Targeting cholesteryl ester accumulation in the heart improves cardiac insulin response
Bibliographic record
Abstract
BACKGROUND: Antibodies against the P3 sequence (Gly1127-Cys1140) of LRP1 (anti-P3 Abs) specifically block cholesteryl ester (CE) accumulation in vascular cells. LRP1 is a key regulator of insulin receptor (InsR) trafficking in different cell types. The link between CE accumulation and the insulin response are largely unknown. Here, the effects of P3 peptide immunization on the alterations induced by a high-fat diet (HFD) in cardiac insulin response were evaluated. METHODS: Irrelevant (IrP)- or P3 peptide-immunized rabbits were randomized into groups fed either HFD or normal chow. Cardiac lipid content was characterized by thin-layer chromatography, confocal microscopy, and electron microscopy. LRP1, InsR and glucose transporter type 4 (GLUT4) levels were determined in membranes and total lysates from rabbit heart. The interaction between InsR and LRP1 was analyzed by immunoprecipitation and confocal microscopy. Insulin signaling activity and glucose uptake were evaluated in HL-1 cells exposed to rabbit serum from the different groups. FINDINGS: HFD reduces cardiac InsR and GLUT4 membrane levels and the interactions between LRP1/InsR. Targeting the P3 sequence on LRP1 through anti-P3 Abs specifically reduces CE accumulation in the heart independently of changes in the circulating lipid profile. This restores InsR and GLUT4 levels in cardiac membranes as well as the LRP1/InsR interactions of HFD-fed rabbits. In addition, anti-P3 Abs restores the insulin signaling cascade and glucose uptake in HL-1 cells exposed to hypercholesterolemic rabbit serum. INTERPRETATION: LRP1-immunotargeting can block CE accumulation within the heart with specificity, selectivity, and efficacy, thereby improving the cardiac insulin response; this has important therapeutic implications for a wide range of cardiac diseases. FUNDING: Fundació MARATÓ TV3: grant 101521-10, Instiuto de Salud Carlos III (ISCIII) and ERDFPI18/01584, Fundación BBVA Ayudas a Equipos de Investigación 2019. SECyT-UNC grants PROYECTOS CONSOLIDAR 2018-2021; FONCyT, Préstamo BID PICT grant 2015-0807 and grant 2017-4497.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".