Choroid plexus in developmental and evolutionary perspective

Bill, Brent R.; Korzh, Vladimir

doi:10.3389/fnins.2014.00363

Cited by 42 publications

(45 citation statements)

References 121 publications

(162 reference statements)

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“…Using claudin-2, a marker of adult epithelium in the CP (Kratzer et al 2012), we did not observe co-localization with GAS1 in neither the LV nor in the 3V confirming at least by exclusion that GAS1 is expressed in the stroma of the CP. The stroma of the CP is mainly composed by endothelial cells and to a lesser extent by a wide variety of cells including: pericytes, fibroblasts, telocytes, stem cells, dendritic cells, macrophages, leukocytes, Kolmer cells, and in some cases T-cells (Strazielle and Ghersi-Egea 2000;Emerich et al 2005b;Bill and Korzh 2014). We then examined the expression of GAS1 in endothelial cells, because they are the most common cells in the stroma but also because there is an in vitro report indicating that endothelial cells express GAS1 (Spagnuolo et al 2004).…”

Section: Discussionmentioning

confidence: 99%

GAS1 is present in the cerebrospinal fluid and is expressed in the choroid plexus of the adult rat

Ayala-Sarmiento

Estudillo

Pérez‐Sánchez

et al. 2016

Histochem Cell Biol

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Growth arrest specific 1 (GAS1) is a GPI-anchored protein that inhibits proliferation when overexpressed in tumors but during development it promotes proliferation and survival of different organs and tissues. This dual ability is caused by its capacity to interact both by inhibiting the signaling induced by the glial cell line-derived neurotrophic factor and by facilitating the activity of the sonic hedgehog pathway. GAS1 is expressed as membrane bound in different organs and as a secreted form by glomerular mesangial cells. In the developing central nervous system, GAS1 is found in neural progenitors; however, it continues to be expressed in the adult brain. Here, we demonstrate that soluble GAS1 is present in the cerebrospinal fluid (CSF) and it is expressed in the choroid plexus (CP) of the adult rat, the main producer of CSF. Additionally, we confirm the presence of GAS1 in blood plasma and liver of the adult rat, the principal source of blood plasma proteins. The pattern of expression of GAS1 is perivascular in both the CP and the liver. In vitro studies show that the fibroblast cell line NIH/3T3 expresses one form of GAS1 and releases two soluble forms into the supernatant. Briefly, in the present work, we show the presence of GAS1 in adult rat body fluids focusing in the CSF and the CP, and suggest that secreted GAS1 exists as two different isoforms.

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Section: Discussionmentioning

confidence: 99%

GAS1 is present in the cerebrospinal fluid and is expressed in the choroid plexus of the adult rat

Ayala-Sarmiento

Estudillo

Pérez‐Sánchez

et al. 2016

Histochem Cell Biol

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“…To compare the network to previously published results, we used a configuration analogous to the setup presented in the work of Bill and Legenstein 40 , who used a model of memristive elements in an unsupervised Winner-take-all network to learn digit prototypes for digits zero to four. A downscaled network of this kind has been partially verified in hardware recently 33 .…”

Section: System-level Behavioral Simulationsmentioning

confidence: 99%

“…Conversely, the cycle-to-cycle variability (e.g., in groups G1 and G2) can be managed by using feedback control to set the desired state to a well-defined value 35 , which requires a large overhead control circuit, or it can be exploited as a means to implement stochastic learning in spiking neural networks 25,26,[36][37][38][39] . Indeed, it has been shown that employing binary synapses, variability and randomness in their switching threshold in spiking neural networks greatly improves the convergence of the network and provides a form of regularization which substantially improves the network generalization performance 26,40,41 . In the case of neural networks with low resolution synapses, it has been shown that a randomized gradient descent method significantly outperforms naive deterministic rounding methods 42 .…”

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confidence: 99%

A neuromorphic systems approach to in-memory computing with non-ideal memristive devices: from mitigation to exploitation

et al. 2019

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Memristive devices represent a promising technology for building neuromorphic electronic systems. In addition to their compactness and non-volatility features, they are characterized by computationally relevant physical properties, such as state-dependence, non-linear conductance changes, and intrinsic variability in both their switching threshold and conductance values, that make them ideal devices for emulating the bio-physics of real synapses. In this paper we present a spiking neural network architecture that supports the use of memristive devices as synaptic elements, and propose mixed-signal analog-digital interfacing circuits which mitigate the effect of variability in their conductance values and exploit their variability in the switching threshold, for implementing stochastic learning. The effect of device variability is mitigated by using pairs of memristive devices configured in a complementary push-pull mechanism and interfaced to a current-mode normalizer circuit. The stochastic learning mechanism is obtained by mapping the desired change in synaptic weight into a corresponding switching probability that is derived from the intrinsic stochastic behavior of memristive devices. We demonstrate the features of the CMOS circuits and apply the architecture proposed to a standard neural network hand-written digit classification benchmark based on the MNIST data-set. We evaluate the performance of the approach proposed on this benchmark using behavioral-level spiking neural network simulation, showing both the effect of the reduction in conductance variability produced by the current-mode normalizer circuit, and the increase in performance as a function of the number of memristive devices used in each synapse.Neuromorphic computing systems comprise synapse and neuron circuits arranged in a massively parallel manner to support the emulation of large-scale spiking neural networks 1-9 . In many of these systems, and in particular in neuromorphic processing devices designed to overcome the von-Neumann bottleneck problem 7,8,10-14 , the bulk of the silicon real-estate is taken up by synaptic circuits that integrate in the same area both memory and computational primitives. To save area and maximize density in such devices, one possible approach is to implement very basic synapse circuits arranged in dense cross-bar arrays [15][16][17][18][19] . However, such approach is likely to relegate the role of the synapse to a basic multiplier 14,20 . In biology, synapses are extremely sophisticated structures that exhibit complex and powerful computational properties, including temporal dynamics, state-dependence, and stochastic learning behavior. The challenge is to design neuromorphic circuits that emulate these computational properties, and are also compact and low power. Memristive devices have recently emerged as nano-scale devices which provide a promising technology for addressing these problems 31,46 . These devices offer a compact and efficient solution to model synaptic weights since they are non-volatile, have ...

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“…A second barrier is formed between blood and cerebrospinal fluid and is sustained by tight junctions between epithelial cells in the choroid plexus (Engelhardt & Sorokin, 2009). Choroid plexus are evolutionarily conserved, highly vascularized structures that protrude into the brain ventricles as well as the subarachnoid space (Bill & Korzh, 2014). Choroid plexus are made of epithelial cells specified from the neuroectoderm as early as E10.5 in the mouse embryo (Liddelow, 2015).…”

Section: Functions Of Perivascular Meningeal and Choroidal Macrophagesmentioning

confidence: 99%

Development and maintenance of the brain's immune toolkit: Microglia and non‐parenchymal brain macrophages

López‐Atalaya

Askew

Sierra

et al. 2017

Developmental Neurobiology

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Microglia and non‐parenchymal macrophages located in the perivascular space, the meninges and the choroid plexus are independent immune populations that play vital roles in brain development, homeostasis, and tissue healing. Resident macrophages account for a significant proportion of cells in the brain and their density remains stable throughout the lifespan thanks to constant turnover. Microglia develop from yolk sac progenitors, later evolving through intermediate progenitors in a fine‐tuned process in which intrinsic factors and external stimuli combine to progressively sculpt their cell type‐specific transcriptional profiles. Recent evidence demonstrates that non‐parenchymal macrophages are also generated during early embryonic development. In recent years, the development of powerful fate mapping approaches combined with novel genomic and transcriptomic methodologies have greatly expanded our understanding of how brain macrophages develop and acquire specialized functions, and how cell population dynamics are regulated. Here, we review the transcription factors, epigenetic remodeling, and signaling pathways orchestrating the embryonic development of microglia and non‐parenchymal macrophages. Next, we describe the dynamics of the macrophage populations of the brain and discuss the role of progenitor cells, to gain a better understanding of their functions in the healthy and diseased brain. © 2017 Wiley Periodicals, Inc. Develop Neurobiol 78: 561–579, 2018

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Choroid plexus in developmental and evolutionary perspective

Cited by 42 publications

References 121 publications

GAS1 is present in the cerebrospinal fluid and is expressed in the choroid plexus of the adult rat

GAS1 is present in the cerebrospinal fluid and is expressed in the choroid plexus of the adult rat

A neuromorphic systems approach to in-memory computing with non-ideal memristive devices: from mitigation to exploitation

Development and maintenance of the brain's immune toolkit: Microglia and non‐parenchymal brain macrophages

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