scholarly journals A tapered channel microfluidic device for comprehensive cell adhesion analysis, using measurements of detachment kinetics and shear stress-dependent motion

2012 ◽  
Vol 6 (1) ◽  
pp. 014107 ◽  
Author(s):  
Peter Rupprecht ◽  
Laurent Golé ◽  
Jean-Paul Rieu ◽  
Cyrille Vézy ◽  
Rosaria Ferrigno ◽  
...  
Keyword(s):  
Shear Stress ◽  
Cell Adhesion ◽  
Microfluidic Device ◽  
Tapered Channel ◽  
Stress Dependent

Shear stress-dependent cell detachment from temperature-responsive cell culture surfaces in a microfluidic device

Biomaterials ◽  
2012 ◽  
Vol 33 (30) ◽  
pp. 7405-7411 ◽  
Author(s):  
Zhonglan Tang ◽  
Yoshikatsu Akiyama ◽  
Kazuyoshi Itoga ◽  
Jun Kobayashi ◽  
Masayuki Yamato ◽  
...  
Keyword(s):  
Cell Culture ◽  
Shear Stress ◽  
Microfluidic Device ◽  
Cell Detachment ◽  
Temperature Responsive ◽  
Dependent Cell ◽  
Stress Dependent ◽  
Responsive Cell

scholarly journals Fluid–structure interactions (FSI) based study of low-density lipoproteins (LDL) uptake in the left coronary artery

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Xueping Chen ◽  
Jian Zhuang ◽  
Huanlei Huang ◽  
Yueheng Wu
Keyword(s):  
Shear Stress ◽  
Coronary Artery ◽  
Left Coronary Artery ◽  
Arterial Wall ◽  
Low Density Lipoproteins ◽  
Patient Specific ◽  
Low Density ◽  
Fluid Structure ◽  
Flowing Blood ◽  
Stress Dependent

AbstractThe purpose of this study is to compare the effect of the different physical factors on low-density lipoproteins (LDL) accumulation from flowing blood to the arterial wall of the left coronary arteries. The three-dimensional (3D) computational model of the left coronary arterial tree is reconstructed from a patient-specific computed tomography angiography (CTA) image. The endothelium of the coronary artery is represented by a shear stress dependent three-pore model. Fluid–structure interaction ($$FSI$$ FSI ) based numerical method is used to study the LDL transport from vascular lumen into the arterial wall. The results show that the high elastic property of the arterial wall decreases the complexity of the local flow field in the coronary bifurcation system. The places of high levels of LDL uptake coincide with the regions of low wall shear stress. In addition, hypertension promotes LDL uptake from flowing blood in the arterial wall, while the thickened arterial wall decreases this process. The present computer strategy combining the methods of coronary CTA image 3D reconstruction, $$FSI$$ FSI simulation, and three-pore modeling was illustrated to be effective on the simulation of the distribution and the uptake of LDL. This may have great potential for the early prediction of the local atherosclerosis lesion in the human left coronary artery.

scholarly journals Heart rate reduction with ivabradine promotes shear stress-dependent anti-inflammatory mechanisms in arteries

2016 ◽  
Vol 116 (07) ◽  
pp. 181-190 ◽  
Author(s):  
Luong Le ◽  
Hayley Duckles ◽  
Torsten Schenkel ◽  
Marwa Mahmoud ◽  
Jordi Tremoleda ◽  
...  
Keyword(s):  
Heart Rate ◽  
Shear Stress ◽  
Carotid Arteries ◽  
Vascular Inflammation ◽  
Protective Effects ◽  
En Face ◽  
Inflammatory Activation ◽  
Anti Inflammatory ◽  
Stress Dependent

SummaryBlood flow generates wall shear stress (WSS) which alters endothelial cell (EC) function. Low WSS promotes vascular inflammation and atherosclerosis whereas high uniform WSS is protective. Ivabradine decreases heart rate leading to altered haemodynamics. Besides its cardio-protective effects, ivabradine protects arteries from inflammation and atherosclerosis via unknown mechanisms. We hypothesised that ivabradine protects arteries by increasing WSS to reduce vascular inflammation. Hypercholesterolaemic mice were treated with ivabradine for seven weeks in drinking water or remained untreated as a control. En face immunostaining demonstrated that treatment with ivabradine reduced the expression of pro-inflammatory VCAM-1 (p<0.01) and enhanced the expression of anti-inflammatory eNOS (p<0.01) at the inner curvature of the aorta. We concluded that ivabradine alters EC physiology indirectly via modulation of flow because treatment with ivabradine had no effect in ligated carotid arteries in vivo, and did not influence the basal or TNFα-induced expression of inflammatory (VCAM-1, MCP-1) or protective (eNOS, HMOX1, KLF2, KLF4) genes in cultured EC. We therefore considered whether ivabradine can alter WSS which is a regulator of EC inflammatory activation. Computational fluid dynamics demonstrated that ivabradine treatment reduced heart rate by 20 % and enhanced WSS in the aorta. In conclusion, ivabradine treatment altered haemodynamics in the murine aorta by increasing the magnitude of shear stress. This was accompanied by induction of eNOS and suppression of VCAM-1, whereas ivabradine did not alter EC that could not respond to flow. Thus ivabradine protects arteries by altering local mechanical conditions to trigger an anti-inflammatory response.

Shear stress induces hepatocyte PAI-1 gene expression through cooperative Sp1/Ets-1 activation of transcription

2006 ◽  
Vol 291 (1) ◽  
pp. G26-G34 ◽  
Author(s):  
Hideki Nakatsuka ◽  
Takaaki Sokabe ◽  
Kimiko Yamamoto ◽  
Yoshinobu Sato ◽  
Katsuyoshi Hatakeyama ◽  
...  
Keyword(s):  
Gene Expression ◽  
Shear Stress ◽  
Consensus Sequence ◽  
Early Gene ◽  
Immediate Early ◽  
Mrna Levels ◽  
Consensus Sequences ◽  
Static Conditions ◽  
Stress Dependent ◽  
Pai 1

Partial hepatectomy causes hemodynamic changes that increase portal blood flow in the remaining lobe, where the expression of immediate-early genes, including plasminogen activator inhibitor-1 (PAI-1), is induced. We hypothesized that a hyperdynamic circulatory state occurring in the remaining lobe induces immediate-early gene expression. In this study, we investigated whether the mechanical force generated by flowing blood, shear stress, induces PAI-1 expression in hepatocytes. When cultured rat hepatocytes were exposed to flow, PAI-1 mRNA levels began to increase within 3 h, peaked at levels significantly higher than the static control levels, and then gradually decreased. The flow-induced PAI-1 expression was shear stress dependent rather than shear rate dependent and accompanied by increased hepatocyte production of PAI-1 protein. Shear stress increased PAI-1 transcription but did not affect PAI-1 mRNA stability. Functional analysis of the 2.1-kb PAI-1 5′-promoter indicated that a 278-bp segment containing transcription factor Sp1 and Ets-1 consensus sequences was critical to the shear stress-dependent increase of PAI-1 transcription. Mutations of both the Sp1 and Ets-1 consensus sequences, but not of either one alone, markedly prevented basal PAI-1 transcription and abolished the response of the PAI-1 promoter to shear stress. EMSA and chromatin immunoprecipitation assays showed binding of Sp1 and Ets-1 to each consensus sequence under static conditions, which increased in response to shear stress. In conclusion, hepatocyte PAI-1 expression is flow sensitive and transcriptionally regulated by shear stress via cooperative interactions between Sp1 and Ets-1.

Prediction of Plantar Shear Stress Distribution by Artificial Intelligence Methods

2009 ◽  
Vol 131 (9) ◽  
Author(s):  
Metin Yavuz ◽  
Hasan Ocak ◽  
Vincent J. Hetherington ◽  
Brian L. Davis
Keyword(s):  
Neural Network ◽  
Shear Stress ◽  
Stress Distribution ◽  
Peak Pressure ◽  
Shear Stress Distribution ◽  
Future Research ◽  
Shear Forces ◽  
Inference System ◽  
Vertical Loading ◽  
Stress Dependent

Shear forces under the human foot are thought to be responsible for various foot pathologies such as diabetic plantar ulcers and athletic blisters. Frictional shear forces might also play a role in the metatarsalgia observed among hallux valgus (HaV) and rheumatoid arthritis (RA) patients. Due to the absence of commercial devices capable of measuring shear stress distribution, a number of linear models were developed. All of these have met with limited success. This study used nonlinear methods, specifically neural network and fuzzy logic schemes, to predict the distribution of plantar shear forces based on vertical loading parameters. In total, 73 subjects were recruited; 17 had diabetic neuropathy, 14 had HaV, 9 had RA, 11 had frequent foot blisters, and 22 were healthy. A feed-forward neural network (NN) and adaptive neurofuzzy inference system (NFIS) were built. These systems were then applied to a custom-built platform, which collected plantar pressure and shear stress data as subjects walked over the device. The inputs to both models were peak pressure, peak pressure-time integral, and time to peak pressure, and the output was peak resultant shear. Root-mean-square error (RMSE) values were calculated to test the models’ accuracy. RMSE/actual shear ratio varied between 0.27 and 0.40 for NN predictions. Similarly, NFIS estimations resulted in a 0.28–0.37 ratio for local peak values in all subject groups. On the other hand, error percentages for global peak shear values were found to be in the range 11.4–44.1. These results indicate that there is no direct relationship between pressure and shear magnitudes. Future research should aim to decrease error levels by introducing shear stress dependent variables into the models.

Sign in / Sign up

Export Citation Format

Share Document