Oscillatory Shear
Oscillatory Shear - Related Videos
06:07
Studying Large Amplitude Oscillatory Shear Response of Soft Materials
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Cited by 14 •
2019
We present a detailed protocol outlining how to perform nonlinear oscillatory shear rheology on soft materials, and how to run the SPP-LAOS analysis to understand the responses as a sequence of physical processes.
11:26
Assessing Cerebral Autoregulation via Oscillatory Lower Body Negative Pressure and Projection Pursuit Regression
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Cited by 7 •
2014
Cerebral perfusion is maintained across a range of pressures via cerebral autoregulation. However, characterizing autoregulation requires prominent pressure fluctuations at regulated frequencies. The described protocol will show how oscillatory lower body negative pressure can generate pressure fluctuations to provide data for projection pursuit regression for quantification of the autoregulatory curve.
04:53
A Novel Capsulorhexis Technique Using Shearing Forces with Cystotome
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Cited by 5 •
2010
This video demonstrates a novel capsulorhexis technique in modern cataract surgery. Capsulorhexis is the most difficult and important part of phacoemulsification surgery.
09:20
The Assembly and Application of 'Shear Rings': A Novel Endothelial Model for Orbital, Unidirectional and Periodic Fluid Flow and Shear Stress
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Cited by 10 •
2016
Different levels and patterns of fluid shear are known to modulate endothelial gene expression, phenotype and susceptibility to disease. We discuss the assembly and use of 'shear rings': a model that produces unidirectional, periodic shear stress patterns. Shear rings are simple to assemble, economical and can produce high cell yields.
07:51
Implantation of a Carotid Cuff for Triggering Shear-stress Induced Atherosclerosis in Mice
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Cited by 30 •
2012
The constricting cuff presented in this article is designed to induce atherosclerosis in the murine common carotid artery. Due to the conical shape of its inner lumen the implanted cuff generates well-defined regions of low, high and oscillatory shear stress triggering the development of atherosclerotic lesions of different inflammatory phenotypes.
FAQs
Energy storage indicates how much of the applied mechanical input is retained elastically, while energy dissipation reflects how much is lost during deformation. Measuring both responses helps researchers distinguish frequency-dependent viscoelastic behavior in brain tissue, neural cells, and biomaterials. These results provide mechanical parameters for comparing neural systems and improving models of brain biomechanics.
Changing the frequency of sinusoidal shear probes how a neural material responds over different timescales. The resulting measurements show whether its viscoelastic behavior changes with loading rate, including shifts in energy storage and dissipation. This frequency-dependent information is important because a single mechanical measurement cannot fully represent the behavior of brain tissue, cells, or biomaterials under time-varying forces.
Alternating tangential loading exposes mechanical responses that may not appear under a single, unchanging deformation. In neuroscience, this approach allows researchers to examine how brain tissue, neural cells, and biomaterials accommodate repeated changes in applied force. The measurements can clarify how neural systems respond mechanically to deformation or fluid-flow-related loading and support more realistic biomechanical models.
The approach can be applied to brain tissue, neural cells, and biomaterials designed for neural research. Testing these different material classes allows investigators to characterize their frequency-dependent viscoelastic behavior using comparable controlled loading. Such comparisons are relevant when linking the mechanics of native neural systems with the performance of engineered materials intended for neural interfaces or tissue models.
A typical workflow applies controlled sinusoidal shear to the selected brain tissue, neural cells, or biomaterial, then records the mechanical response across relevant loading conditions. Researchers analyze energy storage and dissipation to characterize frequency-dependent viscoelastic behavior. The resulting measurements can be used to compare samples, evaluate responses to deformation or fluid flow, and inform brain-biomechanics models.
Measurements from oscillatory shear can describe how neural materials respond to time-varying mechanical loading, providing mechanical context for traumatic brain injury studies. The same strategy supports investigation of neurovascular mechanics by evaluating responses associated with deformation or fluid flow. These data help researchers connect controlled mechanical behavior with broader questions about how neural systems withstand or accommodate applied forces.
Neural interfaces and engineered tissues must be evaluated not only for their structure but also for their mechanical behavior under changing forces. Oscillatory shear provides frequency-dependent measurements of energy storage and dissipation in biomaterials and tissue models. Those outcomes can guide comparisons between engineered and neural materials and support the development of designs that better represent brain biomechanics.