Biology subjects

Dini, D.

Publications and source records attributed to Dini, D..

3 recordsLinked to original sources

bioRxiv2023

Porosity-permeability tensor relationship of closely and randomly packed fibrous biomaterials and biological tissues: Application to the brain white matter

The constitutive model for the porosity-permeability relationship is a powerful tool to estimate and design the transport properties of porous materials, and has thus attracted a significant number of attention for the advancement of composite materials. However, in comparison with engineering composite materials, biomaterials, especially natural and artificial tissues, have more complex micro-structures such as high anisotropy, high randomness of cell/fibre dimensions and very low porosity. Consequently, these properties of the biomaterial make the porosity-permeability relationship more difficult to obtain than traditional composites. To fill this gap, we start the mathematical derivation from the fundamental brain white matter (WM) formed by nerve fibres. This is augmented by a numerical characterisation and experimental validations to obtain an anisotropic permeability tensor of the brain WM as a function of the tissue porosity. Moreover, we propose an anisotropic poroelastic model enhanced by the newly defined porosity-permeability tensor relationship which precisely captures the tissues macro-scale permeability changes due to the micro-structural deformation in an infusion scenario. The constitutive model, the theories and protocols established in this study will both provide improved design strategies to tailor the transport properties of fibrous biomaterials and enable the non-invasive characterisation of the transport properties of biological tissues. This will lead to the provision of better patient-specific medical treatments, such as drug delivery.

bioengineering↗

bioRxiv2023

Linking fluid-axons interactions to the macroscopic fluid transport properties of the brain

Many brain disorders, including Alzheimers Disease and Parkinsons Disease, and drug delivery procedures are linked to fluid transport in the brain; yet, while neurons are extremely soft and can be easily deformed, how the microscale channel flow interacts with the neuronal structures (especially axons) deformation and how this interactions affect the macroscale tissue function and transport properties is poorly understood. Misrepresenting these relationships may lead to the erroneous prediction of e.g. disease spread, drug delivery, and nerve injury in the brain. However, understanding fluid-neuron interactions is an outstanding challenge because the behaviours of both phases are not only dynamic but also occur at an extremely small length scale (the width of flow channel is [~]100 nm), which cannot be captured by the state-of-the-art experimental techniques. Here, by explicitly simulating dynamics of the flow and axons at the microstructural level, we, for the first time, establish the link between micromechanical tissue response to the physical laws governing the macroscopic transport property of the brain white matter. We found that interactions between axons and the interstitial flow is very strong, thus playing an essential role in the brain fluid/mass transport. Furthermore, we proposed the first anisotropic pressure-dependent permeability tensor informed by microstructural dynamics for more accurate brain modelling at the macroscale, and analysed the effect of the variation of the microstructural parameters that influence such tensor. These findings will sheds light on some unsolved issues linked to brain functions and medical treatments relying on intracerebral transport, and the mathematical model provides a framework to more realistically model the brain and design the brain-tissue-like biomaterials. Statement of significanceThis study reveals how neurons interact with the fluid flowing around them and how these microscale interactions affect macroscale transport behaviour of the brain tissue. The findings provide unprecedented insights into some unsolved issues linked to brain functions and medical treatments relying on intracerebral fluid transport. Furthermore, we, for the first time, established a microstructure-informed permeability tensor as a function of local hydraulic pressure and pressure gradient for the brain tissue, which inherently captures the dynamic transport property of the brain. This study is a cornerstone to advance the predicting accuracy of brain tissue transport property and neural tissue engineering.

bioengineering↗

bioRxiv2022

Nanoscale Friction of Model Hair Surfaces

We investigate the nanoscale friction between biomimetic hair surfaces using chemical colloidal probe atomic force microscopy experiments and nonequilibrium molecular dynamics simulations. In the experiments, friction is measured between water-lubricated silica surfaces functionalised with monolayers of either octadecyl or sulfonate groups, which are representative of the surfaces of virgin and ultimately bleached hair, respectively. In the simulations, friction is monitored between coarse-grained model hair surfaces with different levels of chemical damage, where different fractions of grafted lipid molecules are randomly replaced with sulfonate groups. The sliding velocity dependence of friction can be described using an extended stress-augmented thermally activation model. As the damage level increases, the friction generally increases, but its sliding velocity-dependence decreases. At low sliding speeds, which are closer to those encountered physiologically and experimentally, we observe a monotonic increase of friction with the damage ratio, which is consistent with our new experiments using biomimetic surfaces and previous ones using real hair. This observation demonstrates that modified surface chemistry, rather than roughness changes or subsurface damage, control the increase in nanoscale friction of damaged hair. We expect the experimental and computational model surfaces proposed here to be useful to screen the tribological performance of hair care formulations.

biochemistry↗