Logic-Based Modeling of Inflammatory Macrophage Crosstalk with Glomerular Endothelial Cells in Diabetic Kidney Disease

炎症 肾脏疾病 生物 串扰 糖尿病 癌症研究 细胞生物学 免疫学 内分泌学 光学 物理
作者
Krutika Patidar,Ashlee N. Ford Versypt
标识
DOI:10.1101/2023.04.04.535594
摘要

Diabetic kidney disease is a complication in 1 out of 3 patients with diabetes. Aberrant glucose metabolism in diabetes leads to an immune response causing inflammation and to structural and functional damage in the glomerular cells of the kidney. Complex cellular signaling lies at the core of metabolic and functional derangement. Unfortunately, the mechanism underlying the role of inflammation in glomerular endothelial cell dysfunction during diabetic kidney disease is not fully understood. Computational models in systems biology allow the integration of experimental evidence and cellular signaling networks to understand mechanisms involved in disease progression. We built a logic-based ordinary differential equations model to study macrophage-dependent inflammation in glomerular endothelial cells during diabetic kidney disease progression. We studied the crosstalk between macrophages and glomerular endothelial cells in the kidney using a protein signaling network stimulated with glucose and lipopolysaccharide. The network and model were built using the open-source software package Netflux. This modeling approach overcomes the complexity of studying network models and the need for extensive mechanistic details. The model simulations were fitted and validated against available biochemical data from in vitro experiments. The model identified mechanisms responsible for dysregulated signaling in macrophages and glomerular endothelial cells during diabetic kidney disease. In addition, we investigated the influence of signaling interactions and species that on glomerular endothelial cell morphology through selective knockdown and downregulation. We found that partial knockdown of VEGF receptor 1, PLC-γ, adherens junction proteins, and calcium partially recovered the endothelial cell fenestration size. Our model findings contribute to understanding signaling and molecular perturbations that affect the glomerular endothelial cells in the early stage of diabetic kidney disease.

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
bkagyin应助澄桦采纳,获得10
刚刚
李秋秋发布了新的文献求助10
刚刚
刚刚
李健应助大叉烧采纳,获得10
1秒前
Owen应助自信绮琴采纳,获得10
2秒前
3秒前
sunshine发布了新的文献求助10
4秒前
科研通AI6.3应助ayu采纳,获得10
4秒前
XrosGhost发布了新的文献求助10
5秒前
Jasper应助胖儿采纳,获得10
5秒前
Lucas应助mildjorker采纳,获得10
6秒前
BingyuLi完成签到,获得积分10
6秒前
皮代谷完成签到,获得积分10
6秒前
Jenifer完成签到,获得积分10
7秒前
7秒前
爆米花应助缓慢小松鼠采纳,获得10
8秒前
kk完成签到,获得积分10
9秒前
在水一方应助未来王院士采纳,获得10
9秒前
JZ133发布了新的文献求助10
10秒前
10秒前
10秒前
11秒前
fafafa完成签到 ,获得积分10
12秒前
12秒前
RioooOo完成签到,获得积分20
13秒前
刘一发布了新的文献求助20
13秒前
14秒前
15秒前
15秒前
16秒前
16秒前
风中颖应助科研通管家采纳,获得10
16秒前
8R60d8应助科研通管家采纳,获得10
16秒前
所所应助科研通管家采纳,获得10
16秒前
godblessyou应助科研通管家采纳,获得10
16秒前
16秒前
Lucas应助科研通管家采纳,获得50
16秒前
16秒前
赘婿应助科研通管家采纳,获得10
16秒前
田様应助科研通管家采纳,获得10
16秒前
高分求助中
Overcoming Stigma and Bias in Obesity Management 1200
Signals, Systems, and Signal Processing 610
Software that combines deep learning,3D reconstruction and CFD to analyze the state of carotid arteries from ultrasound imaging 500
Bounds for Statistical Estimation in Semiparametric Models 500
Forced degradation and stability indicating LC method for Letrozole: A stress testing guide 500
Ideology and Meaning-Making under the Putin Regime 450
Adhesion Science: Principles & Practice 400
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 物理 内科学 复合材料 催化作用 物理化学 光电子学 电极 细胞生物学 基因 无机化学
热门帖子
关注 科研通微信公众号,转发送积分 6492575
求助须知:如何正确求助?哪些是违规求助? 8290160
关于积分的说明 17690262
捐赠科研通 5584436
什么是DOI,文献DOI怎么找? 2915380
邀请新用户注册赠送积分活动 1892503
关于科研通互助平台的介绍 1750636