Fluid flow-based description of the geometrical features in fluidic channels using the Shannon’s information theory: an exploratory study

Inspired by Nature, where storing information is an intrinsic ability of natural systems, here we investigate the capability of interacting systems to transport/store the information generated/exchanged in the interaction process in the form of energy or matter, preserving it over time. In detail, here we test the possibility to consider a fluid as a carrier of information, speculating about how to use such information. The aim of this work is to propose that information theory can be used to enlighten physical observations, even in those cases where the equations describing the phenomenon under investigation are intractable, are affected by a budget of uncertainty that makes their solution not affordable or may not even be known. In this exploratory work, an information theory-based approach is applied to microfluidic data. In detail, the classical study of the fluid flow in a microchannel with obstacles of different geometry is faced by integrating fluid mechanics theory with Shannon’s theory of information, interpreted in terms of thermodynamics. Technically, computational fluid dynamics simulations at Reynolds’ numbers (Re) equal to 1 and 50 were carried out in fluidic channels presenting obstacles with rectangular and semicircular shape, and on the simulated flow fields, the Shannon’s information theory was applied evaluating the fluid dynamics information entropy content. It emerged that the Shannon Entropy (SE) evaluated at the outflow section of the flow channel depends upon the geometric features (i.e., position, shape, aspect ratio) of the obstacles. This suggests an interpretation of the fluid dynamics establishing in a flow channel presenting obstacles in terms of information theory, that can be used to identify a posteriori the geometric features of the obstacles the fluid interacts with. The proposed approach can be applied to flow data at the boundaries of fluid domains of interest to extract information on the process occurring inside a system, without making any appeal to the governing equations of the phenomenon under observation or intrusive measurements

Does the shape of inflow velocity profiles affect hemodynamics in computational coronary artery models?

In this study, the impact of velocity inflow profiles shape on computational hemodynamic models of coronary arteries was investigated. To this purpose, 3D realistic velocity profiles were generated analytically and prescribed as inflow boundary condition and the impact on near-wall and intravascular flow was assessed. The results suggest that the impact of the shape of inflow velocity profiles on simulated coronary hemodynamics is limited to the proximal segment, while the global hemodynamics is poorly affected

Micromixing and microchannel design: Vortex shape and entropy

This paper was presented at the 2nd Micro and Nano Flows Conference (MNF2009), which was held at Brunel University, West London, UK. The conference was organised by Brunel University and supported by the Institution of Mechanical Engineers, IPEM, the Italian Union of Thermofluid dynamics, the Process Intensification Network, HEXAG - the Heat Exchange Action Group and the Institute of Mathematics and its Applications.In very recent years microdevices, due to their potency in replacing large-scale conventional laboratory instrumentation, are becoming a fast and low cost technology for the treatment of several chemical and biological processes. In particular microfluidics has been massively investigated, aiming at improving the performance of chemical reactors. This is because of the fact that reaction is often an interface phenomenon where the greater the surface to volume ratio, the higher the reaction speed, and microscale mixing increases the interfacial area (in terms of mixing-induced-by-vortices generation). However, microfluidic systems suffer from the limitation that they are characterized mostly by very low Reynolds numbers, with the consequence that (i) they cannot take advantage from the turbulence mixing support, and (ii) viscosity hampers proper vortex detection. Therefore, the proper design of micro-channels (MCs) becomes essential. In this framework, several geometries have been proposed to induce mixing vortices in MCs. However a quantitative comparison between proposed geometries in terms of their passive mixing potency can be done only after proper definition of vortex formation (topology, size) and mixing performance. The objective of this study is to test the ability of different fluid dynamic metrics in vortex detection and mixing effectiveness in micromixers. This is done numerically solving different conditions for the flow in a classic passive mixer, a ring shaped MC. We speculate that MCs design could take advantage from fluidic metrics able to rank properly flow related mixing

Aminoacid substitutions in the glycine zipper affect the conformational stability of amyloid beta fibrils

The aggregation of amyloid-beta peptides is associated with the pathogenesis of Alzheimer’s disease. The hydrophobic core of the amyloid beta sequence contains a GxxxG repeated motif, called glycine zipper, which involves crucial residues for assuring stability and promoting the process of fibril formation. Mutations in this motif lead to a completely different oligomerization pathway and rate of fibril formation. In this work, we have tested G33L and G37L residue substitutions by molecular dynamics simulations. We found that both protein mutations may lead to remarkable changes in the fibril conformational stability. Results suggest the disruption of the glycine zipper as a possible strategy to reduce the aggregation propensity of amyloid beta peptides. On the basis of our data, further investigations may consider this key region as a binding site to design/discover novel effective inhibitors. Communicated by Ramaswamy H. Sarma

The role of structural polymorphism in driving the mechanical performance of the alzheimer's beta amyloid fibrils

Alzheimer's Disease (AD) is related with the abnormal aggregation of amyloid β-peptides Aβ1-40 and Aβ1-42, the latter having a polymorphic character which gives rise to U- or S-shaped fibrils. Elucidating the role played by the nanoscale-material architecture on the amyloid fibril stability is a crucial breakthrough to better understand the pathological nature of amyloid structures and to support the rational design of bio-inspired materials. The computational study here presented highlights the superior mechanical behavior of the S-architecture, characterized by a Young's modulus markedly higher than the U-shaped architecture. The S-architecture showed a higher mechanical resistance to the enforced deformation along the fibril axis, consequence of a better interchain hydrogen bonds' distribution. In conclusion, this study, focusing the attention on the pivotal multiscale relationship between molecular phenomena and material properties, suggests the S-shaped Aβ1-42 species as a target of election in computational screen/design/optimization of effective aggregation modulators

Combining 4D Flow MRI and Complex Networks Theory to Characterize the Hemodynamic Heterogeneity in Dilated and Non-dilated Human Ascending Aortas

Motivated by the evidence that the onset and progression of the aneurysm of the ascending aorta (AAo) is intertwined with an adverse hemodynamic environment, the present study characterized in vivo the hemodynamic spatiotemporal complexity and organization in human aortas, with and without dilated AAo, exploring the relations with clinically relevant hemodynamic and geometric parameters. The Complex Networks (CNs) theory was applied for the first time to 4D flow magnetic resonance imaging (MRI) velocity data of ten patients, five of them presenting with AAo dilation. The time-histories along the cardiac cycle of velocity-based quantities were used to build correlation-based CNs. The CNs approach succeeded in capturing large-scale coherent flow features, delimiting flow separation and recirculation regions. CNs metrics highlighted that an increasing AAo dilation (expressed in terms of the ratio between the maximum AAo and aortic root diameter) disrupts the correlation in forward flow reducing the correlation persistence length, while preserving the spatiotemporal homogeneity of secondary flows. The application of CNs to in vivo 4D MRI data holds promise for a mechanistic understanding of the spatiotemporal complexity and organization of aortic flows, opening possibilities for the integration of in vivo quantitative hemodynamic information into risk stratification and classification criteria

A Practical Approach for Wall Shear Stress Topological Skeleton Analysis Applied to Intracranial Aneurysm Hemodynamics

The physiopathological role of Wall Shear Stress (WSS) in intracranial aneurysm development/rupture and the action of contraction/expansion played by shear forces on vessel wall make topological skeleton analysis of the WSS vector field of great interest. Here we present a practical way to analyze WSS topological skeleton through the identification and classification of WSS fixed points and manifolds. The method is based on the calculation of the WSS vector field divergence and Poincarè index, and it is here successfully applied to a dataset computational hemodynamic models of intracranial aneurysms