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PRONEU-1418; No. of Pages 17 Progress in Neurobiology xxx (2016) xxx–xxx

Contents lists available at ScienceDirect

Progress in Neurobiology journal homepage: www.elsevier.com/locate/pneurobio

The brain interstitial system: Anatomy, modeling, in vivo measurement, and applications Yiming Lei a,b, Hongbin Han a,*, Fan Yuan c, Aqeel Javeed d,e, Yong Zhao e a

Peking University Third Hospital, Peking University, Beijing Key Laboratory of Magnetic Resonance Imaging Devices and Technology, Beijing, China School of Electronic Engineering and Computer Science, Peking University, Beijing, China c Department of Biomedical Engineering, Duke University, Durham, United States d Department of Pharmacology and Toxicology, University of Veterinary and Animal Sciences, Lahore, Pakistan e State Key Laboratory of Biomembrane and Membrane Biotechnology, Institute of Zoology, Chinese Academy of Science, China b

A R T I C L E I N F O

A B S T R A C T

Article history: Received 15 September 2015 Received in revised form 18 November 2015 Accepted 2 December 2015 Available online xxx

Although neurons attract the most attention in neurobiology, our current knowledge of neural circuit can only partially explain the neurological and psychiatric conditions of the brain. Thus, it is also important to consider the influence of brain interstitial system (ISS), which refers to the space among neural cells and capillaries. The ISS is the major compartment of the brain microenvironment that provides the immediate accommodation space for neural cells, and it occupies 15% to 20% of the total brain volume. The brain ISS is a dynamic and complex space connecting the vascular system and neural networks and it plays crucial roles in substance transport and signal transmission among neurons. Investigation of the brain ISS can provide new perspectives for understanding brain architecture and function and for exploring new strategies to treat brain disorders. This review discussed the anatomy of the brain ISS under both physiological and pathological conditions, biophysical modeling of the brain ISS and in vivo measurement and imaging techniques, including recent findings on brain ISS divisions. Moreover, the implications of ISS knowledge for basic neuroscience and clinical applications are addressed. ß 2016 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

Keywords: Brain interstitial system Extracellular space Biophysical modeling Brain interstitial division In vivo measurement

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Introduction . . . . . . . . . . . . . . . . . . . . . . . . The anatomy of the brain ISS . . . . . . . . . . ISS Geometry and boundaries . . . . 2.1. Extracellular matrix . . . . . . . . . . . . 2.2. The Brain interstitial fluid . . . . . . . . . . . . . 3.1. The components of brain ISF . . . . . ISF flow and drainage route . . . . . . 3.2. 3.3. Divisions of the brain ISS based on

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Abbreviations: 2-D, two dimensional; 3-D, three dimensional; Ab, amyloid beta; AD, Alzheimer’s disease; ADC, apparent diffusion coefficient; APOE, apolipoprotein E; APP, amyloid precursor protein; AsF6, hexafluoroarsenate; AQP4, aquaporin4; BBB, blood–brain barrier; BME, brain microenvironment; CCD, charge coupled device; CDPC, cytidinediphosphate choline; CED, convection enhanced delivery; CNS, central nervous system; CSF, cerebrospinal fluid; CSPGs, chondroitinsulfate proteoglycans; DA, dopamine; DWI, diffusion weighted imaging; ECM, extracellular matrix; ECS, extracellular space; EVs, extracellular vesicles; GAGs, glycosaminoglycans; GBM, glioblastoma multiforme; Gd-DTPA, gadolinium-diethylenetriaminepentacetic acid; Glu, glucose; HA, hycluronic acid; HSPGs, heparan sulfate proteoglycans; IOI, integrative optical imaging; ISF, interstitial fluid; ISM, ion-selected microelectrode; ISS, interstitial system; LSM, laser scanning microscope; MMP, matrix metallopeptidase; MRI, magnetic resonance imaging; MS, multiple sclerosis; NIM, neuronal interstitial matrix; PCM, pericapillary matrix; PDD, principal diffusion direction; pH, hydrogen ion concentration; PNNs, perineuronal nets; RTI, real time iontophoresis; RTP, real-time pressure injection; SDD, simple diffusion delivery; SPIO, super paramagnetic iron oxide; STP, short-term potentiation; TEA, tetraethylammonium; TMA+, tetramethylammonium+; tPAs, tissue plasminogen activators. * Corresponding author at: Peking University Third Hospital, Peking University, Beijing Key Laboratory of Magnetic Resonance Imaging Devices and Technology, Beijing, China. Tel.: +86 10 82266972; fax: +86 10 82266972. E-mail address: [email protected] (H. Han). http://dx.doi.org/10.1016/j.pneurobio.2015.12.007 0301-0082/ß 2016 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

Please cite this article in press as: Lei, Y., et al., The brain interstitial system: Anatomy, modeling, in vivo measurement, and applications. Prog. Neurobiol. (2016), http://dx.doi.org/10.1016/j.pneurobio.2015.12.007

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PRONEU-1418; No. of Pages 17 Y. Lei et al. / Progress in Neurobiology xxx (2016) xxx–xxx

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Modeling of substance transport in the brain ISS . . . . . . . . . . The mechanisms of substance transport in the ISS . . . . 4.1. Biophysical parameters and modeling of the ISS . . . . . 4.2. In vivo measurement techniques of brain ISS . . . . . . . . . . . . . The principles of in vivo imaging and measurement of 5.1. Ion-selected microelectrode techniques . . . . . . . . . . . . 5.2. Optical Imaging Techniques . . . . . . . . . . . . . . . . . . . . . . 5.3. Tracer-based MRI and quantitative measurement . . . . 5.4. 5.5. Microdialysis technique . . . . . . . . . . . . . . . . . . . . . . . . . ISS and brain disorders . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Glioma . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.1. 6.2. Ischemic stroke . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Alzheimer’s disease. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.3. Drug delivery via brain ISS . . . . . . . . . . . . . . . . . . . . . . . . . . . . The demand for drug delivery via ISS . . . . . . . . . . . . . . 7.1. 7.2. Convection enhanced delivery . . . . . . . . . . . . . . . . . . . . Simple diffusion delivery . . . . . . . . . . . . . . . . . . . . . . . . 7.3. Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Acknowledgements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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1. Introduction In the past century, brain research has been focused on neurons, their connections, and techniques to record the signals from individual neurons or neural circuits at high spatial and temporal resolutions (Scalabrino, 2009; Morgan and Lichtman, 2013; Hopkins et al., 2014). Despite great advances in neurobiology, the overall understanding of most neurological and psychiatric conditions remains limited, and the clinical drug treatment of brain disorders faces a dilemma of low efficiency (Fisher et al., 2009; Rogawski, 2009; Lam et al., 2011). Brain tissues are composed of three compartments: neural cells (e.g., neurons and glial cells), vascular system, and the interstitial system (ISS) (Fumagalli et al., 2014) (see Fig. 1). Although neural cells have long been considered the most important functional element of the brain, they occupy only 70% to 80% of the total brain volume (Fenstermacher and Kaye, 1988; Sykova and Nicholson, 2008). The vascular system and ISS together form the brain microenvironment (BME), which constitutes the remaining volume of the brain and provides the living environment for neural cells. The ISS occupies 15% to 20% of the total brain volume and was traditionally

Fig. 1. Brain tissue compartments and their spatial relationship. Cyan cells represent neurons, and purple cells represent astrocytes. In the zoom-in subplot, the extracellular matrix (ECM) is shown as a net-like cover attached to the surface of neural cells, and its floating chains of glycoproteins are invisible in ISF. This is a schematic figure for identification purpose and is not be scale.

... ... ... ... ISS ... ... ... ... ... ... ... ... ... ... ... ... ... ... ...

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regarded as a gap filler that functioned in cell maintenance and adherence. However, recent studies have indicated that the brain ISS plays a number of active roles in brain function, such as communication among neural cells, information processing and integration, and the coordinated response to changes in the external and internal environments of the brain (Edwards and Meinertzhagen, 2010; Bechtel and Geschwind, 2013; Deco et al., 2013; Kastellakis et al., 2014; He et al., 2014). Therefore our knowledge of neural cells may only partially explain brain functions and disorders without in-depth consideration of the influence of the BME (Morgan and Lichtman, 2013). The brain ISS is an irregular, tortuous, and narrow space among neural cells and capillaries; the space between adjacent neural cells is also known as extracellular space (ECS) (Larsen, 2005). The width of the ECS between cell bodies ranges from 38 to 64 nm in rat brains (Thorne and Nicholson, 2006), and it can be as narrow as 20 nm at neuron synapses. The brain ISS occupies approximately 15% to 20% of the total brain volume, and it contains interstitial fluid (ISF) and extracellular matrix (ECM) (Nicholson et al., 2011). ECM is produced and secreted by cells, and it surrounds and attaches to the cell membrane (Michel et al., 2010; Nicholson et al., 2011; Barros et al., 2011; Coleman et al., 2014). Brain ISF is a water solvent that contains ions, gaseous molecules, and organic molecules, and it bathes and surrounds the neural cells (Deitmer and Rose, 2009; Fuxe et al., 2010). Due to extensive communication between the cerebrospinal fluid (CSF) and ISF, CSF is also considered a reservoir for ISF and the ultimate site of removal of most waste products from the brain ISF (Milhorat, 1975). The CSF occupies the subarachnoid space and the ventricular system around or inside the brain parenchyma, and it acts as a mechanical cushion or buffer for the brain. It has been reported that approximately 20% of CSF in the human brain originates from brain ISF (Edsbagge et al., 2004; Perez-Figares et al., 2001). The vascular system occupies 3% to 5% of the brain volume (Fenstermacher and Kaye, 1988), and substance exchange between the plasma and ISF occurs at the capillaries (Ide and Secher, 2000). The distance between a neuron and the nearest capillary ranges from 10–20 mm, and this distance guarantees a higher efficiency for diffusion-based substance exchange between capillaries and neurons (Mabuchi et al., 2005). The capillaries in brain tissue characterize the structure of the blood–brain barrier (BBB) (Pan and Kastin, 2007; De et al., 2013). The BBB is a highly selective permeability barrier formed by capillary endothelial cells, pericytes and endfeet of astrocytes, where the endothelial cells are connected by tight junctions with an extremely high electrical


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Fig. 2. Three compartments of the brain and their substance exchanges. The solid blue line represents the ‘one-way’ exchange of substances, and the dashed red line represents interactive exchanges.

resistivity (Petty and Lo, 2002; Pereira and Furlan, 2010). The BBB allows the passage of water, small hydrophobic molecules (O2, CO2, hormones), and lipid soluble molecules by passive or simple diffusion, as well as the selective transport of molecules such as glucose and amino acids by facilitated diffusion or active transport (Brasnjevic et al., 2009; Figley and Stroman, 2011). In Fig. 2, Three major compartments of brain tissue (i.e., neural cell, vascular system, and ISS) and their constituents are, and the substances exchanges between each compartment are illustrated. After the above brief introduction to brain architecture and BME organization, the properties of the brain ISS are presented as follows. In Section 2, the anatomy of the brain ISS is discussed. Section 3 illustrates the properties of ISF and a new finding, i.e., divisions of the brain ISS. In Section 4, substance transport and the biophysical modeling of the ISS are addressed. Section 5 presents in vivo measurement techniques for the ISS. In Section 6, alternations of the ISS associated with the neuropathology of several brain disorders are introduced. Section 7 discusses the practical use of ISS knowledge, especially promising application in the local delivery of central nervous system (CNS) therapeutics. Section 8 represents some concluding remarks.

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Tortuosity and volume fraction are two general parameters depicting the geometry of the brain ISS (Nicholson, 2001). The volume fraction (a) is defined as the ratio of ISS volume to total brain volume and ranges from 15% to 20% in normal adult brain tissue. ISS tortuosity is empirically defined as the ratio of path length for transport to the straight distance between two points in the ISS, and it can be estimated by calculating the square root of the ratio between the measured diffusion coefficient in a free medium and that measured in the ISS (the most commonly used ‘‘free’’ medium in studies of the brain ISS study is a dilute agarose gel). The estimated values of these biophysical parameters of the brain ISS are affected by the selection of measurement techniques, e.g., using the radiotracer method, the ISS tortuosity ranges between 1.4 and 1.7 (Sykova and Nicholson, 2008), using real time iontophoresis tetramethylammonium+ (RTI-TMA+) measurement the ISS tortuosity mostly varies from 1.5 to 1.8 (Rusakov and Kullmann, 1998; Nicholson, 2001; Sykova and Nicholson, 2008), and the tortuosity is greater than 2 by using integrative optical imaging (IOI) technique (Nicholson, 2001). Using a tracer-based magnetic resonance imaging (MRI), the ISS tortuosity in rat caudate nuclei ranges from 1.3 to 1.8 (Han et al., 2014). The boundary structure of the ISS is made of the cell membrane and the wall of blood vessels (Nicholson et al., 2011). The cell membrane (plasma membrane) has aphospholipid bilayer structure with a thickness of approximately 5 nm at the outermost layer. The cell membrane separates the cytoplasm from the outside environment, and it is selectively permeable to specific ions and organic molecules with the aid of embedded proteins (Alberts et al., 2007; Gu and Barry, 2011; Arish et al., 2015; Nicolson, 2015; Bouter et al., 2015). The cell membrane serves as the attachment surface for ECM and thus maintains ISS geometry (Malmstadt et al., 2006). 2.2. Extracellular matrix As noted in Section 1, the ISS is composed of ISF and ECM. Fig. 3 shows the components and structure of the ECM, which provides structural and biochemical support to the attached cells. The ECM is a highly hydrated net-like structure produced and secreted by

2. The anatomy of the brain ISS 2.1. ISS Geometry and boundaries The geometry of the brain ISS undergoes alterations throughout the lifespan during the development, maturation, and aging of the brain, and these changes are related to neuronal migration, neuron differentiation, synapse formation, myelination, regressive processes, and the organization and reorganization of the brain (Bielas et al., 2004; Faissner et al., 2010; Florio and Huttner, 2014). Even each neuronal excitation is accompanied with the alteration in the ISS, which is secondary to the instantaneous cell swelling during excitation (Le Bihan and Johansen-Berg, 2011). Brain cells include neurons and various types of glial cells. Generally, glial cells outnumber neurons, and the ratio varies in different brain regions (Pelvig et al., 2008; Azevedo et al., 2009a, 2009b). Neurons are connected to several thousands of other neurons by means of axons and synapses. The diameter of most neuron bodies ranges from 5–10 mm, and axons can be as long as 1 m. The body width of oligodendrocyte ranges from 1–3 mm, and their processes extend to wrap around axons and form the myelin sheath (EI Waly et al., 2014). Astrocytes are approximately 10 mm in diameter, and they can extend much larger during excitation (Wolak and Thorne, 2013).

Fig. 3. Brain ECM, and an enlarged view of the zoom-in subplot in Fig. 1. The net-like cover represents hyaluronic acid (HA) secreted by cells, which acts as a trestle for the ECM net-like structure. The penniform objects that cross the gaps between the HA chains are glycoproteins (mainly CSPGs in the brain). Tenascin is shown as an orange triple-circle that links glycoproteins up. The colorful single circles represent example components of ISF, e.g., water molecules (H2O), extracellular vesicles (EVs), matrix metallopeptidase (MMP), glucose (Glu), dopamine (DA), and tissue plasminogen activators (tPAs). This figure demonstrated that the ECM acts as an intercellular adhesion and scaffold. This is a schematic figure for identification purpose and is not be scale.


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cells and degraded by enzymes. The ECM consists of collagens, elastin, glycosaminoglycans (GAGs), proteoglycans, and glycoproteins (tenascin, reelin, laminin and fibronectin) (Crocker et al., 2004; Michel et al., 2010; Lau et al., 2013). Compared to other body tissues, the ECM in brain tissue contains less collagens but more proteoglycans (Zimmermann and Dours-Zimmermann, 2008; Rozario and DeSimone, 2009). ECM can be further classified into various types, and its components and structure may vary between locations. Perineuronal nets (PNNs) are pericellular structures of ECM at neural cell bodies, axosomatic synapses, and proximal dendrites (Frischknecht et al., 2009). PNNs are condensed mesh-like structures consisting of CSPGs, HA, linking proteins and tenascin-R. The pericapillary matrix (PCM), also known as the basement membrane and basal lamina, is a sheet-like layer that is continuous with the pia matter of the brain; it mainly contains collagen IV, laminins, fibronectin, dystroglycan and perlecan (Itoh et al., 2011). In addition, the brain ISS contains diffusely distributed interstitial matrix, which consists of proteoglycans, HA, and a small amount of collagens, laminins and fibronectin. The components of the ECM, their functions, and related brain disorders are described in Table 1. HA is strongly negatively charged; thus, it mostly attracts positive ions and positively charged proteins. HA maintains the hydration of ECM and connects the cell body and lecticans. Moreover, HA contributes to the movement and proliferation of cells through interactions with cell surface receptor (Bandtlow and Zimmermann, 2000; Dityatev and Schachner, 2003; Anlar and Gunel-Ozcan, 2012; Hopkins et al., 2014). Members of the lectican family, e.g., CSPGs and HSPGs, can bind with receptors and coat on the neuronal surface. Combined with HA and tenascins, lecticans store various proteins in the ISS, such as

chemokines, proteases and axon guidance molecules. Lecticans are believed to regulate neurogenesis and synaptic plasticity and to contribute to capillary basement membrane formation (Dityatev and Schachner, 2003; Kantor et al., 2004; Sugahara and Mikami, 2007; Purushothaman et al., 2012a, 2012b; Dick et al., 2013; Hopkins et al., 2014). Tenascins are associated with dendrites growth, synaptic plasticity, cell attachment and migration. Tenascin-R is a crosslinker for lectican, and tenascin-C is associated with cell attachment and migration. Reelin is another ECM glycoprotein. During development, reelin promotes the neuronal migration and the organization of cell layer. Reelin can modulate synaptic plasticity and contributes to the dendrites development, and short-term and long-term potentiation (Ogawa et al., 1995; Stranahan et al., 2013). Laminins are high-molecular-weight glycoproteins, that are distinguished by their assembly of three disulfide-linked polypeptide chains. Laminins are involved in constructing the basal lamina and serve as an integrator by binding to cell membranes and contributing to cell attachment, differentiation and migration. Although the expression of collagen family is lower in the brain than in body tissues, this family plays an important role in axon guidance and synaptogenesis (Fox, 2008; Hubert et al., 2009). Degradation of collagen XVII, XV and IV produces three cytokines in the ISS, i.e., endostatin, restin and arresten, respectively. These cytokines can affect the physiological functions of neural cells (Ramchandran et al., 1999; Colorado et al., 2000). The components of PNNs are dynamically regulated in responses to emotions such as fear, reward, and stress, as well as immune activities (Gogolla et al., 2009; Xue et al., 2014), and the integrity of the PNN is damaged during trauma, epilepsy, tumor and schizophrenia (Balmer et al., 2009; Bavelier et al., 2010;

Table 1 Major components of ECM of the brain ISS (abbreviations can be found at the end of this table). Family

Components

Distribution

GAGs

CS HS HA

PNNs, NIM PCM PNNs, NIM

CSPGs (also known as lecticans)

Brevican Neurocan Aggrecan Versican

PNNs, NIM

GBM MS, ischemic stroke, GBM GBM MS, ischemic stroke, GBM

HSPGs

Glypicans Syndecans

PNNs, PCM

AD, ischemic stroke AD, GBM

Glycoproteins

Tenascins C Tenascins R Reelin Laminins Fibronectin

PNNs PNNs, NIM PNNs PCM PCM, NIM

GBM, D-54MG and U-251 MG glioma AD GBM MS, D-54MG and U-251MG cell lines

The glycoproteins are abundantly expressed in the developing and matured brain. They affect nearly all aspects of nervous system development and function.

Collagens

Collagen IV Collagen XV Collagen XVII

PCM, NIM

AD, GBM

The family consists of a right-handed triple helical structure composed of three polypeptide chains with a recurring Gly-X-Y sequence (where X and Y are usually proline and hydroxyproline respectively)

Proteoglycans

Related brain diseases

G26 and U373 MG glioma cells

AD

Overview A family of negatively charged chains with repeating disaccharide units. The family includes five groups: chondroitin sulfate, heparan sulfate, dermatin sulfate, keratin sulfate and HA. Except for HA, GAGs are sulfated on the sugar residues and attached to the core proteins for forming the proteoglycans. As the most abundant components of brain ECM, CSPGs have a c-typelectin domain on the Cterminus and a HA linking site on the N-terminus. CSPGs include three groups: lecticans, phosphacan and neuron-glial antigen 2. Generally, lecticans are the symbols of CSPGs and include brevican, neurocan, aggrecan and versican. They bind HA and tenansins and form the highly organized structure of PNNs. Abundant groups in proteoglycans family. At least 16 groups have been found and most of them have transmembrane proteins and attaches the cell membranes. Two major groups are glypicans and syndecans.

AD: Alzheimer’s disease, CSPGs: chondroitin sulfate proteoglycans, GAGs, glycosaminoglycans, GBM: glioblastomamultiforme, HA: hyaluronic acid, HSPGs: heparan sulfate proteoglycans, NIM: neuronal interstitial matrix, PCM: percapillary matrix.


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Gundelfinger et al., 2010; Pantazopoulos et al., 2010; Soleman et al., 2013; Mauney et al., 2013; Ye and Miao, 2013; Vargova and Sykova, 2014). ECM in the brain ISS may hinder ISF flow or substance transport (Wolak and Thorne, 2013). Moreover, the negatively charged components of the ECM, such as HA, may disturb the movement of charged substances in the ISS (Sykova and Nicholson, 2008). 3. The Brain interstitial fluid 3.1. The components of brain ISF The brain ISF bathes and surrounds neural cells, and it provides the immediate medium for nutrients supply, waste removal and intercellular communication (Howell and Gottschall, 2012). ISF include water, ions, gaseous molecules, and organic molecules, such as proteins, peptides, enzymes, dopamine, extracellular vesicles (EVs), and the floating chains of glycoproteins attached to the ECM. There are few reports of the production or sources of ISF. Correlation studies of ISF and CSF suggest that ISF may originate from CSF, cell metabolism and the vascular system (Abbott, 2004; Magistretti, 2006; Rafalski and Brunet, 2011; Iliff et al., 2012; Brinker et al., 2014). Substance exchange between the ISS and the neural cell compartment exists throughout the entire lifespan of a cell (Magistretti, 2006). Neuronal activities are accompanied by the exchange of ions through the cell membrane. Neural cells maintain inner osmolarity through various ions, proteins and organic compounds (Kristensson and Olsson, 1973). The relatively higher osmolarity in neural cells drives water molecules from the brain ISS into neural cells with the aid of channel proteins, such as AQP4 and Na+/K+-ATPase enzymes in the cell membrane, which are activated upon neurocyte excitation (Yuan et al., 2005; Tian et al., 2005). The peptides and proteins manufactured in the brain ISS differ in composition due to local biochemical processes, such as the proteolytic process involved in cell surface remodeling, protein shedding, and the synthesis of regulatory peptides (Zougman et al., 2008). Some of the above active molecules can also be found in the CSF, and the long-distance transport of active substances by ISFCSF exchange has been suggested to be essential for the onset and maintenance of specific behavioral or motivational states, e.g., fear, appetite, mood, and circadian rhythms (Hobson and Friston, 2012). A series of enzymes in brain ISF are responsible for the degradation and remodeling of ECM proteins, such as matrix metallopeptidases (MMPs), tPAs, plasminogen activator inhibitors, hyaluronidase, heparanase, and chondroitinase. These enzymes are secreted by neurons, oligo dendrocytes, microglia and endothelial cells (Lo et al., 2002). MMPs are a subfamily of zincdependent proteases, that are mainly synthesized in neurons and microglial cells. MMPs are relatively prevalent in brain areas related to learning and memory (Melchor and Strickland, 2005), and they play a wide variety of roles in the brain that include development, synaptic plasticity, and repair after brain disorders, such as Alzheimer’s disease, multiple sclerosis, ischemia/reperfusion and Parkinson’s disease (Conant et al., 1999). tPAs can convert inactive plasminogen to active plasmin and are correlated the neuronal plasticity, ECM degradation, microglial activation, as well as the abnormal accumulation of amyloid plaques (Bonneh-Barkay and Wiley, 2008). EVs are released from glial cells and neurons during normal development, physiologic homeostasis, and response to pathogenic conditions (Agnati and Fuxe, 2014). The release process is energy dependent, and involves exocytosis. EVs are spherical structures that contain water-soluble components and are formed at the plasma membrane (membrane particles) by direct budding

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or shedding into the extracellular space. EVs range from 30 nm to 1 mm in size and include distinct subtypes such as exosomes, microvesicles and apoptotic bodies. These vesicles may contain signaling proteins and both coding and regulatory ribonucleic acids (RNAs), and they can be taken up by target cells, thereby facilitating cell–cell communications (Rajendran et al., 2014). In addition to acting as important mediators of intercellular communication, EVs can regulate a diverse range of biological processes including nerve regeneration, synaptic function, and behavior (Samir et al., 2013). EVs also play a sinister role in neurodegenerative diseases, infectious inflammatory diseases, and tumor-genesis in the brain. Thus, EVs may potentially be used as biomarkers of CNS diseases (Hochberg et al., 2014). Gaseous molecules and small hydrophobic, lipid soluble molecules within blood plasma can passively diffuse across the endothelium and enter the ISS. Their passive diffusion is driven by concentration differences between the two compartments. Water, ions, and small polar and charged molecules cross the endothelium via channels and transporters (e.g., Na+/K+-ATPase). These membrane proteins are asymmetrically distributed in the endothelium, which is essential to maintain the isotonicity of the local cellular microenvironment (Abbott, 2004). 3.2. ISF flow and drainage route The biophysical and biochemical balance between CSF and ISF is crucial for the metabolism of brain cells and drugs. The Brain lymphatic vasculature and the drainage pathway of brain ISF have long been controversial topics (Abbott, 2004; Louveau et al., 2015). With progress in neuroscience research, three potential pathways have been suggested. One pathway occurs at the wall of the ventricle through ependymal cells, and the other exists at the surface of the brain and spinal cord via pia-glial membranes (Pollock et al., 1997; Iliff et al., 2012). These two pathways involve direct exchanges between ISF and CSF, which are identified using optical imaging techniques. The third pathway is the blood vessel wall, where ISF can flow within the basement membrane directly opposite to blood flow, and eventually reaching extracranial lymph nodes (Bradbury et al., 1981; Abbott, 2004; Carare et al., 2008; Lonser et al., 2015). The most recent studies have revealed lymphatic vessels in the CNS, where CSF may reach deep cervical lymph nodes (Louveau et al., 2015). Conventional optical techniques may only provide the micron-depth images of the brain cortex. With newly developed in vivo tracer-based MRI techniques, these pathways have been validated and the corresponding mechanisms partially clarified (Han et al., 2012; Shi et al.,2015). Ependymal cells cover the inner ventricle surfaces with tight junctions. Unlike in the BBB, these tight junctions between ependymal cells are seldom regarded as a real barrier to substance transport because they allows the passage of macromolecules, such as ferritin and inulin (Goldman, 1913; Rall, 1968; Saunders et al., 2008; Johanson et al., 2011). This ISF-CSF communication at the inner ventricle surface has been considered to explain the pathological changes that occur in acute-stage hydrocephalus (Weller et al., 2009a, 2009b). The sudden increase in ventricle pressure causes high ependymal permeability and enhances the flow from CSF to ISF; this further results in interstitial edema of white matter (Laman and Weller, 2013). In cases of hydrocephalus, interstitial edema seldom appears in gray matter of the cerebral cortex, which may be explained by the more efficient drainage from ISF to CSF by the second pathway. The second pathway can be demonstrated using in vivo two-photon imaging with the aid of a fluorescent probe injected into the subarachnoid CSF. Driven by arterial pulsation, the fluorescent probe distributed to the brain ISS along the paravascular spaces surrounding the penetrating arteries. Finally, the probe is cleared


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Fig. 4. Pathways of ISF drainage to CSF in brain. ISF can exchange with CSF in the ventricles and subarachnoid spaces, and ISF can also drain to cervical lymph nodes. Mark A denotes that ISF can drain into ventricles through ependymocytes; mark B denotes that ISF drains into subarachnoid spaces; and mark C denotes that ISF may drain directly along the walls of capillaries and arteries to cervical lymph nodes. The arrows represent the major direction of fluid movement, and thin arrows represent the minor direction.

greater than that for the thalamus (2.30 0.62%). The t1/2 of the thalamus (1.40 0.12 h) is significantly shorter than that in the caudate nucleus (0.81 0.03 h) (Zuo et al., 2015). Although more studies are still necessary to reveal the locations and properties of all the brain divisions, the biophysical properties of brain ISF flow in the two divisions as discussed above have been employed to improve interstitial drug delivery efficiency (Xu et al., 2011a; Han et al., 2012). This advance will also provide valuable biophysical parameters for establishing 3-D brain tissue culture models. Moreover, the traditional concept of CNS drug distribution in brain tissue may be improved with the new concept of ISS-based functional divisions. Specifically, the use or development of CNS drugs must consider these functional divisions for precise and efficient drug distribution at ISS lesions instead of the whole brain. Understanding the regulation of brain ISF flow in each division of the ISS is a more challenging task (Shi et al., 2015). Clarifying substance transport in the brain ISS is necessary to establish a suitable biophysical model to form the basis for further quantitative analyses and mechanism studies of this complicated brain ISS.

4. Modeling of substance transport in the brain ISS 4.1. The mechanisms of substance transport in the ISS

via the paravascular spaces surrounding large draining veins (Iliff et al., 2012). Similar drainage from ISF in the cortex to CSF in the subarachnoid space has also been verified using tracer-based MRI (Han et al., 2012). With the aid of water-soluble tracer gadolinium diethylenetriaminepentacetic acid (Gd-DTPA), water molecules in the brain ISF are specifically ‘‘lightened’’ on MRI, allowing the dynamic distribution of brain ISF flow to be traced at the whole brain scale. It has been found that the traced brain ISF in caudate nuclei flows and distributes to the ipsilateral cortex with in 2 h, it then reaches the cortex margin and finally drains into the subarachnoid space (Han et al., 2014). MRI using a SPIO tracer, showed that the substance tranportation from the brain ISF to the deep cervical lymph nodes can be demonstrated by way of the olfactory bulb and nasal lymphatics (Muldoon et al., 2005). Fig. 4 illustrated these multiple potential pathways of ISF drainage. 3.3. Divisions of the brain ISS based on ISF flow Recently, research on the brain ISF flow in the deep brain of rats indicate the presence of a new division system in the brain. As described in Section 3.1, the ISF from caudate nuclei flows toward the ipsilateral cortex and finally drains into the subarachnoid space (Pardridge, 2011; Han et al., 2012). Although thalamus is located near the caudate nucleus, the traced brain ISF does not flow to it but moves in the opposite direction to the cortex. Moreover, the traced brain ISF in the thalamus does not cross the ‘‘boundary’’ between the thalamus and the caudate nucleus (Han et al., 2014; Shi et al.,2015; Zuo et al., 2015), and this observation has been preliminarily validated using optical techniques (Li et al., 2015). This finding indicates that the ISF in the brain ISS cannot distribute or flow globally; but is restricted to certain divisions or territories. In other words, the brain ISS contains functional divisions based on brain ISF flow. The division is characterized by the probe’s maximal volume distribution (Vdmax) and flow speed. Vdmax is defined as the ratio of the maximal distribution volume of the probe in the brain ISS to the total brain volume. Because the clearance of the tracer in the rat brain is consistent with exponential decay, the clearance speed of the tracer in the ISS is described in terms of half-life (t1/2) (the time required for the tracer amount to decrease by half). The ratio of Vdmax to brain volume for caudate nucleus (10.27 0.19%) is

Substance transport in the brain ISS is a complicated process, and it is determined by both the biophysical properties of the brain ISS and the chemical properties of the substances in the ISS. Recent works have verified that both bulk flow and diffusion are mechanisms of substance transport in the ISS, i.e., substance transport in the ISS can be driven by both concentration gradient and pressure gradient (Cserr et al., 1981; Cserr and Patlak, 1992; Abbott, 2004; Han et al., 2012). The brain ISF and interior substances have a broad spectrum of physical and chemical differences, such as molecular size, water or lipid solubility, charge, concentration of substances, pH, temperature, and viscosity. The geometry of the brain ISS determines the trajectory of substance transport and brain ISF flow. The movement of ISF molecules in the narrow and torturous ISS mostly takes the form of hindered diffusion, where the diffusion rate is much lower than that in free space (Dityatev and Schachner, 2003; Tao and Nicholson, 2004; Sen and Basser, 2005). As illustrated in Section 5, the measurement of substance transport in the brain ISS depends on the molecular probe injected into the ISS. As expected, the physical and chemical properties of these probes also affect the measurement results, and various measurement results of diffusion rates have been reported in previous works. Using a tetramethylammonium+ (TMA+) probe (molecular weight of 74), the measured tortuosity of the brain ISS mostly ranges from 1.3 to 1.8 (Rusakov and Kullmann, 1998; Sykova and Nicholson, 2008; Xie et al., 2013). This result indicates that the diffusion coefficient of TMA+ in the brain ISS is approximately 30% to 60% of that measured in free medium. The functional MRI technique of diffusion weighted imaging (DWI), provides the apparent diffusion coefficient (ADC) of water molecules in each image pixel, which indicates the average diffusivity of water molecules. DWI reveals that the typical diffusion rate of water molecules in the brain is found to be 20% to 25% of that in free medium (Baumann et al., 2012; Klimas et al., 2013). Water molecules have a diameter of 2.7 A˚ (Zhang and Xu, 1995), which is much smaller than organic molecules. These macromolecules are almost equally impacted by water molecules, and their diffusion rate is much slower than that of water in both the ISS and free medium. In agarose, the diffusion rate of dextran molecules (molecular weight of 3000)


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is more than 5 fold less than that of TMA+ (74 molecular weight) (Nicholson, 2001). Bulk flow, another important mechanism of substance transport in ISS (Cserr et al., 1981; Cserr and Patlak, 1992; Abbott, 2004; Han et al., 2012) is suggested to be partially caused by arterial pulsation (Iliff et al., 2013), where arterial pulsation refers to periodic dilation of arterial walls driven by the pulsatile blood flow. As reported in early works (Rosenberg et al., 1980; Ichimura et al., 1991; Yamada et al., 1991), the velocity of bulk flow of ISF ranges within 5–15 mm per minute in white matter, and it is unrelated to the diffusion rate. The bulk convection of macromolecules is significantly constrained by the narrow diameter of the ISS, and the movement of macromolecules of with a molecular weight of 50,000 could be less than 1 mm per day (Raghavan et al., 2006). ISS geometry determines the boundary conditions of the fluid field inside ISS, and thus has a significant influence on the substance transport in the ISS (Yuan et al., 2005). Moreover, the surface properties of the ECM are other factors that affect substance transport in the ISS. For example, the HA in brain ECM is highly negatively charged, which has a clear influence on the transport of ions, charged molecules and nanoscale particles in the ISS, such as cationic liposomes (MacKay et al., 2005). Shielding the positive charge of cationic liposomes to confer either neutrality or anionic charge can significantly improve the distribution (Saito et al., 2006; Kikuchi et al., 2008). Some proteins in the cell membrane can also actively regulate substance transport in the brain ISS. Aquaporin 4 (AQP 4) occupies 50% of the surface area of capillary-facing endfeet of astrocytes along the blood–brain barrier and brain–CSF interfaces (Haj-Yasein et al., 2011; Verkman, 2012). The water molecules entering cells through AQP4 channels cause swelling of astrocytes and decrease the ISS volume fraction, and this process can further change the diffusion or bulk flow in the ISS (Papadopoulos and Verkman, 2007; Iliff et al., 2012). 4.2. Biophysical parameters and modeling of the ISS From the discussions above, it is known that many properties of the ECM and ISF can influence substance transport in the ISS (Taber and Hurley, 2014; Pistillo et al., 2014). An in-depth understanding

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of the mechanisms and methods of regulating substance transport in the brain ISS will benefit the investigation of new drugs to treat brain diseases. Table 2 presents a comprehensive summary of biophysical parameters related to the ISS (Nam and Kaviany, 2003). As discussed in Section 5, only a small number of parameters can be quantitatively acquired using current measurement techniques. These parameters characterize the biophysical properties of the brain ISS, and the extraction and analysis of biological parameters of the brain ISS are usually conducted with the aid of probes injected into ISS (Han et al., 2014). Biophysical modeling of the brain ISS is a fundamental approach for extensively analyzing of its properties. The results from current biophysical modeling of the brain ISS are consistent with the measurement results, and have even successfully predicted the existence of ‘‘dead space’’ in ISS (Sykova and Nicholson, 2008). The biophysical modeling of brain ISS mainly includes two parts: (1) the modeling of ISS boundary condition and ECM, and (2) the modeling of substance transport in ISS. The spatial organization and surface properties of the ISS boundary and ECM determine the boundary condition of substance transport in the ISS, and multiple models have been employed to calculate the biophysical parameters of the brain ISS. The basic model is the unit cell model, which is suitable for describing diffusion around cell bodies (Mathias, 1983; Rusakov and Kullmann, 1998). Several advanced models consider the 2-D and 3-D geometry of the ISS, such as the cubic model and the pore model (Deen, 1987; Chen and Nicholson, 2000; Tao and Nicholson, 2004; Buxton et al., 2010). Modeling of substance transport in the ISS is based on continuity equation and macroscopic convective diffusion (Sommerfeld, 1949) :

@C Q ¼ rðDrCÞ þ f ðCÞv ! rC @t a

(1)

wherein C and Q represents the concentration and source of concerned substance (e.g., the probe molecules) in ISF; r represents gradient operator; f(C) represents the clearance rate of the probe in ISS that depends on C and structures in the brain; f(C) is especially important in studies of the microenvironment of tumor, because its vascular system has clear exchange with ISS

Table 2 The biophysical parameters of geometry and ECM of ISS. Category

Parameter

Unit

Descriptions

ISS geometry and ECM

Volume Fraction Tortuosity

% None

Pressure Boundary area Friction Elasticity Permeability

Pa mm2 N/mm2 Pa1 Darcy

Volume fraction denotes the ratio of ISS volume to brain volume. Tortuosity denotes the length ratio of the actual movement path of a molecule to straight distance in ISS. Pressure denotes the ISF stress Boundary area denotes the surface area of ISS boundary Friction denotes the ability of ISS boundary and ECM to resist the motion of ISF. Elasticity denotes the reversible extension ratio of the surface of ISS boundary Permeability denotes the ability of substances to cross through ISS boundary.

Viscosity

Ns/mm2

Osmolarity

osmol/kg

Density Electric conductivity Thermal conductivity Components concentration

g/ml Siemens/m W/(mmK) mmol/ml

Flow velocity

mm/s

Diffusion rate

mm/s

Vdmax t1/2 Clearance rate

mm3 s mmol/(sml)

ISF components

Substances transport and ISF drainage

Viscosity denotes the ability of ISF to resist the relative motion between its adjacent layers. Colloid osmotic pressure is exerted by proteins and usually tends to pull water into the solution. Crystal osmotic pressure is exerted by small molecules. Density denotes the mass of ISF in the unit volume Electric conductivity denotes the ability of ISF to conduct an electric current. Thermal conductivity denotes the ability of ISF to conduct heat Concentration denotes the amount of ions or molecules in unit volume of ISF. Flow velocity denotes the movement speed of water; convective velocity is the speed of ion or molecule movement caused by the bulk flow of ISF. Diffusion rate denotes the movement speed of water, ions or molecules caused by Brownian motion. The maximal distribution volume of tracer (i.e., Gd-DTPA) in brain tissue The time duration that tracer amount decreases by a half Clearance rate denotes the removal of tracer molecules in ISS.


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(Johansson et al., 2015). a represents the volume fraction of the ISS; v ! represents the velocity of the bulk flow of ISF; t represents time; and D represents the diffusion tensor of concerned substance having six independent elements only, i.e., Simplifying Eq. (1), the diffusion tensor D can be written as (Nicholson, 2001): D ¼ Dxx e ! xx þ Dyy e ! yy þ Dzz e ! zz

(2)

where only the three diagonal elements of diffusion tensor are considered if the axes of the coordinate system are chosen to be the principal diffusion directions (PDDs) of the diffusion tensor. For cases in which the diffusion is isotropic, the diffusion tensor in above equation can be replaced by a scalar coefficient (i.e., a diffusion coefficient). Moreover, when the bulk flow and clearance are absent (e.g., the diffusion of Gd-DTPA in brain ISS), Eq. (1) can be modified as:

@ C D0 2 Q ¼ r Cþ a @t l2

(3)

wherein D0 is the diffusion coefficient of the probe in a free medium, l represents the tortuosity, and r2 represents the Laplace operator. In solving the inverse problem of the above transport equations, the desired biophysical parameters are calculated by a fitting process. Here we can have multiple solutions, because the considered boundary condition is generally not sufficient to select a unique solution. In such cases, additional constraint conditions can be considered, and here in these conditions are the pre-given ranges of calculated parameters (such as tortuosity and volume fraction). The ranges of key biophysical parameters in above transport equations can be found in the above sections and previous studies (Nicholson, 2001; Sykova and Nicholson, 2008). In practical analyses, the scanned distribution of tracers or probes (using MRI or optical imaging) has to be applied with an image processing program to reduce the distortion (such as the offset of scanned animals and the noise of images) that appeared during the scanning process. As mentioned above, many biophysical properties of the ISS and associated parameters (in Table 2) may affect substance transport in the ISS. Approximations of the spatial structure of ISS and fluid properties of ISF are considered when establishing above transport equations. These approximations in modeling ISS boundaries and ECM mostly include the following: (1) the ISS has a rigid spatial geometry; (2) ISS boundaries has a smooth and uncharged surface, and the influence of ECM is also ignorable. (3) ISS has an isotropic structure. The following assumptions are common in modeling ISF: (1) ISF is a continuous and uniform fluid without suspended component, and (2) the movement of the molecules in ISF is mainly caused by diffusion. Several works have shown efforts to incorporate the elasticity of the ISS boundary into models (Raghavan and Brady, 2011; Haar et al., 2014), although many parameters of ISS in Table 2 are excluded. The above approximated models produce somewhat consistent measurements, it is still important to include more parameters from Table 2 into future biophysical modeling studies of the ISS. 5. In vivo measurement techniques of brain ISS In recent decades, numerous measurement techniques have been developed for brain research. Most of these techniques are suitable for investigating neural circuit, and a few general techniques can be considered for measuring multiple brain compartments, such as immunohistochemistry, microdialysis, electron microscopy, and optical microscopy. Ex vivo immunohistochemical and

immunofluorescent stains have been particularly helpful for analyzing the components of brain ECM, and microdialysis can provide continuous monitoring of the local concentration of drugs and metabolites of interest in the ISS. Due to the fixation and dehydration procedure involved in in vitro measurements, the width and volume fraction of the ISS may be under-estimated by traditional microscopy methods (Horstmann and Meves, 1959; Villegas and Fernandez, 1966; Coventry et al., 1995; Chintala et al., 1996). Therefore, the biophysical and biological properties of ISS-like small and dynamic structures should be acquired and recorded in live brains or in live brain slices. In this section, the current state-of-the-art techniques for in vivo measurements of the ISS are introduced. 5.1. The principles of in vivo imaging and measurement of the brain ISS Three special techniques have been developed to measure or image the brain ISS, including the ion-selected microelectrode (ISM) (Nicholson and Rice, 1988; Nicholson, 2001), integrative optical imaging (IOI) (Xiao et al., 2008), and tracer-based MRI techniques (Benveniste and Blackband, 2002; Lee and Chang, 2004; Han et al., 2012; Han et al., 2014). ISM detects the electric potential changes induced by the exogenous ions in the brain ISS using an ion-selected microelectrode. Optical signals of fluorescent probes in the ISS is measured with IOI techniques. The tracer-based MRI method is a novel measurement technique, and it uses magnetic sensitive contrast agents as probes to label and trace water molecules in ISF (Han et al., 2014). These measurements share three basic procedures: (1) micropuncture to introduce or inject probes into the ISS; (2) the detection and quantitative measurment of the injected probe; and (3) post-processing and calculation to extract the parameters. Because no specific molecule is unique and suitable as a natural endogenous probe for visualizing the brain ISS, exogenous probes or tracers are employed in all measurement techniques. The probe or tracer must satisfy the following requirements (Nicholson and Tao, 1993; Han et al., 2014): (1) extracellular distribution: the probe or tracer does not cross the capillary walls or the membranes of neural cells, and thus is well constrained within the ISS; (2) good biocompatibility: the probe or tracer is nontoxic to neurons and does not cause gliosis; (3) biological or chemical inertness: the probe or tracer does not react with the ECM or with substances inside ISF; (4) diffusion properties: relatively small size, allowing effective diffusion and distribution in the ISS; and (5) quantification: the concentration of the probe should have a clear monotonic relationship with the intensity of detected signals (electric, optic, and magnetic), which ensures the further calculation of diffusion or flow parameters in the ISS. The calculation of the biophysical parameters of the ISS is based on both the selected diffusion model and the obtained time profile of probe concentration. 5.2. Ion-selected microelectrode techniques The principle of ion-selected microelectrode (ISM) techniques is usually known as voltammetry, i.e., a branch of electrochemistry. In ISM techniques, the geometry of the brain ISS is quantitatively measured with exogenous charged ions, and the current of the ions is recorded by an ISM. The measured electric potential is converted to the probe concentration for further calculations of ISS parameters. According to their ability to drive the probe into the ISS, ISM techniques are classified as real-time iontophoresis (RTI) methods or real-time pressure injection (RTP) methods. The selected charged ISM probes include TMA+, tetraethylammonium (TEA), hexafluoroarsenate (AsF6), and a-naphthalenesulfonate (Nicholson et al., 1979; Nicholson and Philips, 1981).


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RTI-TMA+ is a general measurement technique for the brain ISS, they employs TMA+ as the probe. TMA+ is delivered from a special micropipette into the brain sing the iontophoresis (Nicholson, 2001),the micropipette is a single barrel glass capillary containing TMA+ with an inserted chloridized silver wire attached to a constant current generator. That produces a positive current to drive TMA+ into the ISS (Nicholson, 1992). The ISM is planted 20– 200 mm away and the local electrical potential is converted to the concentration of the TMA+ ions (Hrabetova and Nicholson, 2007). The measured concentration–time relation of TMA+ ions at a known distance can then be used to extract the diffusion parameters according to the classical diffusion equation (Sykova and Nicholson, 2008). The small ion TMA+ (molecular weight of 74) distributes mainly within the ISS and is not known to affect the physiological functions of local tissues at the employed concentrations (Nicholson and Philips, 1981). As mentioned by Nicholson (2001) and Kaur et al. (2008), TMA+ probe may enter neural cells and the vascular system, which indicates that the TMA+ method has a visible clearance term, i.e., f(C) in Eq. (1). RTI-TMA+ can provide the diffusion coefficient, volume fraction, tortuosity, and clearance rate of probe within a distance of 10 to 200 mm (Nicholson and Tao, 1993; Ujec et al., 1979). In the RTP method, the tracer or probe is driven by pressure. Commonly used probes include dopamine, ascorbic acid (Stamford et al., 1985), and catecholamine (Leszczyszyn et al., 1990; Wightman et al., 1991). However, the distribution volume of these substances in RTP is not as easily controlled as in RTI technique (Hrabetova and Nicholson, 2007; Rice et al., 2007). 5.3. Optical Imaging Techniques In optical imaging techniques, fluorescent molecules are injected into the brain ISS and then detected with the aid of a set of optical devices. Dextran, albumin, transferrin, and polyethyleneglycol have been used as probes to visualize the brain ISS. Unlike the probes used in ISM, the probes for optical imaging are usually biologically active and may be captured by receptors, which may decrease the accuracy of the measured ISS parameters. Dextran is the most popular probe due to its high water solubility and good biocompatibility. The employed size of dextran molecules ranges from 3 kDa to 70 kDa (Nicholson and Tao, 1993; Xiao et al., 2008). The selected probe is injected into the brain ISS of the cortex through a micropipette under external pressure pulses, and the brain tissue with a probe in the brain ISS is illuminated by excitation and bright-field lights. The fluorescent probe molecules in the ISS are excited and transmit fluorescence light. The transmitted fluorescence light passes through the objective and dichroic mirrors, and is finally received and imaged by a charge-coupled device (CCD) camera (Nicholson, 2001; Tao and Nicholson, 1995; Hrabetova and Nicholson, 2007). The received fluorescence signal can be transformed to probe concentration, the distribution process of probe molecules in the brain ISS can be dynamically recorded, and the diffusion coefficient D and ISS tortuosity l can be calculated. To quantitatively measure the parameters of the ISS, optical imaging can be integrated with the RTI-TMA+ technique (ProkopovaKubinova et al., 2001). Due to the detection limitations of light microscope, integrative optical imaging (IOI) is mostly used to image the ISF flow or substances transport in the cortex, i.e., at a depth of approximately 200 (Tao and Nicholson, 1996; Thorne and Frey, 2001; Thorne et al., 2008). The distribution of fluorescence in 3D tissues can be determined via laser scanning microscopy (LSM) (Thorne et al., 2008; Xiao et al., 2008; Sherpa et al., 2014). Both single-photon and multi-photon LSM techniques have been used. The multi-photon technique takes advantage of longer wavelengths and is able to

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image deeper brain layers than the single-photon technique. Moreover, simultaneous multi-fluorescence channel imaging enables the investigation of other structures in tissues, such as the vascular system. The RTI-LSM technique integrates the RTI and LSM techniques, and is therefore able to image the distribution of optical probes in the brain ISS, and to measure ISS volume fractions, diffusion coefficient, and ISS tortuosity (Xie et al., 2013). However, RTI-LSM can only image superficial brain tissue layers, the imaging depth is within approximately 200 mm. 5.4. Tracer-based MRI and quantitative measurement MRI has been widely used for in vivo imaging of biological tissueS, because of its advantages of lminimal tissue damage, excellent soft-tissue contrast, real-time monitoring, and global imaging (Stejskal and Tanner, 1965; Le Bihan, 1995; Brooks and Pavese, 2011; Ewers et al., 2011; Grodd and Beckmann, 2014). Among the currently available brain ISS measurement techniques, MRI is unique in detecting and imaging the brain ISS at the whole brain scale, especially for investigations of the brain ISS in the deep center of the brain (Han et al., 2014; Zuo et al., 2015; Shi et al., 2015). The tracers used in MRI methods can be classified into positive or negative groups, where positive tracers increase the MRI signal intensity on T1 (longitudinal relaxation time) weighted images and negative tracers decrease it on T2 (transverse relaxation time) and T2* weighted images (Duong et al., 2001; Han et al., 2012; Cabral et al., 2014; Han et al., 2014). Negative tracers, e.g., super paramagnetic iron oxide (SPIO), have been successfully used to investigate the drainage route of the traced brain ISF, although the significant susceptibility to artifacts and distortion of the brain parenchyma make it impossible to image and quantitatively measure brain ISS parameters (Muldoon et al., 2005; Muthana et al., 2015). Gd-DTPA is a positive contrast agent frequently used in clinical applications. Compared with other ion or fluorescent probes, Gd-DTPA has many advantages, including biological inertness, thermal stability, small molecular size, and extracellular distribution (Caravan et al., 1999; Han et al., 2014). At the employed concentration, Gd-DTPA does not cause any distortion or artifacts of the brain parenchyma on MRI. Furthermore, Gd-DTPA can trace endogenous water molecules in brain ISF by shortening the spin-lattice relaxation time of hydrogen nuclei in water molecules within an effective distance of 2.5 A˚, which is visible as a high signal on MR images (Han et al., 2012). Gd-DTPA has been used in previous studies to simulate or trace the substances transport in the brain ISS (Shoesmith et al., 2000), while the calculation of brain ISS parameters was not available until a study conducted by Xu and Han in 2011b: a special 3-D T1weighted imaging sequence was developed and modified to quantitatively measure the concentration of Gd-DTPA in real time (Xu et al., 2011b). The tracer-based MRI enables a ‘‘one-stop shopping’’ acquisition of many transport and distribution parameters in brain ISS, including Vdmax, t1/2, D, l (Han et al., 2014). After the injection of tracer into the brain ISS, the tracer is diluted and the signal intensity in MRI decreases gradually, which presents as an attenuation of the signal enhancement on a series of MR images (Han et al., 2012). In the inverse problem of transport equations, the extracted diffusion parameters depend on the measured concentration of the injected probe in the brain ISS over time domain. In this tracer-based MRI measurement of the brain ISS, an image processing program must be applied before the fitting process of parameter extraction, and it is designed to eliminate the distortions of scanned MRI data and to calculate the Gd-DTPA concentration (Xu et al., 2011b; Li et al., 2013). The major functions of this image processing program include the removal of MRI noise, the rigid registration for scanned images,


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Fig. 5. Procedure for measuring the ISS within the rat brain using the tracer-based MRI technique (above) and the ‘‘lightened’’ water molecules by MRI tracer Gd-DTPA (below left). Step A: MRI pre-scanning is applied to the rat to acquire the pre-contrast image; Step B: intraparenchymal microinjection of Gd-DTPA into the rat brain to enhance the MRI signal intensity of the water molecules within the ISS; Step C: the concentration distribution of MRI tracer can be obtained by subtracting the pre-contrast image from post-processing images; Step D: analysis of the distribution of MRI tracers and calculation of ISS parameters. The scanned MR images of the rat show that the brain is a physiologically partitioned system referring to the distribution of MRI tracers in the brain ISS (below right).

and conversion of the MRI signal intensity to the concentration of the injected Gd-DTPA probe. As shown in Fig. 5, using the tracer-based MRI technique, the flow (or transport) of the traced brain ISF from the deep center of the rat brain can be investigated, The results indicate that the brain ISS is a physiologically partitioned system, and each division is characterized by the unique distribution territory and drainage velocity of the traced brain ISF. The location-dependent properties of the ISF drainage system will improve our understanding of the ISS, and provide a useful reference for optimizing the technique for local brain drug delivery (Guerin et al., 2004; Gulati et al., 2012). Thus far, the tracer-based MRI technique is the only measurement technique that provides a global view of 3-D visualization of the dynamic drainage flow of brain ISF. Moreover, this technique can also produce multi-point measurements of diffusion parameters along any direction near the injection site. Additionally, giving potential independence and ‘‘lighting’’ endogenous water molecules, this tracer-based MRI technique may provide a special advantage in analyzing and predicting the dynamic distribution of water-soluble drugs in the brain (Xu et al., 2011a). It is challenging to develop a non-invasive measuring technique, that provides both the diffusion parameters of water molecules in the brain ISS and the anisotropic structure of various compartments in brain tissue (Le Bihan et al., 1988). To establish such a technique, four questions must be satisfactorily answered. The first question is how to model the anisotropic movement (including diffusion and bulk flow) of water molecules. The second is how to include all the major compartments (i.e., vessels, ISS and neural cells) of brain tissue in the mathematical model of MRI signal intensity. The third one is that how to distinguish the various compartments according to the movement characteristics of water molecules. The last is how to efficiently calculate the nonconvex inverse problem of desired modeling while considering the anisotropic movement of water molecules as multiple compartments. 5.5. Microdialysis technique Microdialysis sampling was first established in 1966 (Bito et al., 1966), and it is the only sampling technique that can continuously monitor drugs and metabolite concentrations in the brain ISS. This real-time analysis method barely disturbs the local BME because there is no fluid loss or pressure artifact (Portas et al., 2000; Herrera-Marschitz et al., 2010). The sampling system consists of a microdialysis pump, microdialysis probe, and microvial. With the aid of a stereotactic positioning coordinate system, the microdialysis probe is planted

into the target location in the brain tissue. Driven by the pump, the perfusate (mainly Ringer’s solution or artificial CSF) enters the microdialysis probe at a velocity of 0.5–5 ml per minute. The semipermeable membrane in the tip, which has a diameter of 0.15– 0.3 mm, is the most important unit of the microdialysis system (Benjamin et al., 2004). The perfusate is driven though the probe and collected in a microvial, where the collected liquid is called the dialysate (Plock and Kloft, 2005). Different types of semipermeable membranes have been designed for different purposes and tissues, and each type of semipermeable membrane can be distinguished fby its specific molecular weight cut-off, shape, and material (Hoistad et al., 2002). The exchangeable substances usually range from 6 kDa to 100 kDa, large molecules and proteins cannot diffuse through the membrane (Chefer et al., 2009). The quantification of sampled molecules in dialysates from brain ISF is conducted with general analysis devices, such as highperformance liquid chromatography (Kanno et al., 2004), liquid chromatography mass spectrometry (Larmene-Beld et al., 2014), nuclear magnetic resonance (Khandelwal et al., 2004), radiotracer (Bernards et al., 2003), liquid scintillation spectrometry (Hoistad et al., 2002), gas chromatographic analysis (Winter et al., 2004), and flame ionization (Lindberger et al., 2001). 6. ISS and brain disorders In this section, we describe neuropathologic alterations in the ISS caused by several common brain disorders. Neuropathologic alterations of the ISS can generally be classified as follows: (1) ISS geometry, i.e., changes in volume fraction and tortuosity (Hrabetova et al., 2009); (2) ECM and its components (Bekku et al., 2010); (3) the components and biochemical properties of ISF; and (4) substance transport and ISF flow in the ISS (Lehmenkuhler et al., 1991; Lehmenkuhler et al., 1993; Kohling and Lehmenkkhler, 1993; Schwindt et al., 1997; Chen et al., 2005). The purpose of the above classification is to facilitate the depiction and quantitative studies of the ISS, although different alterations may occur together or follow each other (Zoli and Agnati, 1996). 6.1. Glioma Uncontrolled growth of tumor cells in glioma can destroy the normal architecture of brain tissue, and this pathological damage is accompanied by the biochemical processes of proteolytic degradation of ECM and active movement of tumor cells (Birlik et al., 2006). Alterations of ISS geometry have a clear relationship with the invasiveness and malignancy of glioma. Compared to normal brain


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tissue, both the volume fraction (a) and tortuosity (l) of the ISS may be increased in low-grade diffuse astrocytomas, anaplastic astrocytomas, and a further increase is demonstrated in solid portions of high-grade astrocytomas (Vargova et al., 2003). In pilocytic astroglioma and ependymoma, a is increased without any change in l. No change in the ISS geometry is found in oligodendroglioma (Zamecnik et al., 2004). Increased a of ISS has been verified in tenascin-accumulated astrocytoma but not in tenascin-negative tumors (Mahesparan et al., 2003). In high-grade glioma, the overproduction of tenascin familial aggregation of ECM may be the cause of increased l and restricted diffusion (Zamecnik, 2005). Components of the ECM such as laminin, collagen IV, tenascin and hyaluronic acid have been shown to be preferred substrates for glioma spread and are ECM components in the pathways of known dissemination (Goldbrunner et al., 1998). Glioma EVs in brain ISF carry a variety of biomolecules such as oncogenic growth factors, receptors, enzymes, transcription factors, and signaling and immunomodulatory molecules. These EVs can support malignancy of glioma, including tumor growth, expansion, invasion, and survival against host immune responses. Substance transport in the ISS is significantly restricted in ISS of glioma, as indicated by the increased tortuosity (Li et al., 2013; Han et al., 2014). Moreover, the interstitial fluid pressure (IFP) increases with tumor volume in glioma, which reduces the driving force behind the convective transport of substances and drugs across capillary. To improve transport in the ISS, especially large molecular transport, convection enhanced delivery (CED) has been investigated to improve the drug distribution in brain tumors. In CED, one or more catheters is stereotactically placed directly into brain tumors or tissues through cranial burr holes. Therapeutic agents are continuously administered through the catheter with a positive pressure gradient at the catheter tip. As the pressure is maintained, it creates convection to supplement the diffusion of drugs through ECS, thus enhancing the distribution of the drug to the targeted area. In 2010, a phase III clinical trial of anti-tumor agentsadministrated via brain ECS was approved by the United States Food and Drug Administration. (Kunwar et al., 2010). More details about CED are presented in Section 7. 6.2. Ischemic stroke Ischemic stroke is commonly defined as a sudden loss of neurological function resulting from insufficient cerebral blood flow. The low blood supply leads to the delivery of both oxygen and energy substrates at levels below metabolic requirements. In the very early stages of ischemic stroke, excessive water is transported into neural cells, especially astrocytes, due to disorders of Na+-K+ pumps resulting from energy failure and blood–brain barrier disruption, and cytotoxic edema presents as marked swelling of the cell bodies and processes. (Steiner et al., 2012). These pathological changes dramatically decrease the ISS volume and increase the ISS tortuosity. The ISS a decreases obviously from 0.20 to 0.05, and l increases from 1.5 to 2.1 (Sykova et al., 1994; Vorisek and Sykova, 1997). The increase in l during ischemia is accompanied by a reduction in diffusion, and this is suggested to be caused by dead-space in the micro domains of ISS (Hrabetova et al., 2003). Alterations of ISS geometry block the ISF drainage route (ArbelOrnath et al., 2013), which results in the accumulation of numerous harmful factors released from the damaged neural cells (such as glutamate, pro-apoptotic factors, pro-inflammatory factors and free radicals). This accumulation further aggregate the damage. Additionally, the constituents of ISF are remarkably changed following an ischemic attack. Increase in lactate and glutamate and

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decrease in glucose in ISF can be detected by microdialysis measurements. Osteopontin accumulates in the ECM 5–15 days after stroke, and finally forms the boundary of the glial scar (Hobohm et al., 2005; Al’Qteishat et al., 2006). The elimination of brain edema (both vasogenic and cytotoxic edema) and reestablish the ISF clearance route may provide new avenues to alleviate pathological processes under ischemic injury. Moreover, the efficiency of administration of neuronal protective agents to treat brain ischemic damage via brain ISS has been recently verified using cytidinediphosphate choline (CDPC) (Xu et al., 2011b). 6.3. Alzheimer’s disease Alzheimer’s disease (AD) is characterized by the loss of neurons in the cortex, where neurofibrillary tangles accumulate inside neurons and amyloid beta (Ab) deposits accumulate in the brain ISS (Mudher and Lovestone, 2002; Nistor et al., 2007; Burns and Iliffe, 2009). The above pathological changes caused increased a and l in the cortex in a mouse AD model (Sykova et al., 2005). Ab is a fragment of the transmembrane amyloid precursor protein (APP). In AD,the enzyme degrades APP to smaller fragments in the brain ISS(Hooper, 2005). These fragments give rise to fibrils of Ab, which forms clumps that are deposited outside neurons in dense formations known as senile plaques (Ohnishi and Takano, 2004). Some components of ECM contribute to the formation and stabilization of Ab plaques in the brain ISS, such as HSPGs, perlecan, agrin, collagen XVIII and syndecans and glypicans, and these can form complexes with both the dense and diffuse types of Ab plaque (Snow et al., 1990; Verbeek et al., 1999; Cotman et al., 2000; van Horssen et al., 2002; Miosge et al., 2003; van Horssen et al., 2006). A significant reduction in reelinexpression is found in AD brains (Fatemi, 2005). There is evidence that reelin negatively affects Ab accumulation when it interacts with apolipoprotein E (APOE) receptor 2 and low density lipoprotein (LDL) receptor 2 (Hoe et al., 2006). Although Ab has been associated with the brain ECM, how and why Ab accumulates in the cerebral cortex is unclear; this issue needs to be further explored and clarified. The drainage of brain ISF is crucial for the clearance of Ab. Soluble Ab in ISF reaches the capillar bedsy beds, and the basement membranes between smooth muscle cells in the tunica media of arteries (Weller et al., 1998, 2009a, 2009b). Blockage of brain ISF drainage accelerates the abnormal deposition of Ab and is closely associated with neuronal degeneration (Iliff et al., 2012; ArbelOrnath et al., 2013). In addition to the above drainage within ISF, Ab drains through the perivascular space to reach the CSF, and the concentration of Ab in CSF is significantly altered in dementia (Blennow et al., 2010). The ISF-CSF communication pathway in the subarachnoid space has been applied to develop an alternative CNS drug delivery strategy, i.e., intranasal administration. Here drugs delivered intranasally are transported along olfactory sensory neurons to yield significant concentrations in the CSF and olfactory bulb (Misra et al., 2003). Using this method, the therapeutic neurotropic factor is delivered to the olfactory bulb to treat AD. Proposed pathways of ISF drainage are illustrated in Fig. 2. An in-depth understanding of the ISS may facilitate the discovery of new ways to reduce Ab accumulation and damage in CNS disorders. In addition to the above common brain diseases, alternations of the ISS have also been reported in other diseases, such as Parkinson’s disease (Marti et al., 2010), multiple sclerosis (Simonova et al., 1996; van Horssen et al., 2007; Sykova and Nicholson, 2008; Miabi et al., 2010), and epilepsy (Rogawski, 2009). With progress in the in vivo techniques of ISS measurement, the links between ISS properties and brain disorders will be further clarified at cellular or sub-cellular levels.


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7. Drug delivery via brain ISS 7.1. The demand for drug delivery via ISS Brain disorders, such as brain tumors, AD, and stroke, are a significant cause of human disability, and the patients suffering from brain disorders are far more than the people dying of all types of systemic cancer and cardiovascular diseases. Due to the risks and side effects of surgical treatment, pharmacotherapy is the preferred approach for treating brain disorders. However, due to the use of standard drug delivery by intravenous infusions, the clinical success rate of new CNS drugs is only 7%, compared with approximately 15% for other types of drugs (Pangalos et al., 2007; Wolak and Thorne, 2013). Standard trials of drug delivery to the brain by intravenous infusions have revealed limited penetration of the brain tissue, and the clinical failures of many potentially effective therapeutics for brain disorders is due to our inability to effectively deliver and sustain drugs within the brain (Modi et al., 2009). This inability is partly due to the lack of knowledge of the BME. The investigation of neuro-protective drugs for ischemic stroke is an example of the dilemma of standard drug delivery, which has taken several decades, cost billions of dollars, and led to complete failure in clinical applications. The vascular compartment takes up only 3% to 5% of the total brain volume and the administered drug, but all the previous drug investigations and clinical trials in this field have considered the vascular compartment the preferred route of administration to the ischemic or penumbra region of the brain. (Fisher et al., 2009; Bidros et al., 2010). (Macdonald et al., 2008; Lees et al., 2013). With traditional oral or intravenous administration, the drug needs to reach the ischemic region where there has been no blood supply or low perfusion for a substantial period. Additionally, the BBB allows only very low penetration, and the cerebral microvasculature in tumor adjacent regions of normal brain may be even less permeable to drugs (Misra et al., 2003). Finally, if the drug can pass the BBB, it still must travel from the capillary bed to the cells under ischemic injury (Fuxe et al., 2010). In response to this dilemma of standard drug delivery, aggressive efforts have focused on the development of new strategies to more effectively deliver drugs, such as BBB disruption, Liposomes and nanoparticle soluble drugs (Figley and Stroman, 2011). These methods focus on how the drug molecules pass through the BBB. Becasue the ISS provides a direct space for substance transport and exchange among neural cells, local drug delivery via ISS attracts the attentions of scientists. Local brain drug delivery via the ISS is a highly technical procedure that involves the stereotactic placement of a catheter through cranial burr holes directly into the brain tissue or target (e.g., tumor). Therapeutic agents are administered through the catheter, and using a micro-infusion delivery system, a concentration gradient is created at the catheter tip driven by pressure. The procedure creates enhanced flow of the drugs through the extracellular spaces and the drug distribution to the targeted area. The aim of local drug delivery is to distribute the drug at higher concentrations to brain lesions. Based on the driven force and mechanism of the drug’s transport in the ECS, local drug delivery can be classified as convection enhanced delivery (CED) simple diffusion delivery (SDD). Although local delivery via the ISS is still an experimental method due to regarding its safety and efficacy, this novel method shows advantages compared to the dilemma of standard drug delivery, including bypass of the BBB, targeted distribution through large brain volumes, and limited systemic side effects. As an example, the practical application of neuro-protective drug, CDPC for ischemic stroke has been difficult in previous research

(Clark and Clark, 2012). Recently, the administration of a very small dose CDPC through the brain ISS using a novel SDD method has proven more efficient than standard trials (Han et al., 2011; Xu et al., 2011a). According to the illustrations presented in Section 4, we know that many factors affect the transport of therapeutic drug agents in the brain ISS, such as electric charges and pressure, and controlling the distribution or transport speed of injected drugs in the brain ISS is particular complex. In the future, several goals would be attractive for scientists in the area of local drug delivery via the ISS: (1) modeling of substance transport in the ISS and prediction of the dynamic distribution of CNS drugs, and (2) the development of high-efficiency and safe methods of regulating the transport of drugs or substances in the brain ISS (Shi et al., 2015). 7.2. Convection enhanced delivery Although the flow and transport of ISF in the ISS at the wholebrain scale were far from clear in the early 1990s, scientists had begun to investigate the possibility of using the ISS to delivery drugs to circumvent the BBB. ISS-based drug delivery is also known as CED in the literature, which is conducted with the continuous injection of the therapeutic agent under positive pressure via a catheter implanted into the brain (Bobo et al., 1994; Debinski and Tatter, 2009; Barua et al., 2013; Anderson et al., 2013; Barua et al., 2014). Based on a retrospective clinical study, it was reported that infusion parameters may improve the efficiency of drugs delivered by CED (Sampson et al., 2010). CED offers a number of advantages over conventional drug delivery methods, including bypass of the BBB, minor systemic toxicity and better efficacy. Despite showing great promise in the treatment of high-grade glioma, PD and AD, substantial refinements are necessary before CED can be successfully translated to the clinic, primarily in the following areas: (1) the back flow of injection in CED may degrade its performance; (2) the concentration and distribution of the injected drug cannot be easily predicted and controlled (Sampson et al., 2009; Barua et al., 2012a, 2012b); (3) the side effects of CED may be significant in practical applications due to mechanical damage to brain tissue (Lidar et al., 2004; Slevin et al., 2006; Bruce et al., 2011). Because of the above technical challenges, great efforts are still dedicated to optimizing CED technology, e.g., implantable intermittent delivery (Barua et al., 2013). All of the above problems originate from an incomplete understanding of the ISS in the normal brain and tumors, inevitable changes in ISS structures caused by drug infusion, and the pharmacokinetics of CED are still poorly understood (Sampson et al., 2009). Local brain drug delivery would be more practical, if the distribution and the processes of brain ISF in the live brain could be monitored and quantitatively analyzed, An effective method is therefore needed to optimize the operational parameters, including infusion rate, catheter design, catheter placement and a feasible pharmacological formulation. 7.3. Simple diffusion delivery Simple diffusion delivery (SDD) is a recently developed local brain drug delivery method that uses the concentration gradients to drive pharmaceutical agents to target zones via the brain ISS (Han et al., 2011). It was previously believed that the brain ISS was highly connected, such the molecules could travel through multiple pathways to reach another location at any given point in the brain ECS. However, according to new results based on the tracer-based MRI technique, no such global distribution has been demonstrated. Instead, a new ISS division system based on brain ISF flow distribution territories has been revealed and has been


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preliminarily validated with optical techniques (Sykova and Nicholson, 2008). (Han et al., 2011; Han et al., 2014; Li et al., 2015). SDD is based on the above findings of the brain ISS divisions and the properties of substance transport in each division. Before or during SDD, the tracer-based MRI technique has been used to trace the dynamic distribution of the water soluble probe Gd-DTPA, along with the transport and flow of water molecules in the brain ISF. Due to the inertness of GdDTPA, its biophysical parameters provide the net background or reference for other water soluble agents, such as CDPC. Therefore, compared to CED, the unique advantage of SDD is that the dynamic distribution of drugs in any specific division can be simulated and the full immersion and contact with target cells makes treatment with only small doses of drug more effective (Xu et al., 2011b). Moreover, the delivery process without continuous pressure avoids the drawbacks of the CED method, e.g., unwanted backflow, uncontrollable distribution, and tissue damage. Both CED and SDD are promising methods for local drug delivery to the brain, although several challenges remain to be overcome before their practical application in clinical treatment. Of particular importance is to clarify the influence of factors (e.g., injection pressure) on the distribution and spread rate of drugs in various brain ISS divisions. Another important issue is the manual method for regulating the distribution and transport of drugs in each brain division (Shi et al., 2015). We have successfully applied prophylactic treatment for ischemic stroke in rats by injecting CDPC based on the SDD method. The effective dose via the brain ISS was only approximately 0.1% of that applied through the vascular system (Xu et al., 2011a). 8. Conclusion The brain is a delicate organ that has evolved over millions of years, and it provides an efficient means for humans to feel and respond to the outside environment, and have intelligence and consciousness. Brain functions can be influenced by the dynamic internal environment (especially the ISS), which is an important aspect of neuroscience research. With the consideration of the ISS, new perspectives on brain research will expand our understanding of basic brain functions and mechanisms, such as perception, reflection, motion, cognition, memory, and emotion. The ISS is an elastic porous structure that supports the brain organization, and the contents of the tortuous and narrow ISS, including solutes and ECM, maintain a dynamic balance to support the viability of neural cells. Due to the complexity of this system, however, many mechanisms and properties of the ISS remain unknown. To understand these issues, we need to develop new techniques to study the brain ISS, including biophysical modeling, next generation brain imaging techniques, and techniques for large-scale recording and signal modulation in the CNS, which were not discussed in this review. The results from ISS research can be used to improve the treatment of brain disorders through the development of new drugs or novel delivery systems for drugs, genes and stem cells. Acknowledgements This work is partially supported by the National Natural Science Foundation of China (NSFC, Grant Nos. 91330103, 61450004, 61470005). Here the authors would also acknowledge the suggestions and supports from Prof. Junhao Yan, Prof. Lan Yuan, Prof. Yu Fu, Prof. Dehua Chui, Dr. Wei Wang.

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