Biology subjects

Vidal, L.

Publications and source records attributed to Vidal, L..

3 recordsLinked to original sources

bioRxiv2024

Induction of hemodynamic traveling waves by glial-related vasomotion in a rat model of neuroinflammation: implications for functional neuroimaging

BackgroundCerebral hemodynamics are crucial for brain homeostasis and serve as a key proxy for brain activity. Although this process involves coordinated interaction between vessels, neurons and glial cells, its dysregulation in neuroinflammation is not well understood. MethodsWe used in vivo mesoscopic functional ultrasound imaging to monitor cerebral blood volume changes during neuroinflammation in male rats injected with lipopolysaccharide (LPS) in the visual cortex, under resting-state or visual stimulation, combined to advanced ex vivo techniques for glial cell reactivity analysis. FindingsCortical neuroinflammation induced large oscillatory hemodynamic traveling waves in the frequency band of vasomotion ([~]0.1 Hz) in both anesthetized and awake rats. Vasomotor waves traveled through large distances between adjacent penetrating vessels, spanning the entire cortex thickness, and even extending to subcortical areas. Moreover, vasomotion amplitude correlated with microglial morphology changes and was significantly reduced by astrocytic toxins, suggesting that both microglia and astrocytes are involved in the enhancement of vasomotion during neuroinflammation. Notably, functional connectivity was increased under this oscillatory state and functional hyperemia was exacerbated. InterpretationThese findings reveal new spatiotemporal properties of cerebral vasomotion and suggest this is a major component of brain hemodynamics in pathological states. Moreover, reactive microglia and astrocytes are participating to increased vasomotion during neuroinflammation. For the field of functional neuroimaging, our results advocate for considering 0.1 Hz hemodynamic oscillations as an important complement to traditional measurements, particularly in neuroinflammatory conditions. Indeed, brain hemodynamics may provide insights not only into neuronal activity but also glial reactivity. FundingSupported by ANR ("LabCom-NI2D") and Auvergne-Rhone-Alpes Region ("BI2D").

neuroscience↗

bioRxiv2021

Controlling fibroblast fibrinolytic activity allows for the bio-engineering of stable connective tissue equivalents

In tissue engineering, cell origin is important to ensure outcome quality. However, the impact of the cell type chosen for seeding in a biocompatible matrix has been less investigated. Here, we investigated the capacity of primary and immortalized fibroblasts of distinct origins to degrade a gelatin/alginate/fibrin (GAF)-based biomaterial. We further established that fibrin was targeted by degradative fibroblasts through the secretion of fibrinolytic matrix-metalloproteinases (MMPs) and urokinase, two types of serine protease. Finally, we demonstrated that besides aprotinin, specific targeting of fibrinolytic MMPs and urokinase led to cell-laden GAF stability for at least several days. These results support the use of specific strategies to tune fibrin-based biomaterials degradation over time. It emphasizes the need to choose the right cell type and further bring targeted solutions to avoid the degradation of fibrin-containing hydrogels or bioinks.

bioengineering↗

bioRxiv2020

Multi-Modal Biomarkers of Cerebral Edema in Low Resolution MRI

A central challenge of medical imaging studies is to extract biomarkers that characterize disease pathology or outcomes. Modern automated approaches have found tremendous success in high-resolution, high-quality magnetic resonance images (MRI). These methods, however, may not translate to low resolution images acquired on MRI scanners with lower magnetic field strength. In low-resource settings where low-field scanners are more common and there is a shortage of radiologists to manually interpret MRI scans, it is critical to develop automated methods that can augment or replace manual interpretation, while accommodating reduced image quality. We present a fully automated framework for translating radiological diagnostic criteria into image-based biomarkers, inspired by a project in which children with cerebral malaria were imaged using low-field 0.35 Tesla MRI. We integrate multi-atlas label fusion, which leverages high-resolution images from another sample as prior spatial information, with parametric Gaussian hidden Markov models based on image intensities, to create a robust method for determining ventricular cerebrospinal fluid volume. We also propose normalized image intensity and texture measurements to determine the loss of gray-to-white matter tissue differentiation and sulcal effacement. These integrated biomarkers have excellent classification performance for determining severe brain swelling due to cerebral malaria.

neuroscience↗