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A Practical Guide to the Automated Analysis of Vascular Growth, Maturation and Injury in the Brain.

ABSTRACT: The distinct organization of the brain's vasculature ensures the adequate delivery of oxygen and nutrients during development and adulthood. Acute and chronic pathological changes of the vascular system have been implicated in many neurological disorders including stroke and dementia. Here, we describe a fast, automated method that allows the highly reproducible, quantitative assessment of distinct vascular parameters and their changes based on the open source software Fiji (ImageJ). In particular, we developed a practical guide to reliably measure aspects of growth, repair and maturation of the brain's vasculature during development and neurovascular disease in mice and humans. The script can be used to assess the effects of different external factors including pharmacological treatments or disease states. Moreover, the procedure is expandable to blood vessels of other organs and vascular in vitro models.

SUBMITTER: Rust R

PROVIDER: S-EPMC7099171 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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A Practical Guide to the Automated Analysis of Vascular Growth, Maturation and Injury in the Brain.

Rust Ruslan R Kirabali Tunahan T Grönnert Lisa L Dogancay Berre B Limasale Yanuar D P YDP Meinhardt Andrea A Werner Carsten C Laviña Bàrbara B Kulic Luka L Nitsch Roger M RM Tackenberg Christian C Schwab Martin E ME

Frontiers in neuroscience 20200320

The distinct organization of the brain's vasculature ensures the adequate delivery of oxygen and nutrients during development and adulthood. Acute and chronic pathological changes of the vascular system have been implicated in many neurological disorders including stroke and dementia. Here, we describe a fast, automated method that allows the highly reproducible, quantitative assessment of distinct vascular parameters and their changes based on the open source software Fiji (ImageJ). In particul ...[more]

PMID: 32265643

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Project description:ObjectivePredicting how the brain can be driven to specific states by means of internal or external control requires a fundamental understanding of the relationship between neural connectivity and activity. Network control theory is a powerful tool from the physical and engineering sciences that can provide insights regarding that relationship; it formalizes the study of how the dynamics of a complex system can arise from its underlying structure of interconnected units.ApproachGiven the recent use of network control theory in neuroscience, it is now timely to offer a practical guide to methodological considerations in the controllability of structural brain networks. Here we provide a systematic overview of the framework, examine the impact of modeling choices on frequently studied control metrics, and suggest potentially useful theoretical extensions. We ground our discussions, numerical demonstrations, and theoretical advances in a dataset of high-resolution diffusion imaging with 730 diffusion directions acquired over approximately 1 h of scanning from ten healthy young adults.Main resultsFollowing a didactic introduction of the theory, we probe how a selection of modeling choices affects four common statistics: average controllability, modal controllability, minimum control energy, and optimal control energy. Next, we extend the current state-of-the-art in two ways: first, by developing an alternative measure of structural connectivity that accounts for radial propagation of activity through abutting tissue, and second, by defining a complementary metric quantifying the complexity of the energy landscape of a system. We close with specific modeling recommendations and a discussion of methodological constraints.SignificanceOur hope is that this accessible account will inspire the neuroimaging community to more fully exploit the potential of network control theory in tackling pressing questions in cognitive, developmental, and clinical neuroscience.

Project description:Appropriate growth and development of the endometrium across the menstrual cycle is key for a woman's quality of life and reproductive well-being. Recurrent pregnancy loss (RPL) and heavy menstrual bleeding (HMB) affect a significant proportion of the female population worldwide. These endometrial pathologies have a significant impact on a woman's quality of life as well as placing a high economic burden on a country's health service. An underlying cause for both conditions is unknown in approximately 50% of cases. Previous research has demonstrated that aberrant endometrial vascular maturation is associated with both RPL and HMB, where it is increased in RPL but reduced in HMB. TGFβ1 is one of the key growth factors that regulate vascular maturation, by inducing phenotypic switching of vascular smooth muscle cells (VSMCs) from a synthetic phenotype to a more contractile one. Our previous data demonstrated an increase in TGFβ1 in the endometrium of RPL, while others have shown a decrease in women with HMB. However, TGFβ1 bioavailability is tightly controlled, and we therefore sought to perform an extensive immunohistochemical analysis of different components in the pathway in the endometrium of normal controls, women with HMB or RPL. In addition, two in vitro models were used to examine the role of TGFβ1 in endometrial vascular maturation and endothelial cell (EC):VSMC association. Taken all together, the immunohistochemical data suggest a decrease in bioavailability, receptor binding capacity, and signaling in the endometrium of women with HMB compared with controls. In contrast, there is an increase in the bioavailability of active TGFβ1 in the endometrium of women with RPL compared with controls. Endometrial explants cultured in TGFβ1 had an increase in the number of vessels associated with contractile VSMC markers, although the total number of vessels did not increase. In addition, TGFβ1 increased EC:VSMC association in an in vitro model. In conclusion, TGFβ1 is a key regulator of endometrial vascular maturation and could be considered as a therapeutic target for women suffering from HMB and/or RPL.

Dataset Information

A Practical Guide to the Automated Analysis of Vascular Growth, Maturation and Injury in the Brain.

Publications

A Practical Guide to the Automated Analysis of Vascular Growth, Maturation and Injury in the Brain.

Similar Datasets

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