A Two-Phase Model of Early Atherosclerotic Plaque Development with LDL Toxicity Effects
원문 초록
Atherosclerosis is a chronic inflammatory cardiovascular disease in which fatty plaque is built inside an artery wall. Early atherosclerotic plaque development is typically characterized by inflammatory tissues primarily consisting of foam cells and macrophages. We present a biphasic model that explores early plaque growth to emphasize the role of cytokines (particularly, Monocyte Chemoattractant Protein-1) and oxidized low-density lipoprotein (oxLDL) in monocyte recruitment and foam cell production, respectively. The plaque boundary is assumed to move at the same speed as the inflammatory tissues close to the periphery. This study discusses the oxLDL cholesterols recruitment inside intima and their internalization by the inflammatory cells. Excessive intracellular cholesterol accumulation becomes toxic to macrophage foam cells, leading to cell death beyond a threshold. Our findings reveal that initially, the plaque evolves rapidly, and the growth rate eventually reduces because of the cholesterol-induced toxicity. The present study manifests that higher oxLDL cholesterol flux reduces plaque growth rate, while elevated cytokines flux promotes the corresponding plaque growth behaviour. Between oxLDL cholesterol and intracellular cholesterol, the second one is much more effective towards the growth of inflammatory tissue. The cholesterol-based toxicity-induced cell death parameters are crucial in flattening the plaque growth profile. A detailed analysis of the model presented in this article provides critical insights into the various biochemical and cellular mechanisms behind early plaque development.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
Quantile-Based Deep Reinforcement Learning using Two-Timescale Policy Gradient Algorithms
Leveraging the two timescale regime to demonstrate convergence of neural networks
Training a Two Layer ReLU Network Analytically
MiniRBT: A Two-stage Distilled Small Chinese Pre-trained Model
FinalMLP: An Enhanced Two-Stream MLP Model for CTR Prediction
Using Simple Incentives to Improve Two-Sided Fairness in Ridesharing Systems
토론
이 논문과 연결된 포럼 글이 아직 없습니다.