Biology subjects

Dini, D.

Publications and source records attributed to Dini, D..

7 recordsLinked to original sources

bioRxiv2026

Image-Derived 3D Blood-Brain Mechanics: Cerebral Haemodynamics, Brain Motion and In Vivo Benchmarking

Cerebrovascular pulsatility drives measurable brain tissue deformation and has been associated with ageing and a range of neurological disorders. Yet how pulsatile haemodynamic forces are transmitted through deformable cerebral arteries into the surrounding brain remains poorly understood, particularly in anatomically realistic vascular geometries. Existing computational approaches have largely treated cerebral fluid and tissue mechanics separately or relied on idealised geometries, limiting our ability to determine how vascular anatomy simultaneously governs intraluminal haemodynamics and extravascular mechanical loading. Here, we develop an image-derived three-dimensional computational framework that jointly resolves pulsatile blood flow, arterial wall deformation and surrounding brain tissue motion in representative cerebral arteries. Four arterial segments, including the middle cerebral artery, middle cerebral artery bifurcation, basilar artery and internal carotid artery, are reconstructed from high-field (5 Tesla) magnetic resonance imaging data of a healthy subject. A finite-deformation fluid-structure interaction model is established by coupling non-Newtonian blood flow, hyperelastic arterial wall and hyper-viscoelastic brain tissue. The predicted tissue response is benchmarked against in vivo magnetic resonance elastography measurements of cardiac-induced volumetric strain over a cardiac cycle. Results reveal spatially localised arterial and tissue deformation whose magnitude and distribution are strongly governed by vascular geometry and wall thickness. Among the segments examined, the internal carotid artery exhibits the largest deformation response, while reduced wall thickness increases strain transmission into the surrounding tissue. Geometrically complex regions also exhibit greater spatial heterogeneity in near-wall haemodynamic metrics. These findings demonstrate that cerebral vascular anatomy simultaneously shapes intraluminal haemodynamics and extravascular mechanical loading. By integrating image-derived vascular anatomy, coupled blood-vessel-brain mechanics and in vivo benchmarking within a unified framework, this study provides a mechanically consistent reference for healthy cerebral pulsatility and establishes a foundation for quantifying how blood-vessel-brain interactions are altered under pathological conditions.

bioengineering↗

bioRxiv2026

The Molecular Origin of Water-Mediated Collagen Contraction

The mechanical toughness of bone and teeth relies on residual stresses generated during mineralisation, where the dehydration of collagen fibrils leads to contraction, putting the mineral phase under compression. While macroscopic stiffening of collagen upon drying is well-documented, the atomic-level structural rearrangements driving this phenomenon have remained elusive. By performing molecular dynamics simulations, we demonstrate that collagen contraction is not homogeneous but is driven by specific charged motifs. We identify a critical sequence-dependent rule for contraction: oppositely charged side chains must be separated by at least four residues to drive backbone contraction. While salt bridges can form between side chains at a distance less than four residues without perturbing the helix, those at greater distances cannot form without rupturing backbone hydrogen bonds. Consequently, dehydration forces these distant charges together, breaking local backbone structure and driving collagen contraction. These findings imply that collagen sequences are evolutionarily tuned to actively control tissue mechanics and redefines collagen as an active mechanical element rather than a passive scaffold. Furthermore, this framework provides a molecular basis for understanding mechanical failure associated with pathologies and ageing, while simultaneously opening avenues for designing bio-inspired materials with tunable pre-stress and fracture resistance.

biophysics↗

bioRxiv2025

In vivo MRI measurement of microstructural constraints for direct delivery of therapeutics within the brain

Brain tissue microstructure influences the efficient delivery of therapeutics within the brain. Diffusion Tensor Imaging (DTI) enables the depiction of tissue properties in vivo, and thus is potentially relevant for planning convection-enhanced delivery (CED) within the brain. We report on the quantitative assessment of the distribution of a Gadolinium solution infused by CED within the brain of a live ovine model. Infusate distributions were measured at multiple timepoints and compared to microstructural properties as depicted by DTI, thus demonstrating the impact of tissue features and catheter positioning on drug distribution in vivo. This study contributed to the clinical translation of the CED for flow-based therapy to ultimately provide new therapeutic approaches for several brain diseases, by providing essential tools and results used to develop a better prediction model and a delivery platform to reach the therapeutic target more precisely and non-invasively.

neuroscience↗

bioRxiv2025

Decoding Brain Interstitial Transport In Vivo: A Fully Validated Bottom-Up Mechanistic Prediction Framework

The transport of fluids and substances within the brain parenchyma (i.e. interstitial transport) is fundamental to maintaining brain health and delivering treatments for neurological disorders. However, accurately predicting these transport processes has remained a formidable challenge due to the intricate and dynamic nature of the brains microenvironment. Here, we report a novel, fully validated bottom-up mechanistic framework that bridges advanced mathematical modelling, ultra-high-resolution imaging, and biomechanical testing to achieve precise, in vivo predictions of interstitial transport. Using this approach, we accurately modelled the transport of MRI tracers in living sheep brains, offering unprecedented insights into the interplay between fluid dynamics and tissue properties. This platform is a transformative step forward, with the potential to revolutionise drug delivery strategies not only in the brain but also in cancer therapy and other soft biological systems. By addressing limitations in modelling complex transport in soft tissue, our work establishes a significant tool with profound implications for biomedical engineering and translational medicine.

biophysics↗

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↗