Reconstruction of major fibers using 7T multi-shell Hybrid Diffusion Imaging in mice

Diffusion weighted imaging (DWI) can reveal the orientation of the underlying fiber populations in the brain. High angular resolution diffusion imaging (HARDI) is increasingly used to better resolve the orientation and mixing of fibers. Here, we assessed the added value of multi-shell q-space sampling on the reconstruction of major fibers using mathematical frameworks from q-ball imaging (QBI) and generalized q-sampling imaging (GQI), as compared to diffusion tensor imaging (DTI). We scanned a healthy mouse brain using 7-Tesla 5-shell HARDI (b=1000, 3000, 4000, 8000, 12000 s/mm2), also known as hybrid diffusion imaging (HYDI). We found that QBI may provide greater reconstruction accuracy for major fibers, which improves with the addition of higher b-value shells, unlike GQI or DTI (as expected). Although QBI is a special case of GQI, the major fiber orientation in QBI was more closely related to the orientation in DTI, rather than GQI. HYDI can aid the clinical outcomes of research and especially – more advanced human and animal connectomics projects to map the brain’s neural pathways and networks

The Complex Ginzburg-Landau Equation in the Presence of Walls and Corners

We investigate the influence of walls and corners (with Dirichlet and Neumann boundary conditions) in the evolution of twodimensional autooscillating fields described by the complex Ginzburg-Landau equation. Analytical solutions are found, and arguments provided, to show that Dirichlet walls introduce strong selection mechanisms for the wave pattern. Corners between walls provide additional synchronization mechanisms and associated selection criteria. The numerical results fit well with the theoretical predictions in the parameter range studied.Comment: 10 pages, 9 figures; for related work visit http://www.nbi.dk/~martine

Imaging subtle leaks in the blood–brain barrier in the aging human brain: potential pitfalls, challenges, and possible solutions

Recent studies using dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) with gadolinium-based contrast agents (GBCA) have demonstrated subtle blood–brain barrier (BBB) leaks in the human brain during normal aging, in individuals with age-related cognitive dysfunction, genetic risk for Alzheimer’s disease (AD), mild cognitive impairment, early AD, cerebral small vessel disease (SVD), and other neurodegenerative disorders. In these neurological conditions, the BBB leaks, quantified by the unidirectional BBB GBCA tracer’s constant K(trans) maps, are typically orders of magnitude lower than in brain tumors, after stroke and/or during relapsing episodes of multiple sclerosis. This puts extra challenges for the DCE-MRI technique by pushing calculations towards its lower limits of detectability. In addition, presently, there are no standardized multivendor protocols or evidence of repeatability and reproducibility. Nevertheless, subtle BBB leaks may critically contribute to the pathophysiology of cognitive impairment and dementia associated with AD or SVD, and therefore, efforts to improve sensitivity of detection, reliability, and reproducibility are warranted. A larger number of participants scanned by different MR scanners at different clinical sites are sometimes required to detect differences in BBB integrity between control and at-risk groups, which impose additional challenges. Here, we focus on these new challenges and propose some approaches to normalize and harmonize DCE data between different scanners. In brief, we recommend specific regions to be used for the tracer’s vascular input function and DCE data processing and how to find and correct negative K(trans) values that are physiologically impossible. We hope this information will prove helpful to new investigators wishing to study subtle BBB damage in neurovascular and neurodegenerative conditions and in the aging human brain. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s11357-022-00571-x

Effect of TiO2 addition on structure, solubility and crystallisation of phosphate invert glasses for biomedical applications

NOTICE: this is the author’s version of a work that was accepted for publication in JOURNAL OF NON-CRYSTALLINE SOLIDS. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in JOURNAL OF NON-CRYSTALLINE SOLIDS, [VOL 356, ISSUE 44-49, (2001)] DOI: 10.1016/j.jnoncrysol.2010.03.02

ROCKETSHIP: a flexible and modular software tool for the planning, processing and analysis of dynamic MRI studies

Background: Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is a promising technique to characterize pathology and evaluate treatment response. However, analysis of DCE-MRI data is complex and benefits from concurrent analysis of multiple kinetic models and parameters. Few software tools are currently available that specifically focuses on DCE-MRI analysis with multiple kinetic models. Here, we developed ROCKETSHIP, an open-source, flexible and modular software for DCE-MRI analysis. ROCKETSHIP incorporates analyses with multiple kinetic models, including data-driven nested model analysis. Results: ROCKETSHIP was implemented using the MATLAB programming language. Robustness of the software to provide reliable fits using multiple kinetic models is demonstrated using simulated data. Simulations also demonstrate the utility of the data-driven nested model analysis. Applicability of ROCKETSHIP for both preclinical and clinical studies is shown using DCE-MRI studies of the human brain and a murine tumor model. Conclusion: A DCE-MRI software suite was implemented and tested using simulations. Its applicability to both preclinical and clinical datasets is shown. ROCKETSHIP was designed to be easily accessible for the beginner, but flexible enough for changes or additions to be made by the advanced user as well. The availability of a flexible analysis tool will aid future studies using DCE-MRI

Prenatal disruption of blood–brain barrier formation via cyclooxygenase activation leads to lifelong brain inflammation

Gestational maternal immune activation (MIA) in mice induces persistent brain microglial activation and a range of neuropathologies in the adult offspring. Although long-term phenotypes are well documented, how MIA in utero leads to persistent brain inflammation is not well understood. Here, we found that offspring of mothers treated with polyriboinosinic–polyribocytidylic acid [poly(I:C)] to induce MIA at gestational day 13 exhibit blood–brain barrier (BBB) dysfunction throughout life. Live MRI in utero revealed fetal BBB hyperpermeability 2 d after MIA. Decreased pericyte–endothelium coupling in cerebral blood vessels and increased microglial activation were found in fetal and 1- and 6-mo-old offspring brains. The long-lasting disruptions result from abnormal prenatal BBB formation, driven by increased proliferation of cyclooxygenase-2 (COX2; Ptgs2)-expressing microglia in fetal brain parenchyma and perivascular spaces. Targeted deletion of the Ptgs2 gene in fetal myeloid cells or treatment with the inhibitor celecoxib 24 h after immune activation prevented microglial proliferation and disruption of BBB formation and function, showing that prenatal COX2 activation is a causal pathway of MIA effects. Thus, gestational MIA disrupts fetal BBB formation, inducing persistent BBB dysfunction, which promotes microglial overactivation and behavioral alterations across the offspring life span. Taken together, the data suggest that gestational MIA disruption of BBB formation could be an etiological contributor to neuropsychiatric disorders

7T multi-shell hybrid diffusion imaging (HYDI) for mapping brain connectivity in mice

Diffusion weighted imaging (DWI) is widely used to study microstructural characteristics of the brain. High angular resolution diffusion imaging (HARDI) samples diffusivity at a large number of spherical angles, to better resolve neural fibers that mix or cross. Here, we implemented a framework for advanced mathematical analysis of mouse 5-shell HARDI (b=1000, 3000, 4000, 8000, 12000 s/mm^2), also known as hybrid diffusion imaging (HYDI). Using q-ball imaging (QBI) at ultra-high field strength (7 Tesla), we computed diffusion and fiber orientation distribution functions (dODF, fODF) to better detect crossing fibers. We also computed a quantitative anisotropy (QA) index, and deterministic tractography, from the peak orientation of the fODFs. We found that the signal to noise ratio (SNR) of the QA was significantly higher in single and multi-shell reconstructed data at the lower b-values (b=1000, 3000, 4000 s/mm^2) than at higher b-values (b=8000, 12000 s/mm2); the b=1000 s/mm^2 shell increased the SNR of the QA in all multi-shell reconstructions, but when used alone or in <5-shell reconstruction, it led to higher angular error for the major fibers, compared to 5-shell HYDI. Multi-shell data reconstructed major fibers with less error than single-shell data, and was most successful at reducing the angular error when the lowest shell was excluded (b=1000 s/mm2). Overall, high-resolution connectivity mapping with 7T HYDI offers great potential for understanding unresolved changes in mouse models of brain disease

Wound-up phase turbulence in the Complex Ginzburg-Landau equation

We consider phase turbulent regimes with nonzero winding number in the one-dimensional Complex Ginzburg-Landau equation. We find that phase turbulent states with winding number larger than a critical one are only transients and decay to states within a range of allowed winding numbers. The analogy with the Eckhaus instability for non-turbulent waves is stressed. The transition from phase to defect turbulence is interpreted as an ergodicity breaking transition which occurs when the range of allowed winding numbers vanishes. We explain the states reached at long times in terms of three basic states, namely quasiperiodic states, frozen turbulence states, and riding turbulence states. Justification and some insight into them is obtained from an analysis of a phase equation for nonzero winding number: rigidly moving solutions of this equation, which correspond to quasiperiodic and frozen turbulence states, are understood in terms of periodic and chaotic solutions of an associated system of ordinary differential equations. A short report of some of our results has been published in [Montagne et al., Phys. Rev. Lett. 77, 267 (1996)].Comment: 22 pages, 15 figures included. Uses subfigure.sty (included) and epsf.tex (not included). Related research in http://www.imedea.uib.es/Nonlinea

Endothelial LRP1 protects against neurodegeneration by blocking cyclophilin A

The low-density lipoprotein receptor-related protein 1 (LRP1) is an endocytic and cell signaling transmembrane protein. Endothelial LRP1 clears proteinaceous toxins at the blood-brain barrier (BBB), regulates angiogenesis, and is increasingly reduced in Alzheimer\u27s disease associated with BBB breakdown and neurodegeneration. Whether loss of endothelial LRP1 plays a direct causative role in BBB breakdown and neurodegenerative changes remains elusive. Here, we show that LRP1 inactivation from the mouse endothelium results in progressive BBB breakdown, followed by neuron loss and cognitive deficits, which is reversible by endothelial-specific LRP1 gene therapy. LRP1 endothelial knockout led to a self-autonomous activation of the cyclophilin A-matrix metalloproteinase-9 pathway in the endothelium, causing loss of tight junctions underlying structural BBB impairment. Cyclophilin A inhibition in mice with endothelial-specific LRP1 knockout restored BBB integrity and reversed and prevented neuronal loss and behavioral deficits. Thus, endothelial LRP1 protects against neurodegeneration by inhibiting cyclophilin A, which has implications for the pathophysiology and treatment of neurodegeneration linked to vascular dysfunction