Multiphasic triacylglycerol dynamics in the intact heart during acute in vivo overexpression of CD36
Bibliographic record
Abstract
Cardiac triacylglycerol (TAG) stores buffer the intracellular availability of long chain fatty acid (LCFA) that act as nuclear receptor ligands, substrate for lipotoxic derivatives, and high energy-yield fuel. The kinetic characteristics of TAG turnover and homeostatic mechanisms linking uptake and storage dynamics in hearts have until now remained elusive. This work examines TAG pool dynamics in the intact beating heart, under normal conditions and in response to acute gene expression-induced changes in CD36. Dynamic mode (13)C NMR elucidated multiple kinetic processes in (13)C-palmitate incorporation into TAG: an initial, saturable exponential component and a slower linear rate. Although previous work indicates the linear component to reflect TAG turnover, we hypothesized the saturable exponential to reflect transport of LCFA across the sarcolemma. Thus, we overexpressed the LCFA transporter CD36 through cardiac-specific adenoviral infection in vivo. Within 72 h, CD36 expression was increased 40% in intact hearts, accelerating the exponential phase relative to PBS-infused hearts. TAG turnover also increased with elevations in adipose triglyceride lipase (ATGL) and a modest increase in diacylglycerol acyltransferase 1 (DGAT1), without a significant expansion of the intracellular lipid pools. The results demonstrate a dynamic system of reciprocal gene regulation that couples saturable LCFA uptake across the sarcolemma to TAG synthesis/lipolysis rates.
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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 | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".