Protein-mediated Fatty Acid Uptake in the Heart
Bibliographic record
Abstract
Long chain fatty acids (LCFAs) provide 70-80% of the energy for cardiac contractile activity. LCFAs are also essential for many other cellular functions, such as transcriptional regulation of proteins involved in lipid metabolism, modulation of intracellular signalling pathways, and as substrates for membrane constituents. When LCFA uptake exceeds the capacity for their cardiac utilization, the intracellular lipids accumulate and are thought to contribute to contractile dysfunction, arrhythmias, cardiac myocyte apoptosis and congestive heart failure. Moreover, increased cardiac myocyte triacylglycerol, diacylglycerol and ceramide depots are cardinal features associated with obesity and type 2 diabetes. In recent years considerable evidence has accumulated to suggest that, the rate of entry of long chain fatty acids (LCFAs) into the cardiac myocyte is a key factor contributing to a) regulating cardiac LCFA metabolism and b) lipotoxicity in the obese and diabetic heart. In the present review we i) examine the evidence indicating that LCFA transport into the heart involves a protein-mediated mechanism, ii) discuss the proteins involved in this process, including FAT/CD36, FABPpm and FATP1, iii) discuss the mechanisms involved in regulating LCFA transport by some of these proteins (including signaling pathways), as well as iv) the possible interactions of these proteins in regulating LCFA transport into the heart. In addition, v) we discuss how LCFA transport and transporters are altered in the obese/diabetic heart.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".