm) is integral to skeletal muscle function and health. Previous studies assessing SLpm PL composition have demonstrated contamination from transverse (t)-tubule, sarcoplasmic reticulum, and nuclear membranes. This study assessed the possibility of isolating SL by mechanically skinning skeletal muscle fiber segments for the analysis of SLpm PL composition. Mechanically skinned SLpm from rat extensor digitorum longus (EDL) muscle fibers underwent Western blot analysis to assess contamination from t-tubule, sarcoplasmic reticulum, nuclear and mitochondrial membranes. The results indicate that isolated SLpm had minimal nuclear and mitochondrial membrane contamination and was void of contamination from sarcoplasmic reticulum and t-tubule membranes. After performing both high-performance thin layer chromatography and gas chromatography, we found that the SLpm obtained by mechanical skinning had higher sphingomyelin and total fatty acid saturation and lower phosphatidylcholine when compared to previous literature. Thus, by avoiding the use of various chemical treatments and membrane fractionation, we present data that may truly represent the SLpm and future studies can use this technique to assess potential changes under various perturbations and disease conditions such as insulin resistance and muscular dystrophy.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".