High saturated fat diet alters skeletal muscle phospholipid composition and increases SERCA activity (895.2)
Bibliographic record
Abstract
Sarcoplasmic/endoplasmic reticulum calcium ATPase (SERCA) is a transmembrane protein whose activity is, in part, dependent on its lipid environment. Past studies using synthetic membranes have demonstrated that 20‐22 carbon long monounsaturated fatty acids are associated with maximal SERCA activity. However, this association has not been examined in biological membranes. Thus, the objective of this study was to examine this association in a biological system and the response to high saturated fat (HSF) diet‐mediated membrane alterations in skeletal muscle. Female Wistar rats (28 days old) were fed control (CON; AIN93G, 7% soybean oil by weight) or HSF (AIN93G, 20% lard by weight) diet for 16 weeks. Mixed hind limb muscle phospholipids from rats fed a HSF diet had lower percent mole fraction of polyunsaturated fatty acids, unsaturation index (UI), and average chain length (ACL); and higher saturated fatty acids and SERCA activity compared to CON (p<0.05). Correlation analysis demonstrated ACL (R2= 0.83, p < 0.05) and UI (R2=0.53, p = 0.062) were negatively correlated with SERCA activity. These results suggest that SERCA activity may be influenced by phospholipid composition in biological membranes differently than in synthetic membranes. Future studies will examine the lipid annulus closely associated with SERCA. Grant Funding Source : Supported by Natural Sciences and Engineering Research Council (NSERC)
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".