Engineering Biomaterials for Neural Applications 3031114086, 9783031114083

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Elizabeth Nance   Editor

Engineering Biomaterials for Neural Applications

Engineering Biomaterials for Neural Applications

Elizabeth Nance Editor

Engineering Biomaterials for Neural Applications

Editor Elizabeth Nance Department of Chemical Engineering University of Washington Seattle, WA, USA Department of Bioengineering University of Washington Seattle, WA, USA

ISBN 978-3-031-11408-3    ISBN 978-3-031-11409-0 (eBook) https://doi.org/10.1007/978-3-031-11409-0 © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2022 This work is subject to copyright. All rights are solely and exclusively licensed by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors, and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, expressed or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. This Springer imprint is published by the registered company Springer Nature Switzerland AG The registered company address is: Gewerbestrasse 11, 6330 Cham, Switzerland

Preface

The brain is considered the most complex organ in the body, and one that we have had a longstanding fascination with how it functions. Early philosophers Galen and Aristotle in the time of 170–350 BC first suggested the brain was the seat of complex thought, and drove our personality and our daily bodily functions. The first detailed sketch of the nervous system was generated in the sixteenth century by Andreas Vesalius, and by 1791, Luigi Galvani demonstrated the important role of electrical firing. In 1832, Jan Evangelista Purkyne identified the first neuron (later named Purkinje cells), although the term neuron was not introduced until 1891 by Wilhelm von Waldeyer. Robert Remak and Theodor Schwann identified the first glial cell, Schwann cells, in 1838, which was followed with coining of the term neuroglia in 1859 by Rudolf Virchow. By the late 1800s, Paul Broca and Carl Wernicke introduced the concept of specific brain regions, and Paul Ehrlick identified the exclusionary nature of blood vessels in the brain, which was later coined as the blood-brain barrier in 1900. Camillo Golgi and Santiago Ramon y Cajal received the Nobel Prize in 1906 for describing the structure of the nervous system. Microglia were discovered in 1919 by Pio del Rio-Hortega, but like many other aspects of the brain, our appreciation of these cells and their critical role in the brain took another 100 years to come to light. As technology has advanced, our understanding of the brain has rapidly evolved, and new discoveries continue to be made. In the last 20 years alone, scientists have identified the glymphatic system as a system for waste clearance in the brain, uncovered the biochemical processes that determine how memories are formed and accessed, and identified that the brain is highly malleable into adulthood, among many other prominent findings. Yet, as our understanding of the brain has evolved, so has our awareness of where failures in normal brain processes give rise to pathology and disease. This has driven a greater need for advancing tools and technologies to better diagnosis, prognose, and treat brain diseases, or maintain the health of the brain across the increasing human lifespan. Along with this need has risen an appreciation and integration of multiple disciplines to tackle the complexities of the brain, and engineers have played a prominent role.

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Engineers have driven a number of advances in designing materials for materials, electronics, devices, and computing applications in the brain. For example, in the late 1990s, chemical engineer Robert Langer, along with co-investigator neurosurgeon Henry Brem, developed the first biodegradable polymer wafer system to deliver drugs to residual tumor cells in brain tumors, when implanted in the resected tumor cavity following surgery. Physicist and electrical engineer by training Edward Boyden is considered one of the leading innovators in neuroscience through the application of optogenetics, a technology which has enabled unparalleled spatial and temporal control over neuronal activity using light. There continue to be advancements in computing and device interfaces, and a number of resources to guide a reader interested in exploring these technologies for use in the brain. In this book, we bring together a diverse group of researchers from around the world who focus on developing and implementing engineered materials for understanding of the brain, and for diagnosis and treatment of brain disease. This book addresses application of these materials across scale, including past, present, and future efforts in engineering models of the blood-brain barrier, probing the parenchymal interface, developing sensors for brain function, generating microfluidic platforms for directing cell function, and tuning materials to target brain regions and cells of interest in a range of neurological diseases. Importantly, this book represents contributions from early career and mid-career researchers, who will be leading the next generation of scientists to engineer materials for neural applications. Seattle, WA, USA

Elizabeth Nance

Contents

Part I Engineering Neural Models and Materials 1

 Configurable Models of the Neurovascular Unit����������������������������������    3 Yash Mishra, Janire Saez, and Róisín M. Owens

Part II Probing Biological Underpinnings of Neurological Function and Disease 2

 Nano-Based Probes for the Brain Extracellular Environment������������   53 Jeremy R. Filteau, Brendan P. Butler, Nels Schimek, and Elizabeth Nance

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Engineered Materials for Probing and Perturbing Brain Chemistry��������������������������������������������������������������������������������������   89 Andrew T. Krasley, Chandima Bulumulla, and Abraham G. Beyene

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 Microfluidic Devices for Analysis of Neuronal Development��������������  169 Miles D. Norsworthy and Martha U. Gillette

Part III Designing Therapeutic and Diagnostic Interventions for Neurological Disease 5

 Bioresponsive Nanomaterials for CNS Disease ������������������������������������  189 Julia A. Kudryashev, Marianne I. Madias, and Ester J. Kwon

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 Polymer-Mediated Delivery of CRISPR-­Cas9 Genome-Editing Therapeutics for CNS Disease����������������������������������������������������������������  229 Shoaib Iqbal, Angela Alexander-Bryant, and Jessica Larsen

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Multifunctional Polymeric Nanocarriers for Targeted Brain Delivery��������������������������������������������������������������������  259 Zhiqi Zhang and Kyle J. Lampe

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 Theranostic Nanomaterials for Brain Injury����������������������������������������  307 Hunter A. Miller and Forrest M. Kievit

Index������������������������������������������������������������������������������������������������������������������  351

Part I

Engineering Neural Models and Materials

Chapter 1

Configurable Models of the Neurovascular Unit Yash Mishra

, Janire Saez

, and Róisín M. Owens

Abstract  The blood-brain barrier (BBB) restricts the paracellular diffusion of compounds into and out of the brain and is extremely important for maintaining brain homeostasis and proper neuronal function. The BBB is composed of multiple cell types arranged in a complex 3D structure that enables sophisticated interplay between endothelial cells, pericytes, glial cells, and neurons. This complex is known as the “neurovascular unit” (NVU). Several neuropathological conditions, including dementia and stroke which are two of the top ten causes of death worldwide, are associated with BBB dysfunction, but there is still often a lack of understanding of the underlying mechanisms and causal relationships. Representative, translatable preclinical models of the NVU are needed to facilitate a better mechanistic understanding of the relationship between BBB dysfunction and neurological diseases, which is critical for developing new treatments. They have the potential to be used to test the efficacy, toxicology, and delivery of drugs. A plethora of factors such as cell origin, co-culture, shear, substrate stiffness, substrate biochemical composition, 3D structure, etc. greatly affect BBB permeability and thus NVU integrity. Advancements in materials science, microfluidics, and fabrication techniques, for example, soft lithography and 3D bio-printing, have enabled increased control of pertinent factors leading to countless different configurations. Hence, the field has seen a gradual movement away from static models, where non-human cells are cultured in 2D in relatively rigid semi-permeable membranes made of PET or polycarbonate, toward dynamic organ-on-a-chip systems where multiple human NVU cell

Y. Mishra · R. M. Owens (*) Department of Chemical Engineering and Biotechnology, Cambridge, UK e-mail: [email protected] J. Saez Department of Chemical Engineering and Biotechnology, Cambridge, UK Microfluidics Cluster UPV/EHU, BIOMICs Microfluidics Group, Lascaray Research Center, University of the Basque Country UPV/EHU, Leioa, Spain Basque Foundation of Science, IKERBASQUE, Bilbao, Spain © The Author(s), under exclusive license to Springer Nature Switzerland AG 2022 E. Nance (ed.), Engineering Biomaterials for Neural Applications, https://doi.org/10.1007/978-3-031-11409-0_1

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types are co-cultured under physiological shear in 3D tubular structures that recreate in vivo architecture using biomaterials found in native tissue with representative biomechanical properties and biochemical composition. Furthermore, models have been significantly enhanced by the incorporation of analytical technologies, including live cell imaging and TEER measurement, with further improvement possible using bioelectronics. However, several challenges still remain and applications in fields such as neuropsychiatry are still scarce. This chapter aims to discuss the importance and evolution of in vitro NVU models, key considerations, various configurations that have been developed, their main features, and the variety of fabrication methods that have been used to create them. Keywords  Blood-brain barrier · Neurovascular unit · Tight junction proteins · Microfluidic · Trans-endothelial electrical resistance · Electrospinning · Lithography · 3D printing · Organ-on-a-chip · Multicellular · Bioelectronics

1 Introduction The blood-brain barrier (BBB) restricts the paracellular diffusion of compounds into and out of the brain and is extremely important for maintaining brain homeostasis and proper neuronal function (Cecchelli et al., 2007). Specifically, brain endothelial cells form a continuous endothelium that separates the cerebral tissue from the bloodstream and are specialized in the regulation of ion and molecule diffusion between the bloodstream and the brain to ensure brain tissue composition stability (Abbott et al., 2010). This is possible because brain endothelial cell membranes are lined with specific transporters, thus making the BBB a metabolic barrier (Oldendorf, 1971). While influx transporters facilitate the movement of water-soluble molecules abundantly needed by the CNS 10–100  times faster than predicted based on physicochemical characteristics, efflux transporters remove waste molecules from neural tissue and repel neurotoxic agents coming from the blood (Abbott et al., 2010; Oldendorf, 1971). Drug delivery into the brain is challenging due to the presence of drug-transporter P-Glycoprotein (P-Gp), which rejects most large drugs (>400  Da) (van der Helm et al., 2016). Unlike peripheral vasculature, BBB endothelial cells are non-fenestrated and exhibit low pinocytotic vesicle concentration to perform as a barrier with selective transportation (Bauer et al., 2014). Extensive additional information about the molecular composition, function, and organization of the BBB can be found in literature (Abbott et al., 2010; Bauer et al., 2014). In the past, brain cells and cerebral blood vessels were considered completely distinct entities, such that it was generally assumed that unless blood flow to the brain was critically compromised, there was little relation between neurons and vasculature leading to a rigid separation between “neurodegenerative diseases” like Alzheimer’s disease (AD) and cerebrovascular diseases like stroke, which were considered mutually exclusive and unrelated in mechanism (Iadecola, 2017). Over the last 25 years, experimental data of cerebral blood flow dynamics have shown significant intercellular communication between neurons,

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glia, and brain vasculature cells, thereby implying that the BBB functions within the greater context of a multicellular neurovascular unit (NVU) rather than independently (McConnell et al., 2017). The concept of the NVU was formalised in 2001 at the first Stroke Progress Review Group meeting of NIH’s National Institute of Neurological Disorders and Stroke of the (Iadecola, 2017). Several neuropathological conditions are associated with BBB dysfunction, but there is still often a lack of understanding of the underlying mechanisms and causal relationships. This includes Parkinson’s and Alzheimer’s diseases, epilepsy, and amyotrophic lateral sclerosis (Cai et  al., 2018; Modarres et  al., 2018). Dementia, most commonly caused by Alzheimer’s disease (AD), is ranked seventh among the biggest causes of death worldwide, with over 1.5 million victims each year (WHO, 2020). The connection between the BBB and AD pathogenesis has been well reported (Cai et al., 2018). Changes in the paracellular permeability of endothelial cells have been associated with the accumulation of beta-amyloid (Aβ), which is heavily implicated in AD pathology, and to further exacerbate the problem, Aβ peptides have been shown to impair endothelial cell function (Zenaro et al., 2017). Receptors associated with the transport of Aβ across the BBB have been reported to be impaired in the presence of Aβ peptides (Kuhnke et al., 2007; Park et al., 2014; Zenaro et al., 2017). While the alteration in BBB function is a key progression point in AD pathogenesis, it is still unclear what mechanism connects the two events. Strokes are the second biggest cause of death, the third leading cause of disability, and a leading cause of depression and dementia (Johnson et al., 2016; WHO, 2020). One of the pathophysiological features of stroke is disruption of the BBB, which significantly contributes to brain injury, subsequent neurological impairment, and mortality (Abdullahi et  al., 2018). BBB dysfunction, characterized by structural disruption and increased permeability, is a prominent pathological characteristic of both ischemic and hemorrhagic stroke and is associated with poor prognosis (Jiang et al., 2018). BBB disruption facilitates injury progression and increases the risk of hemorrhage, predicting poor patient outcome and limiting the use of common treatments (Jiang et al., 2018). Homeostasis of the brain is disrupted, leading to cerebral edema, and injury is exacerbated due to inflammatory responses caused by infiltrating materials (Jiang et al., 2018). It is important to note that stroke and AD are just two examples of widely studied brain diseases where BBB dysfunction is a pathological hallmark and that BBB dysfunction plays a role in the pathogenesis of most neurological diseases; however, much more research is needed for many other diseases, such as neuropsychiatric disease and diseases affecting early developmental. Representative, translatable preclinical models of the BBB are needed to facilitate better mechanistic understanding of the relationship between BBB dysfunction and neurological diseases, which is critical for developing interventional strategies, facilitating long-­term functional recovery, and reducing recurrence as well as incidence. This chapter aims to discuss the importance and evolution of in vitro NVU models, key considerations, various configurations that have been developed, their main features, and the variety of fabrication methods that have been used to create them. It is not an extensive list of all in vitro models of the NVU.

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1.1 Structure of the NVU 1.1.1 Cell Types and Function The BBB is composed of multiple cell types arranged in a complex 3D structure that enables sophisticated interplay between endothelial cells, pericytes, glial cells, and neurons (Cecchelli et al., 2007). This complex is known as the “neurovascular unit” (NVU), schematically represented in Fig. 1.1 (Zenaro et al., 2017). The glial cells are astrocytes, microglia, and oligodendroglia (Yu et al., 2020). Capillary endothelial cells form the only physical barrier separating the brain from blood, thus creating the BBB (Rahman et al., 2016). Human brain endothelial cells are characterized by specific endothelial markers, such as von Willebrand factor (vWf), BBB transporter proteins, and the formation of functional tight junctions (TJ) comprised of proteins like claudin-5 and Zona Occludin- 1 (ZO-1), which restrict paracellular permeability (Rahman et  al., 2016). Endothelial cells in the human brain are estimated to make up approximately 30% of its nonneuronal cells, and the glia to endothelial cell ratio is 2:1 (von Bartheld et al., 2016). In the central nervous system (CNS), pericytes are present in a 1:1 ratio with endothelial cells, forming the BBB (Caporarello et al., 2019). The highest coverage of pericytes is found in the brain, although they wrap around microvascular endothelial cells throughout the body (Umehara et al., 2018). They play a vital role in various brain functions, including BBB development and stabilization, control of cerebral blood flow, tissue regeneration, and brain inflammation (Umehara et al., 2018). Inflammatory stimuli can cause brain pericytes to acquire a “reactive” state, which is characterized by increased phagocytic phenotype, the ability to migrate, and the production of numerous cytokines and chemokines. This can cause BBB disruption due to their loss at the BBB (Umehara et al., 2018). Pericytes not only provide structural support to the BBB but also strongly regulate BBB properties along with astrocytes by secreting various mediator molecules affecting transporters and TJ protein expression (Armulik et al., 2010; Sweeney et al., 2016). Histological data suggests a 1:1 ratio of glia to neurons in the entire human brain (von Bartheld et al., 2016). Astrocytes are the most abundant glial cells, accounting for approximately 20% to 40% of the total number of brain cells (von Bartheld et  al., 2016). Distinguished by their expression of Glial Fibrillary Acidic Protein (GFAP), human astrocytes are typically stellate cells with processes (Vasile et al., 2017). Their many roles include neurotransmitter uptake and recycling, promoting neuronal survival, and contributing to synapse formation and synaptosomes engulfment (Vasile et al., 2017). Protoplasmic astrocytes’ end-feet contact blood vessels, and astrocytes express purinergic P2Y receptors, K+ channels, and the water-­channel protein aquaporin-4 (AQP4) indicating their extensive involvement in brain homeostasis through the BBB (Cecchelli et al., 2007; Vasile et al., 2017). Moreover, they can express TJ proteins like Occludin and ZO-1 and play a role in BBB formation and function, via complex TJ, specialized enzyme systems, and transporters (Cecchelli et  al., 2007; Morgan et  al., 2018). Furthermore, astrocytes secrete

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Fig. 1.1  Structural diagram of the NVU as well as tight and adherens junctions. Endothelial tubes are surrounded by pericytes and astrocyte end-feet. Tight junctions (mainly consisting of claudin, occludin, and adhesion molecules) and adherens junction (mainly composed of Vascular Endothelial (VE) cadherin) connect adjacent endothelial cells to form the barrier. (Reprinted from Yu et al. 2020)

pro-­inflammatory mediators to increase BBB permeability and leukocyte infiltration during inflammation (Argaw et  al., 2009). Microglia are the only dedicated immune cells in the brain parenchyma, constituting 5–10% of total brain cells (Li & Barres, 2018). Their development, structure, and functions have already been extensively reviewed (Alekseeva et  al., 2019; Nayak et  al., 2014; Wake et  al., 2011). Oligodendrocytes are the other main remaining type of glia, and their central role is to generate myelin, which is an extended membrane from the cell that wraps tightly around the axons of neurons to help facilitate brain signaling (Kuhn et al., 2019).

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Since they do not have a prominent role in BBB function or its current in vitro models, further discussion of oligodendrocytes is beyond the scope of this chapter, but more information on them can be found in dedicated, extensive reviews (Baumann & Pham-Dinh, 2001; Kuhn et al., 2019; Simons & Nave, 2016). The average human brain has around 100  billion neurons (Zhang, 2019). A mature neuron performs the critical function of processing and transmitting signals along its long, feathery, branching filaments called dendrites to other cells through synapses, which are complex membrane junctions or gaps (Zhang, 2019). Hence, they express specific structural, mature neuronal markers such as βIII-tubulin, Microtubule-Associated Protein-2 (MAP2), Neurofilaments (NF), NeuN, and synaptic genes (Kovalevich & Langford, 2013). They transmit biochemical signals through neurotransmitters and thus express receptors and enzymes for neurotransmitters, such as acetylcholine, dopamine, and adrenaline (Zhang, 2019). They also carry out electrochemical signaling using ions and are electrophysiologically active, possessing voltage-gated ion channels for Na+, K+, and Ca2+ (Zhang, 2019). 1.1.2 Extracellular Matrix Microenvironment BBB endothelial cells receive biochemical and mechanical cues from the noncellular surrounding microenvironment, in particular from blood flow induced shear stress and the extracellular matrix (ECM) (Gray & Stroka, 2017). Structurally, the ECM is a colloid constituted of a fibrous network of proteins entangled in a specific 3D configuration able to retain soluble factors secreted by surrounding cells to form diffusion gradients. The elastic modulus of the brain in vivo is approximately 500 Pa (Levental et al., 2007). The advancement of technologies for observing local matrix physical properties has helped in directly linking changes in the ECM, including in mechanical properties such as stiffness, to BBB dysfunction (Lepelletier et  al., 2017; Liu et al., 2017; Rempe et al., 2018). This suggests the importance of physical ECM properties and cell-matrix remodeling in the regulation of BBB integrity. ECM composition is altered upon BBB disruption and directly impacts disease progression (Baeten & Akassoglou, 2011). A basement membrane (BM) is an ECM associated with cell surfaces, which supports epithelial and vascular endothelial cells by forming a sheetlike structure (Baeten & Akassoglou, 2011). Four glycoprotein families mainly make up the BBB BM: laminins, collagen IV, nidogens, and heparan sulfate proteoglycans, including perlecan and agrin as illustrated in Fig. 1.2 (Baeten & Akassoglou, 2011; Roberts et al., 2012; Thomsen et al., 2017). Laminin forms a first polymer network through self-assembly initially and is then connected to a secondary penetrating and stabilizing polymer network of collagen IV by nidogen and heparin (Baeten & Akassoglou, 2011; Thomsen et al., 2017). The BBB BM has a thickness varying between 20 and 200 nm (Buxboim et al., 2010; Sen et al., 2009). The origin, organization, and roles of the various BM proteins are summarized below (Box 1.1):

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Blood

Endothelial Cells

BM ECM

Pericyte

Astrocyte End-feet Brain Parenchyma

Claudin

Occludin

ZO-1

Cingulin

JAM

Cadherin

Laminin Collagen IV Perlecan Fibronectin Integrins Dystroglycan

Actin

Fig. 1.2  Schematic diagram illustrating the BBB TJ, ECM, and BM. (Reprinted with permission from Roberts et al. 2012)

1.2 Importance of In Vitro Models Over 90% of drugs that pass animal testing fail to make it to market due to high toxicity levels and/or low therapeutic efficacy (Van Norman, 2019a). This failure rate is even higher at over 99% for drugs treating a neurological condition such as AD (Cummings, 2018). Failures to translate promising animal therapeutic studies to successful clinical trials have raised questions over potential species differences (AKHTAR, 2015; Van Norman, 2019b). Animal models do not express a number of human-specific proteins and protein isoforms that may be pertinent to development and disease physiopathology (Kovalevich & Langford, 2013). The development of complex, accurately representative, human-based models of the BBB is essential to improve the success rate of newly developed therapeutic strategies, reducing both the time and resources required. There is currently no translational model of the NVU reproducing all its structural and functional key features, but a variety of models which have recreated several aspects of the BBB are discussed in Sect. 4. Additionally, the development of novel therapeutic

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Box 1.1: Brief Overview of BM Proteins • Collagen IV: Expressed by endothelial cells, pericytes, and astrocytes, collagen IV helps retain laminin, nidogen and perlecan, and stabilize the structure of the BM (Allt & Lawrenson, 2001; Kose et al., 2007; Pöschl et  al., 2004; Tilling et  al., 2002). It also affects BBB integrity (Tilling et al., 1998). • Laminin: Laminin binds to collagen and plays a role in cellular polarization, claudin-5 localization, and astrocyte end-feet anchoring through dystroglycan (Tilling et al., 1998; Yurchenco et al., 2004; Yurchenco & Patton, 2009). It is also possibly involved in the inhibition of leukocyte migration and is expressed by endothelial cells, pericytes, and astrocytes (Allt & Lawrenson, 2001; Sixt et al., 2001). • Fibronectin: Fibronectin is transiently expressed by endothelial cells, pericytes, and astrocytes (Kose et al., 2007). It plays an important role in BM assembly and affects BBB properties and integrity (Risau & Lemmon, 1988; Tilling et al., 1998; Wang & Milner, 2006). • Nidogen: Nidogen is expressed by endothelial cells to stabilize BM structure by linking laminin and collagen IV and binding to other ECM proteins (Grimpe et al., 1999; Stratman et al., 2009; Yurchenco et al., 2004). • Agrin: Agrin is expressed by astrocytes and endothelial cells (Stone & Nikolics, 1995; Wolburg et al., 2009). It is likely involved in the anchoring of endothelial cells and astrocytes to the BM and BBB formation and function possibly through occludin and claudin-5 expression regulation (Barber & Lieth, 1997; Gesemann et al., 1998; Rascher et al., 2002). • Perlecan: Expressed by pericytes, perlecan helps regulate cell-cell interactions and stabilize blood vessels (Baeten & Akassoglou, 2011; Roberts et al., 2012).

strategies based on an in vitro model of the NVU requires technology that can accurately assess BBB function and structure in a reliable and dynamic manner.

1.3 BBB Characterization BBB integrity is usually assessed by either imaging its key components or through functional tests, such as permeability measurements, which quantify how much of certain compounds or ions are able to pass through the BBB over a period of time. Due to methodological limitations, the vast majority of methods (mostly optical) used to monitor in vitro BBB models do not represent all of its properties and are deficient in terms of their predictive capability, often consisting of static images, or isolated endpoint measurements with a large degree of inhomogeneity (Bickel, 2005).

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1.3.1 Expression of BBB Markers The barrier function and properties of the BBB depend on TJ proteins that form connecting strands between brain endothelial cells to protect the brain from fluctuations in plasma composition (Zobel et al., 2016). TJ proteins include claudin-5 and ZO-1, and their expression indicates BBB formation (Zobel et  al., 2016). Immunofluorescence staining of TJ proteins of an intact BBB reveals a typical, distinct pattern as illustrated in Fig. 1.3, where TJ proteins are localized near the boundaries between cells in a monolayer (Page et al., 2016). However, this pattern is not visible or is disrupted and irregular if a BBB is not formed or disrupted, so the impact of various compounds on the BBB can be studied using immunostaining (Page et al., 2016). The expression of TJ proteins can also be measured or verified using assays like RT-PCR, ELISA, and Western blots, but these techniques can only confirm TJ protein expression not TJ formation or function so their utility is limited. Other BBB markers include efflux transporters, such as the ATP-binding cassette (ABC) transporters, P-glycoprotein (P-gp), multidrug resistance associated protein

b-CATENIN

GLUT-1

CLAUDIN-5

OCCLUDIN

100mM

30mM

10mM

0mM

PECAM-1

Fig. 1.3  Cobalt-chloride (CoCl2) treatment impacts BBB integrity in an iPSC-derived in  vitro model. Immunocytochemistry micrograph pictures of the endothelial cell monolayers treated with different CoCl2 concentrations show irregular patterning in TJ proteins (claudin-5 and occludin) under 30  μM treatment as marked by asterisks and complete disruption at 100  μM.  Scale bar = 20 μm. (Reprinted with permission from Page et al. 2016)

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(MRP), and breast cancer resistance protein (BCRP), which protect the brain by actively transporting molecules leaked from the blood into the brain back into the capillary lumen (Hoosain et al., 2015; Park et al., 2019). Their expression can be verified using the same techniques as TJ proteins. 1.3.2 Permeability Assays Permeability assays can be used to not only assess BBB integrity but also study drug transport and metabolism (Sloan et al., 2012). To assess the integrity of endothelial cell TJs and thus the BBB, low-molecular-weight, control compounds that are added to one (donor or “blood”) side of the endothelial cell monolayer and samples are removed from the other (receiver or “brain”) side or in some cases both sides of the cells over the course of 1 h (Sloan et al., 2012). Experiments must be carried out under appropriate conditions to ensure the maintenance of healthy cells throughout the course of the experiments, and for studies lasting longer than an hour, transport media must maintain isotonicity, TJ integrity, physiological pH (7.4), and sufficient nutrient levels (Sloan et al., 2012). The amounts of the compound of interest in the samples collected are then quantified using analytical techniques such as scintillation counting or fluorescence spectrophotometry (Sloan et al., 2012). This is followed by calculations of the percent transported or the apparent permeability coefficient of the compounds of interest (Sloan et al., 2012). Compounds like fluorescein and radiolabelled sucrose are commonly used for this purpose because their ability to permeate falls within a known, defined range for an intact, functioning BBB, so they can be used to accurately assess the model’s BBB integrity and can be used as controls for validating the transport of other compounds of interest (Sloan et al., 2012). Once an in vitro model’s BBB integrity has been experimentally validated using a control compound, it can then be used to determine transport properties of drugs or other compounds using the same procedure (Sloan et al., 2012). However, several factors must be considered, including sample-volume requirements, the labeling of the compounds of interest (fluorescently or radioactively) for subsequent detection, limits of detection, the compatibility of the materials used to make the model with the compound and chosen analytical technique, etc. (Sloan et  al., 2012). Permeability assays are versatile functional assays that have been used for a plethora of configurations and combinations, including hanging cell culture inserts (Bayir et al., 2019; Ito et al., 2019; Lippmann et  al., 2014; Marino et  al., 2018), microfluidic devices (Gerigk et  al., 2021; Katt et al., 2018; Sloan et al., 2012; Wevers et al., 2018), and even with other analytical systems such as liquid chromatography/mass spectrometry to detect and measure the quantity of substance P transported across the BBB (Sloan et al., 2012). Due to their importance for brain homeostasis, efflux transport activity is a key characteristic of BBB models that can be used to not only evaluate the predictive capabilities of BBB models but also screen for drugs that are subject to active transport; however, most current in vitro BBB models are not very robust in this regard, and results often depend on the drug of interest (Neumaier et al., 2021). Therefore,

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preliminary studies must be carefully carried out to confirm that transporter function is present under physiological conditions and evaluate if the BBB transporters can replicate features of in vivo transport before in vitro efflux studies (Erickson et al., 2020). P-gp is a membrane transporter of the ABC superfamily that plays a dynamic role in controlling the bioavailability of orally administered drugs for treating brain disorders (Hoosain et al., 2015). To assess the activity of a transporter like the P-gp efflux transporter in an in vitro BBB model, the transcytosis of known P-gp substrate molecules, such as rhodamine 123 and DiOC240, and drugs of interest should be measured with and without treatment with a known P-gp inhibitor, such as verapamil (Park et al., 2019). In contrast to static hanging cell culture insert systems, in vitro BBB models with functional P-gp efflux pumps should exhibit significantly higher substrate molecule permeability when the P-gp transporter is blocked by its inhibitor as demonstrated by a microfluidic BBB chip (Park et al., 2019). In vitro BBB models more accurately reflect efflux of compounds from the parenchymal side of the BBB back into the luminal side if they are more representative and incorporate features such as fluid flow, so newer microfluidic-based dynamic models that closely mimic in  vivo microcirculatory environments successfully reproduce in vivo findings and BBB characteristics (Moya et al., 2020; Neumaier et al., 2021; Park et al., 2019). Additionally, other factors that lead to more physiologically representative efflux transporter activity include co-culture with various cells of the NVU and the use of appropriate types of cells, as human iPSC-derived BBB models correlated more strongly with in vivo human BBB efflux transporter activity than rat BBB models (Ohshima et al., 2019; Strazielle & Ghersi-Egea, 2015). 1.3.3 Trans-endothelial Electrical Resistance The measurement of ion flow across endothelial tissue, trans-endothelial electrical resistance (TEER), is a widely used and well accepted in vitro method for assessing barrier integrity (Srinivasan & Kolli, 2019). It is label-free and directly measures a property of the cell layer, rather than indirectly measuring the permeability of tracer molecules or control compounds which do not always correlate with changes in permeability to ions (Srinivasan & Kolli, 2019). Although the TEER of a human BBB in vivo has not been directly determined, it is widely accepted that the mammalian BBB in vivo characteristically has high TEER values well above 1000 Ω cm2 (Weksler et al., 2013). The ohmic resistance of the barrier tissue is calculated after passing an alternating current between electrodes on either side of the endothelial cell layer and measuring the voltage drop across it (Raut et  al., 2021). The TEER value is then calculated by subtracting the resistance of the barrier tissue from the initial background value of freshly seeded insert samples (Raut et al., 2021). In the circuit, the current can flow through the junctions between cells, which is the paracellular route, or through the cell membrane of the cells – the transcellular route (Srinivasan et al., 2015). TEER reflects the ionic conductance of the paracellular pathway (Srinivasan et al., 2015). More information on these calculations can be found in Fig. 1.4.

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Fig. 1.4  Schematic illustration of TEER determination for brain endothelial cells modeling the blood-brain barrier. (a) The equivalent circuit of a cell monolayer, where the orange dotted line depicts TJs and the paracellular resistance (Rparacellular) through them primarily dominates the TEER (RTEER) value, while the transcellular pathway (Rtranscellular, Ccell) and the properties of the electrode (Relectrode, Celectrode) also affect the recorded signal (impedance spectrum). (b) Representative impedance spectrum of a BBB cell monolayer, which shows the variation in opposition to current flow when voltage is applied over an extended range of frequency values. The α-band contains RTEER, the capacitance of the cell layer (Cc), and the electrode polarization (Ce), while the β-band is dominated by the resistance of the medium (Rm) and the resulting system capacitance. (Reprinted with permission from Vigh et al. 2021)

BBB disruption or dysfunction generally correlates with lower TEER and greater permeability as ions can leak through the barrier tissue (Williams-Medina et  al., 2021). Commercially available TEER measurement systems, such as the EVOM® (World Precision Instruments (WPI), Sarasota, FL, USA) and CellZscope (Nano Analytics, Münster, Germany), are widely used (Raut et al., 2021). However, simple volt-ohmmeter systems, such as the EVOM, are not automated, and commercially available automated systems like the CellZscope can only be used with static hanging cell culture inserts (Raut et al., 2021). Furthermore, TEER measurements using existing technologies can have significant fluctuations due to incorrect alignment between electrodes and inserts, temperature and/or volume variation of the medium during measurement, etc. (Raut et al., 2021). Hence, there is a need for more robust TEER measurement systems, preferably conducive to automation and high-­ throughput experiments.

2 Key Factors Affecting NVU Models 2.1 Cells The origin and nature of the brain endothelial cells used in an in vitro NVU model and co-culturing them with other cell types can have an immense impact on the representativeness and integrity of the BBB. A co-culture of rat brain endothelial cells (RBECs) and primary neonatal rat astrocytes, for instance, results in a stable BBB model that can achieve TEER >600 Ω cm2 (Abbott et al., 2012). Porcine brain

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endothelial cells give a mean TEER of 800 Ω cm2 without co-culture (Patabendige et al., 2013). However, acquiring and using primary cells can be extremely challenging and/or expensive, and animal-derived cells may not fully represent human in vivo physiology (Geraghty et al., 2014; José Barbosa et al., 2015). Using human amniotic fluid-derived Induced Pluripotent Stem Cells (iPSCs) to create a model with endothelial cells, neurons and astrocytes resulted in TEER values over 1000  Ω  cm2 (Ribecco-Lutkiewicz et  al., 2018). The complexity of stem cells, as well as the added challenges and time requirements associated with working with these cells, makes such models difficult to reproduce and widely use (Lipps et al., 2018; McKee & Chaudhry, 2017). Regardless of the nature or origin of the endothelial cells, co-culturing with other types of cells found in the NVU has widely shown to improve BBB integrity. The co-culture of an immortalized cell line, human cerebral microvascular endothelial cells (hCMEC/D3), with astrocytes or pericytes increased TEER by about 1.5-fold after 5 days compared to a purely endothelial cell culture (Helms et  al., 2016). The culture of human primary astrocytes, primary pericytes, and iPSC-derived neural stem cells was shown to improve human iPSC-derived brain endothelial cells’ barrier integrity by increasing the secretion of transporters (Appelt-Menzel et  al., 2017). Moreover, the TEER of an iPSC-derived BBB model has more than tripled from 1040 Ω cm2 to 3610 Ω cm2 upon co-culture with pericytes, astrocytes, and neurons (Lippmann et al., 2014). Therefore, co-culturing is very important because cells of the NVU beyond the endothelial cells contribute significantly to BBB formation and maintenance as previously mentioned. This is mainly through the secretion of soluble factors into the media and ECM proteins and direct cell-cell interactions in some cases (Baeten & Akassoglou, 2011; Wong et al., 2013). Despite there being no in vitro studies specifically focused on the impacts of biological sex on the BBB, several studies have revealed that BBB models derived from iPSC lines from male subjects had higher permeability and thus lower barrier strength compared to those from premenopausal women (Weber & Clyne, 2021). Higher expression of higher platelet endothelial cell adhesion molecule-1 (PECAM-1 or CD31), a TJ protein, in male cell lines indicates that other TJ proteins are likely responsible for the tighter BBB of the female cell lines (Lippmann et al., 2012). Other studies also show higher TEER values for female-derived brain endothelial cells compared to their male counterparts (Hollmann et al., 2017). On the contrary, one study reported similar values for both sexes, but its accuracy may be limited because they had 26 biological replicates for the male cell line and only 3 for the female (Qian et al., 2017). While sex may be a significant factor affecting the BBB, large differences in TEER values have been observed for similar, all-male iPSC lines because a variety of other factors, such as cell tissue source, differences in the donor’s age, and differentiation or culture conditions also contribute to the variation (Weber & Clyne, 2021). More information on the impact of sex differences on BBB shear stress response, metabolism, and vascular function can be found in literature (Weber & Clyne, 2021).

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2.2 Biochemical Cues Numerous substances have been integrated into in vitro NVU models because they provide biochemical cues that improve BBB formation and thus representativeness. These compounds are usually either soluble factors in the media or BM components that are used to coat or make cell culture substrates. For instance, the addition of retinoic acid to culture media increased the TEER of iPSC-derived models by over 1000 Ω cm2 (Lippmann et al., 2014). Additionally, the barrier properties of HBMEC/ciβ, a brain microvascular endothelial cell line, are enhanced by hydrocortisone, which is often part of BBB culture media, by promoting mesenchymal-to-endothelial transition-like effects (Furihata et  al., 2015). Other compounds which have enhanced or protected the BBB include imiquimod (TLR7 ligand) (Johnson et al., 2018), interferon-λ [also known as type III interferon or interleukin-28 (IL-28)/IL-29] (Lazear et al., 2015), U0126 (antiglycation agent) (Tóth et al., 2014), aminoguanidine (Tóth et al., 2014), etc. On the contrary, BBB disruption occurs in response to cobalt chloride (Page et al., 2016), methylglyoxal (Tóth et al., 2014), and pro-inflammatory stimuli, including lipopolysaccharide and tumor necrosis factor-α (Lazear et al., 2015). ECM proteins contribute to BBB formation and function through both biochemical signaling and mechanical cues, which are discussed in the next section. Better BBB formation was observed when brain endothelial cells were grown on the decellularized ECM of endothelial cells or glial cells previously grown on the same substrate (Zobel et al., 2016). The importance of ECM proteins produced by cells like pericytes has been shown by studies where TEER tripled when the barrier was formed on pericyte-secreted ECM compared to endothelial-secreted ECM (Zobel et al., 2016). ECM proteins like perlecan improve not only TJ protein expression but also cell adhesion through the provision of attachment sites (Maherally et al., 2017). On the other hand, the effect of some ECM proteins like agrin on TEER is not fully understood and appears to vary depending on the origin of the cells (Katt et  al., 2018; Maherally et al., 2017).

2.3 Substrate Mechanical Properties and Structure The dynamic shear elastic modulus or “stiffness” of the brain in vivo is approximately 500 Pa (Levental et al., 2007). 3D models using hydrogels (which are discussed in more detail in Sect. 3.4) to mimic native biomechanical stiffness have resulted in improved BBB formation and more representative models (Gray et al., 2019; Grifno et  al., 2019). An increase of mechanical tension on cell adhesion receptors regulated by ECM stiffness has been hypothesized to be a crucial cue governing capillary morphogenesis during development (Ingber, 2002). Barrier function modulation by substrate stiffness and its underlying molecular mechanisms have been reviewed in depth (Karki & Birukova, 2018). Increasing substrate

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pore density and reducing pore size also improve cell-cell interactions and barrier formation (Casillo et al., 2017). Traditional 2D cell culture, where cells are grown as a monolayer on a flat substrate, has been prevalent for over 100 years; however, 2D cell cultures are not representative of the natural microenvironments of the cells because they offer unnatural growth kinetics and cell attachments (Joseph et  al., 2018). Increasingly, 3D cell cultures, which better mimic in vivo tissue physiology, are being used because the growth of cells in their native 3D architecture allows better cell-cell contact, intercellular signaling networks, and developmental processes, thus resulting in differentiation into more complex structures as well as protein expression patterns and intracellular junctions that are similar to in  vivo states (Joseph et  al., 2018). Therefore, 3D structure is an important factor in determining how representative an in vitro model is in addition to substrate mechanical properties.

2.4 Fluid Flow Shear, which is stress that is applied in parallel or tangent to the face of a material usually by fluid flow, has been recognized as an important factor for inducing a mature BBB phenotype and controlling BBB integrity by adjusting TJ expression (Cucullo et al., 2011). Since vascular endothelial cells are directly exposed to blood flow of approximately 6 to 12 nL min−1 in brain capillaries around 10 μm in diameter, they experience shear stress ranging from 10 to 20  dynes  cm−2, which also plays a critical role in vascular remodeling and homeostasis (Kaisar et al., 2017). Shear stress exerts a mechanical strain and pressure effects on cells leading to the rearrangement of cell morphology and enhanced transfer of small molecules such as CO2, which reduces cell growth to promote differentiate (Elbakary & Badhan, 2020). The introduction of flow-based shear stress increased the TEER of hCMEC/ D3 from less than 100 Ω cm2 to over 1000 Ω cm2 (Cucullo et al., 2007). The effects of shear on the BBB have been extensively documented (Gray & Stroka, 2017). Static in vitro BBB models without fluid flow do not accurately reproduce in vivo conditions of nutrient flow due to the accumulation of substances near the basal membrane of cells which affect concentration gradients and thus the speed at which substances are transported across the BBB in either direction because the functioning of various BBB transporters is dependent on the surrounding concentration gradients (Rusanov et  al., 2015). Although reducing perfusion flow rates did not significantly alter the BBB permeability of adult female Sprague-Dawley rats, the transport of insulin and K+ greatly reduced at half and quarter flow (Hom et  al., 2001). Hence, reduced flow may compromise BBB transport process and interfere with ion homeostasis (Hom et al., 2001). A dynamic perfusion-based blood-brain barrier model revealed that flow in the basolateral side of cells growing on a porous membrane, mimicking human brain interstitial flow, enhances the transfer of small molecules such as oxygen and CO2, across the porous membrane, due to the pressure differential created (Elbakary & Badhan, 2020). An increase in dissolved CO2

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concentrations can reduce intracellular pH, thus impacting cell metabolism and reducing cell growth rates (Elbakary & Badhan, 2020). In static systems, such as hanging cell culture insert setups (discussed in Sect. 4.1), the metabolic use of oxygen and glucose is mostly anaerobic and thereby adversely affected because the cells adapt to chronic hypoxic conditions, whereas endothelial cells in dynamic models with gas permeant tubing and fluid mobility are exposed to physiologically relevant oxygen levels similar to blood in vivo (Williams-Medina et al., 2021). In vitro models incorporating fluid flow recapitulate in  vivo conditions more accurately than static models, thereby significantly affecting cell viability and metabolic activity (Williams-Medina et al., 2021). In addition to shear-driven differentiation, these are other likely factors that result in much lower permeability values for fluidic models compared to static systems indicating tighter and more representative barriers in dynamic conditions (Choublier et al., 2021).

3 Blood-Brain Barrier Model Fabrication Techniques 3.1 Electrospinning Electrospinning, which comes from a fiber-manufacturing method called electrical spinning, is a relatively easy and effective way of producing ultrafine fibers with micro- and nanometer-scale diameters that has seen a great growth in use for in vitro model fabrication in recent years (Zhang et al., 2005). As illustrated in Fig. 1.5, this process uses an electric field to convert droplets of a polymer solution into a fiber (Zhang et al., 2005). The external electrostatic field acts upon the surface charge of the polymer droplets to create tangential stress that deforms each droplet into a conical shape (Taylor cone), and once the electric field strength is great enough to overcome the surface tension, an elongated fluid jet is ejected from the apex of the cone toward a metal collector, where the solvent evaporates to yield fibers (Zhang et al., 2005). Fibrous and porous structures made of electrospun nanofibers with inherently high specific surface area and aspect ratio have a range of potential applications, including for drug delivery, wound healing, and in particular, scaffolds for tissue engineering (Zhang et al., 2005). The ECM of several native tissues and organs can be physically and structurally recreated by scaffolds with a high surface-area-to-­ volume ratio, highly porous microstructure, and interconnected pores favorable for tissue growth made by organizing extremely thin electrospun fibers into hierarchical structures (Zhang et al., 2005). In addition to being cost-efficient, electrospinning is also very versatile as it is compatible with a wide variety of inorganic materials, polymers, and their blends as well as the incorporation of biomolecules, additives, and cells in order to meet the requirements of numerous applications (Zhang et al., 2005). Both synthetic and natural polymers can be dissolved into a solvent or solvent mixture for electrospinning (Zhang et al., 2005). Hundreds of synthetic polymers

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Fig. 1.5  Schematic diagram and microscopy images breaking down the process of tissue engineering using electrospun scaffolds, which entails the electrospinning of polymer solutions using specialized equipment to create micro-/nanofibrous scaffolds conducive to cell adhesion and tissue growth for the formation of biomimetic BMs. (Reprinted with permission from Pazhanimala et al. 2019)

have been electrospun, with relative ease, including biodegradable polymers, including poly(lactic acid) (PLA), poly(ϵ-caprolactone), and (PCL)poly(lactide-co-­ glycolide) (PLGA) (Zhang et  al., 2005). Increasingly, natural biopolymers with greater biocompatibility, such as silk and collagen, are being used for electrospinning; however, they have generally poor processability and can be challenging to electrospin (Zhang et al., 2005). Human brain microvascular endothelial cell (HBMEC) monolayers had lower permeability after 21 days of culture on electrospun gelatin-based cell-degradable “biopaper” compared to conventional polyesther terephthalate (PET) membranes (Bischel et al., 2016). Furthermore, co-culturing the HBMEC with primary astrocytes with the different cell types on opposite sides of the membrane permitted the cells to get closer to each other and have greater cell-cell interactions due to a lower thickness of 4.5  μm compared to conventional membranes resulting in improved physicochemical features and the increased expression of genes with TJs and the ECM (Gaston et al., 2017). The properties of such electrospun gelatin mats, such as water degradability rates and fiber diameter, can be tailored by changing cross-­ linking time as well as the amounts of gelatin and cross-linkers like genipin or glutaraldehyde (Topuz & Uyar, 2017). PCL has relatively low biocompatibility and coating molecule adhesion, but this has been addressed by mixing it with polyethylene glycol (PEG) in an electrospun BBB model composed of endothelial cells, astrocytes, and pericytes (Pensabene et al. 2016). IPSC-derived endothelial cells and astrocytes have been co-cultured in nanofibrous meshes created by electrospinning poly(lactic-co-glycolic) (Qi et al., 2018).

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3.2 Lithography Lithography is a term used to describe a number of microfabrication techniques used to print patterns onto surfaces (Vladimirsky, 1999). Photolithography is a type of lithography that involves exposing a photosensitive material, called a resist, to light to form patterns on the chosen surface plate. A negative photoresist becomes insoluble and hard where exposed to light, while the rest of it is covered by a mask and can be washed away (Vladimirsky, 1999). The reverse holds true for a positive photoresist. SU-8 resin is a commonly used epoxy-based negative photoresist (Lemma et al., 2016). Photolithography has been used to create pores in stiff materials for semipermeable membranes with high porosity and the required, uniform distribution (Ma et al., 2005; Marino et al., 2018). Moreover, porous microtubules at the biomimetic scale of brain microcapillaries (10 μm) have also been created using two-photon lithography with SU-8 resin (Marino et al., 2018). The formation of mature TJs with low dextran permeability was observed when a rat brain endothelial cell line (bEnd.3) and human U87 glioblastoma cells where co-cultured in the microtubules (Marino et al., 2018). On the other hand, electron beam lithography (EBL) uses a focused beam of electrons to pattern a surface without the potentially complicated need for a mask, allowing smaller feature sizes even under 10 nm (Puryear III et al., 2020). A major disadvantage of EBL is its extremely low throughput (Puryear III et al., 2020), in contrast to track etching, which is explained in Sect. 3.4. EBL can be used to pattern silicon- or resin-based materials with very high pore densities (Ma et al., 2005). For example, pore densities as high as 50% were achieved in 0.5-μm-thin silicon substrates using EBL, facilitating the protrusion of astrocytic end-feet through the membrane of a BBB model (Ma et al., 2005). Soft lithography is the most commonly used fabrication technique for organs-on-­ chips (Puryear III et  al., 2020). Soft lithography is an easy to use, inexpensive method for molding a variety of soft elastomers into 3D structures (Puryear III et al., 2020). The biocompatibility, transparency, and low cost and gas permeability of polydimethylsiloxane (PDMS), a polymeric organosilicon compound, have made it one of the most often used material for soft lithography as illustrated in Fig. 1.6; however, its absorption of drugs, proteins, and other bioactive substances interferes with accurate analysis. This has been addressed by using other elastomers or mixing PDMS with different amounts of other materials and curing agents, which also adjusts mechanical properties (Puryear III et al., 2020). Replica molding, which is described in Fig. 1.6, is the most common implementation of soft lithography, and it has been used to create a variety of in vitro models (Puryear III et al., 2020). The fabrication of a typical organ-on-a-chip’s microfluidic channels involves the replica molding of PDMS using a photo-defined master mold (Kaisar et al., 2017). Silicones (such as PDMS) and glass are commonly used to build in vitro models because they are relatively inert, strong, and stable and can be used with microfabrication techniques like lithography in different ways; however, they are significantly stiff (MPa-GPa) and not gas permeable, so they make poor substrates for

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directly culturing cells (Adriani et al., 2017). As a result, they are often used to build the supporting structures of 3D in vitro models, assisting in the construction and maintenance of the 3D spatial organization of more biocompatible materials like hydrogels, which are the substrates that the cells directly grow on in biomimetic structures like the tubes of BBB vessels (Adriani et al., 2017). Soft lithography has been used to replicate complex in  vivo flow patterns and cell-cell interactions of multiple cell types, including mural cells, to elucidate their importance and roles in the BBB through the 3D reconstruction of intricate native tissue such as multiple channels and bifurcated vessels (Uwamori et al., 2017; Zheng et al., 2012).

3.3 3D Printing Despite being not very accessible and widely adopted, 3D bioprinting is a promising new technique that could be used for the construction of functional 3D NVU models with multiple cell types combined with appropriate biomaterials for ECM

Photoresist

UV Light

Mask

Silicon wafer PDMS

Plasma Treatment

PDMS Stamp

Bonding

Glass slide Fig. 1.6  Diagram illustrating a typical replica molding process using PDMS. Initially, photolithography is used to create a master mold by exposing photoresist to UV light through a mask to make the required pattern. A PDMS stamp is then made by filling the master mold with it and curing. The PDMS is then bonded to the base of the device (glass slide in this example) using plasma oxidation treatment, which plays a key role in the process as it also makes the surfaces hydrophilic and thus more biocompatible and suitable for cell adhesion as well as replicating in vivo fluid interactions (Puryear III et al., 2020). (Reprinted with permission from Puryear III et al. 2020)

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mimicry to examine neurovascular function and disruption at the molecular and cellular levels (Potjewyd et al., 2018). Bioinks are specialized pre-gelled biomaterials that can encapsulate cells in an environment that is suitable for their viability and growth and form solid constructs that have precise cell positioning to form appropriate, biomimetic interactive interfaces (Potjewyd et al., 2018). While collagen has inherent cell adhesion domains and is very suitable for making hydrogels, its physical properties, including relatively slow gelation times, render it a poor bioink, unless it is combined with other materials, such as gelatin, alginate, Matrigel, agarose, and methacrylate, which modify shear thinning properties to create an effective bioink for NVU cell culture. The application of 3D bioprinting for NVU in vitro modeling, its advantages and disadvantages, as well as bioink properties and composition have been reviewed in greater detail in (Potjewyd et al., 2018). Standard 3D printing has been used for fabricating a 3D printed frame for an array of cylindrical collagen microchannels where bEnd.3 cells reconstructed an array of brain microvasculature with low permeability and circular cross sections in vitro (Kim et al., 2015). This model was also used to study BBB disruption by mannitol and its subsequent recovery (Kim et al., 2015).

3.4 Other Fabrication Techniques for Creating BBB Models Track-etching is the standard technique used to make the semipermeable membranes made of stiff materials like polycarbonate and PET widely used for hanging cell culture inserts, despite a limited range of pore sizes possible, random pore distribution, poor pore coverage, and a high minimum thickness of 10 μm (Kim et al., 2014). Track-etching uses two steps to create pores in membranes – irradiation and chemical etching (Apel, 2001). Irradiation usually uses an accelerator to create an ion beam made up of fragments from the fission of heavy nuclei like uranium or californium from a nuclear reactor (Apel, 2001). Chemical etching is subsequently used for pore formation through the removal of the damaged zones by the ion beam using chemical dissolution by alcohols or alkali such as ethanol or propanol (Apel, 2001). Vapor-induced phase separation (VIPS) has been utilized for the creation of transparent, porous cellulose acetate scaffolds, which can serve as stable substrates, composed of a nondegradable, bioinspired material, suitable for cell culture, microscopy, and the development of BBB models (Marino et al., 2021). Solvent evaporation and polymer precipitation from polymer-solvent mixtures exposed to non-solvent vapors that induce thermodynamic instabilities creates membranes with porosity and optical and mechanical properties that can be tuned by changing the process conditions and the proportions of input materials (Marino et al., 2021). Thermal denaturation of a collagen hydrogel using a near-infrared laser beam created channels in a computer-controlled pattern in the gel, which can be altered by varying laser power and writing speed for channel diameters ranging from 9 to 180  μm (Hribar et  al., 2015). The thermal denaturation was stimulated by gold nanorods that absorb the near-infrared light and convert its energy into heat through

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the photothermal effect (Hribar et al., 2015). Bend.3 cells encapsulated in the collagen hydrogel underwent elongation and migration to form tubular vessels due to channel shape (Hribar et al., 2015). A templating method that uses zinc oxide, a material extensively used for microcrystalline manufacturing, can produce ultrathin PEG hydrogels with a random porous network similar to the interconnected pore networks of human BMs (Pellowe et al., 2017). Polymer synthesis entails pore creation using zinc oxide needles from two sacrificial zinc oxide layers surrounding the polymer solution and is followed by cross-linking of the bulk polymer and removal of the zinc oxide using hydrochloric acid (Pellowe et al., 2017). Fabrication methods depend on the biomaterials used, and new biomaterials can drive the development of tailored, new production processes. Bacterial cellulose scaffolds have been made by boiling bacterial cellulose from Gluconacetobacter xylinus for 20 min in freshly prepared 0.1 M NaOH and then with deionized water until the bacterial cellulose was bleached, followed by purification (Bayir et  al., 2019). Compared to standard hanging cell culture inserts, bacterial cellulose membranes made in this way produced more realistic human in vitro BBB model with significantly higher TEER values (Bayir et al., 2019). The bacterial cellulose membranes have a nanoporous ( 104 (Taratula & Dmochowski, 2010; Meier et  al., 2014). The second, chemical exchange saturation transfer (CEST), involves amplifying the radiofrequencies absorbed by the diamagnetic contrast agent through physically exchanging the energy with a larger pool of atoms in the surrounding solvent, allowing CEST agents to be imaged in millimolar concentrations (Ward et al., 2000; Van Zijl & Yadav, 2011).

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Fig. 3.8  Common gadolinium contrast agents used in MRI

Genetically encoded MRI probes are another variation of the previously discussed versions but with the potential for truly noninvasive endogenous production in animals. Metalloproteins are the nearest biosynthetic contrast agent to T1 and T2 contrast agents with both natural and bio-engineered being used as MRI sensors (Bartelle et al., 2016; Gossuin et al., 2002; Gillis & Koenig, 1987; Matsumoto & Jasanoff, 2013). Some engineered proteins and peptides have also acted as CEST agents, overcoming sensitivity limitations by organizing into a single biopolymer (Bar-Shir et al., 2015). 3.5.1 Functional MRI Functional magnetic resonance imaging (fMRI) involves collecting a series of brain images over a time period and then comparing the images for changes occurring due to brain activity. The signals detected by fMRI primarily occur from neural activity

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altering the flow of blood (Kim & Ogawa, 2012). Most fMRI imagining is derived from T2 changes impacting hemoglobin oxygenation (Kwong et al., 1992; Ogawa et al., 1992), while other techniques such as perfusion imaging (Detre et al., 1992) are derived from T1 changes caused from blood flow changes (Bartelle et al., 2016). fMRI depends on neurovascular coupling. Therefore, single-cell resolution is out of reach since capillaries in the brain are ~50 μm apart and many different cells of different types contribute simultaneously to fMRI data collected over given volumes. The temporal resolution is limited by phenomenology of blood flow, often delayed and broadened over several seconds compared to the sub-second measurements needed for neural imaging (Bartelle et al., 2016). Signal changes collected by fMRI are often quite small, and the technique is prone to false positives and negatives (Bennett et  al., 2009). To overcome these challenges, the field has shifted toward hybrid “molecular fMRI.” In molecular fMRI the noninvasive whole brain analysis of fMRI is coupled to the resolution and molecular specificity seen with optical functional imaging techniques. Rather than imaging vascular changes associated with blood flow in the brain, interactions between the molecular fMRI agent and substrate of interest are visualized. An early molecular fMRI probe was designed by Koretsky and coworkers that used manganese ions (Mn2+) to label stimulated neural populations. The paramagnetic Mn2+ can enter cells through calcium channels, accumulate, and act as an MRI contrast agent. Using Mn2+ generally requires stimulation from minutes to hours but can result in signal enhancements >  100% (Massaad & Pautler, 2011; Lin & Koretsky, 1997). The long stimulation time and even longer time required to return to baseline over a period of days limit this approach for dynamic functional imaging. Shapiro and coworkers sought to improve on the long times required by developing an MRI contrast agent based upon the same principles. They focused their efforts on evolving an MRI sensor from proteins that are magnetically active and have tunable binding pockets such as flavocytochrome P450-BM3. This cytochrome has a paramagnetic iron atom embedded in a solvent-accessible substrate-binding pocket that, through directed evolution of the protein, produced  a genetically encoded protein sensor that could sense dopamine selectively with a dissociation constant of ~1  μM (Shapiro et  al., 2010; Lee et  al., 2014a). Lee and coworkers injected this sensor directly into rat brains, and serial images were collected with intermittent delivery of electrical stimuli to the medial forebrain bundle. The images obtained resembled standard fMRI images; however, the map was of an individual neurochemical rather than neurovascular changes. Researchers were able to reveal a pattern of dopamine release that peaks at the core of the nucleus accumbens while studying reward stimulation in rats (Bartelle et al., 2016; Lee et al., 2014a). The same protein has also been engineered to sense serotonin and norepinephrine and is able to detect neurotransmitters at low micromolar concentrations (Shapiro et al., 2010; Brustad et al., 2012). To target neurotransmitters, Oukhatar and coworkers synthesized a crown ether cation-binding motif centered around gadolinium, which can chelate to a carboxylate group. This complex was used to bind glutamate, GABA, glycine, and zwitterionic neurotransmitters in micromolar concentrations in mouse brain slices

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(Oukhatar et al., 2015). Mishra and coworkers developed another glutamate sensor based on competitive binding to mGluR5 receptors that produced detectable changes at micromolar concentrations in vitro. They used these sensors to target astrocytes and were able to directly observe the receptor binding on the cell surface with optical imaging (Mishra et al., 2014). Of note, Cai and coworkers utilized endogenous glutamate as a sensor leveraging CEST signals. By utilizing the exchangeable amine protons on glutamate, they were able to perform in vivo sensing within a rat brain and rapidly extended it to human brains (Cai et al., 2012) with others also utilizing the technique (Davis et al., 2015). These signals are difficult to interpret due to contamination from pH effects, other metabolites contributing to the signals, varying concentrations between intercellular and extracellular space, and the difficulty in designing controls since the sensor is endogenous. But the data suggests that dynamic brain activation changes correlated to the glutamate signals could be detectable at low resolution on the timescale of minutes (Bednařík et al., 2015). Calcium MRI sensors are another area interest, and several have been developed over the years based upon gadolinium complexes or superparamagnetic iron oxide nanoparticles (Li et al., 1999; Atanasijevic et al., 2006; Angelovski et al., 2008). Progress on these sensors has been slow due to the difficulty of moving the bulky polarized sensors across the BBB. Some have been developed and deployed in vivo but only to measure extracellular calcium (Moussaron et  al., 2015; Okada et  al., 2018). Cell-permeable manganese-based MRI contrast agent, ManICS1-AM, was developed by Barandov and coworkers, which was modeled after cell-permeable optical probes and leveraged the AM ester-based approach for cell labeling and probe trapping (Barandov et al., 2019). Measurements taken in rat brains were consistent with analogous optical calcium sensors but allowed for deep brain imaging (Barandov et  al., 2019). Savić and coworkers develop a dynamic bismacrocyclic Gd3+ complex MRI calcium sensor which has an ethylene glycol bis (2-aminoethyl ether)-N,N,N′,N′-tetraacetic acid (EGTA) chelator. This agent selectively interacts with only Ca2+ ions in a reversible manner. With this probe, they were able to explore rat brains with submillimeter spatial and second-scale temporal resolution (Savić et al., 2019). Ozbakir and coworkers have developed an alternative MRI calcium sensor that is a protein based on calprotectin which sequesters manganese upon calcium binding. They have demonstrated this probe in vitro in mouse hippocampal cultures with results being on par with other MRI calcium sensors. Their approach is unique in that it is both T1 and T2 tunable, giving flexibility and breadth to what can be imaged, and that it can be engineered further through directed evolution to develop new variants (Ozbakir et al., 2021). Gene expression is another area to which MRI sensors are being applied. In this technique, a foreign gene that encodes an MRI reporter protein can be introduced to genome of a cell, either stably or transiently, and transcribed to produce a cellular marker (e.g., protein, peptide, or enzyme) that is MRI detectable (Srivastava et al., 2015). Many of these probes utilize ferritins and target iron transporters or storage proteins (Weissleder et  al., 2000; Deans et  al., 2006; Cohen et  al., 2005; Bernau et al., 2016; Pereira et al., 2015); however, Perlman and coworkers recently utilized

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CEST to construct a lysine-rich protein that was MRI detectable and applied to in vitro as well as in vivo to mice brains (Perlman et al., 2020). The spatial resolution of these probes is often worse than histochemical techniques. However, MRI offers certain advantages, including the potential to image repeatedly for comparison on longitudinal studies; the possibility of performing gene induction experiments in awake, behaving animals; and for monitoring plasticity and development (Bartelle et al., 2016). To become more powerful sensors, fMRI probes must be able to access more brain volume, more effectively, in a less invasive manner. More probes that can permeate cells and localize cytosolically would be important for application in human research (Zhang et al., 2007; Lee et al., 2010b). Probes that can cross the BBB that do not require direct injection to the brain and address the slow transport and response kinetics of the nanoparticles would also be beneficial (Bartelle et al., 2016; Rodriguez et  al., 2014). This is particularly challenging since many MRI probes contain highly polar metal complexes (Ghosh et al., 2018). Presently, fMRI probes require micromolar concentrations to detect signaling molecules, but most molecules of interest are only present in nanomolar quantities. By improving the technique and sensors, the level of detection can be shifted lower to capture these minute quantities while minimizing interference with the signaling pathway being studied (Lelyveld et al., 2011).

3.6 Ultrasound Probes and Imaging Modes Ultrasound is a form of energy that can penetrate soft tissues, producing images with spatial precision up to several μm with a temporal precision below 1 ms. Sound waves, above frequencies audible to humans, can travel through biological tissue and deliver momentum and energy to areas of interest, generating compression waves, which can be used to produce contrast for imaging (Fig. 3.9). Ultrasound uses a pulse-echo technique in which pulses of ultrasonic energy are transmitted into tissue and the backscattered echoes are received by a piezoelectric receiver. Scattering occurs due to different biological components having different densities or compressibilities. Ultrasound has been utilized by neuroscientists in applications ranging from high-resolution hemodynamic and molecular imaging to noninvasive neuromodulation (Rabut et al., 2020; Maresca et al., 2018). 3.6.1 Ultrasound Imaging Modes 3.6.1.1  B-mode Imaging When discussing ultrasound imaging, the images that come to mind are those of 2D grayscale fetuses and organs. These are known as brightness mode (B-mode) imaging. These images are generated using short ultrasound pulses and recording the

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Fig. 3.9  Cartoon of ultrasound transducer transmitting and collecting ultrasound pulses and echoes

backscattered echoes on an array element. The changes in position of the sound wave from generation to detection can be reconstructed into an image. B-mode imaging is effective for imaging most organs except for bone or air-filled organs such as the lungs (Maresca et al., 2018). 3.6.1.2  Doppler Imaging Besides soft tissue and organs, ultrasound can be used to detect blood flow using Doppler imaging (Evans et  al., 2011). Red blood cells weakly scatter ultrasound echoes, and with the advent of modern probes and computational processing, these weak signals can be detected to generate images. Temporal shifts in consecutive images show the displacement of the cells and a Doppler signal that is proportional to their velocity. This information can be used to create a vascular image of velocity (color Doppler) or energy of the cell echoes (power Doppler) (Maresca et al., 2018). 3.6.1.3  Contrast Imaging Like other imaging modalities, contrast imaging, in the context of ultrasound, relies on a contrast agent to label specific targets. The contrast agent of choice for this application is often micron-sized synthetic bubbles of gas, stabilized by a lipid or protein shell (Ferrara et al., 2007; Paefgen et al., 2015; Unnikrishnan & Klibanov, 2012; Frinking et al., 2000) that produce strong scattering as they resonate at the imaging frequencies with unique characteristic signals. Even a small amount of microbubbles (1 per 10,000 red blood cells) can increase the intensities by more than a factor of 100 due to the impedance mismatch between the blood and gas and by their natural oscillating resonance (Leighton, 1994; Couture et  al., 2018). By

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varying the amplitude modulation (Mor-Avi et  al., 2001) or phase inversion (Simpson et al., 1999), the detection of these microbubbles can occur with higher specificity or to enhance other ultrasound images techniques (e.g., Doppler imaging) (Maresca et al., 2018). 3.6.1.4  Ultrafast Ultrasound Imaging Traditional B-mode imaging generates an image from a series of focused transmission along an array. Ultrafast ultrasound imaging is similar; however, it uses a single-­plane wave transmission instead of focused line transmissions in series. This causes the frame rate to increase significantly and produce thousands of images per second compared to the typical 50 frames per second with traditional B-mode imaging. The advance was achieved with improvements to computing hardware for flexible beamforming and processing of scattered signals (Rabut et al., 2020). 3.6.1.5  Functional Ultrasound Imaging Through combining the concepts of ultrafast ultrasound imaging with Doppler imaging, functional ultrasound imaging began and has raised the sensitivity of conventional Doppler imaging by a factor of 30 (Maresca et al., 2018). By transmitting the plane waves at a series of angles, their echoes can be mathematically summed prior to processing, leading to enhanced signal to noise ratios and more robust contrast (Rabut et al., 2020). This technique is sensitive to blood flow velocities of the largest vessels (> 10 mm/s) to the smallest (0.5–1.5 mm/s) (Boido et al., 2019). In coupling these techniques, sequential imaging of brain has enabled the detection of neural activity through neurovascular coupling (Macé et al., 2011). 3.6.2 Ultrasound Localization Microscopy Taking inspiration from photoactivated localization microscopy (PALM) (Hess et al., 2006; Betzig et al., 2006) and stochastic optical reconstruction microscopy (STORM) (Rust et  al., 2006) imaging, Couture and coworkers envisioned ultrasound localization microscopy (Couture et al., 2011) by replacing fluorescent tags with ultrasonic contrast agents and cameras with high-speed programmable ultrasonic scanners. The technique is based on ultrafast imaging (i.e., 1000+ frames/sec) using hundreds of channels simultaneously to transmit a small set of plane or diverging waves that can be synthetically focused everywhere afterward using computer processing (Tanter & Fink, 2014). A big advantage to this technique, compared to power Doppler imaging, is a large increase in the number of temporal samples per pixel allowing for detection of extremely slow blood flow and gaining a 50-fold increase in sensitivity (Mace et al., 2013; Deffieux et al., 2021). The echo that originates from individual microbubbles can be both localized within microns

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and then tracked up to hundreds of milliseconds, allowing precise perfusion and high temporal sampling. In the context of the brain, super resolution ultrasound has been used to generate 2D vascular maps, 10+ mm deep, of rats (Errico et al., 2015) (10 μm resolution, 150 s), chicken embryos (Zhou et al., 2021) (10 μm resolution, ~17 s), and humans (Demené et al., 2021) (25 μm resolution, ~60 s) and, more recently, 3D whole brains of rats (Heiles et al., 2021) (12 μm resolution, 17 min). This approach has mostly been applied to vascular mapping; however, the nascent area is quickly expanding and adopting other areas of ultrasound (i.e., biomolecular ultrasound) and has been reviewed extensively (Couture et al., 2018; Errico et al., 2015; Chen et al., 2021; Christensen-Jeffries et al., 2020). 3.6.3 Imaging with Functional Ultrasound The first in vivo functional ultrasound imaging was performed on rats during whisker stimulation and through induced epileptic seizures. The technique was sensitive enough to detect single-trial cerebral blood velocity changes of 2% (Macé et al., 2011). Since then functional ultrasound imaging has been used in over 100 studies ranging from rodents to humans (Deffieux et al., 2018). It has been used for functional connectivity (Osmanski et al., 2014a), for mapping sensory cortical regions (Bimbard et  al., 2018; Osmanski et  al., 2014b; Rau et  al., 2018), for tracking of spreading depression waves (Macé et al., 2011; Demene et al., 2017; Rabut et al., 2019), and in the planning of movement (Norman et al., 2021). The precise quantitative relationships between the neural activity and functional ultrasound signals are still an active area of investigation though some studies, such as the one performed by Boido and coworkers in mice (Boido et al., 2019), demonstrated a linear relationship between standard optical imaging techniques and functional ultrasound images (Rabut et al., 2020). More recently, Aydin and coworkers demonstrated that functional ultrasound imaging of hyperemia is a robust reporter of underlying neuronal calcic activity, although this is an indirect measurement (Aydin et al., 2020). A drawback to this technique is caused by attenuation and aberration acoustic waves by bones (Pinton et al., 2011). In mice and young rats, the technique can be performed through intact skull (Tiran et al., 2017) but has been used in conjunction with open craniotomy for terminal imaging sessions (Mace et al., 2013; Osmanski et  al., 2014a, b; Gesnik et  al., 2017). Chronic imaging has been performed via thinned-skull procedures (Urban et  al., 2014) or through acoustically transparent cranial windows (Norman et al., 2021; Bergel et al., 2018; Sieu et al., 2015; Urban et al., 2015; Blaize et al., 2020; Dizeux et al., 2019). In humans, the technique has been used in intraoperative craniotomy procedures where the skull is absent (Imbault et al., 2017; Soloukey et al., 2020) and in newborns through the anterior fontanelle window (Demene et al., 2017).

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3.6.4 Biomolecular Ultrasound The concept of a genetically targeted ultrasound agent is relatively new with Shapiro and coworkers identifying Anabaena flos-aquae as producing natural gas vesicles that can be imaged via ultrasound (Shapiro et al., 2014). The genes responsible were quickly identified and engineered for bacterial cells followed by mammalian cells (Farhadi et al., 2019; Bourdeau et al., 2018). Recently, it was used as a biosensor by Lakshmanan and coworkers to sense protease activity within a mouse intestinal tract (Lakshmanan et al., 2020). While this approach has yet to be applied to brain research, the novelty of the approach combined with the burst of recent developments centered around ultrasound imaging makes it worth noting. 3.6.5 Ultrasonic Neuromodulation The ability to penetrate deeply into tissue and achieve high spatiotemporal precision makes ultrasound an appealing candidate for neuromodulation. In this application, waves only need to travel unidirectionally (i.e., from generator to target, not back to a receiver) and can be used at lower frequencies allowing for transcranial application in humans. In the context of functional ultrasound, these frequencies can be adjusted to interact specifically with different constituents of biological tissue in different manners including localized heating, mechanical force, and bubble cavitation. Through varying the pulsing parameters of the ultrasound waves (i.e., frequency, pressure, pulse duration, and duty cycle), the acoustic energy can have different thermal or mechanical effects on neurons (O’Brien, 2007). These forces can be used to directly activate or inhibit unmodified neurons, control genetically modified cells via sonogenetics, and deliver pharmacological agents or for acoustic targeting of chemogenetic agents (Rabut et al., 2020). The concept of using ultrasound to modulate brain function was first introduced in the 1950s when Fry and coworkers demonstrated the suppression of visualevoked potential in cats (Fry et  al., 1958). Since its inception, it has mostly laid dormant until the recent renewal of interest in ultrasound applications. Researchers have used it to study rodents (Tyler et al., 2008; Tufail et al., 2010; King et al., 2013; Ye et al., 2016; Sato et al., 2018; Mohammadjavadi et al., 2019; Wang et al., 2020; Min et al., 2011; Kim et al., 2012, 2014b; Younan et al., 2013; Sharabi et al., 2019; Guo et al., 2018), larger animals (Yoo et al., 2011; Lee et al., 2016a; Yoon et al., 2019; Dallapiazza et al., 2018), non-human primates (Deffieux et al., 2013; Wattiez et al., 2017; Yang et al., 2018; Folloni et al., 2019; Verhagen et al., 2019; Kubanek et al., 2020), and humans (Mueller et al., 2014; Legon et al., 2014; Lee et al., 2015, 2016b; Ai et al., 2018; Legon et al., 2018a, b; Braun et al., 2020; Sanguinetti et al., 2020) in a multitude of areas including ultrasound signal modulation and control of acoustic parameters for functional ultrasound targeting (Tufail et  al., 2010; King et al., 2013; Ye et al., 2016; Wang et al., 2020; Min et al., 2011; Yoo et al., 2011; Lee et al., 2016a; Yoon et al., 2019; Dallapiazza et al., 2018; Wattiez et al., 2017; Yang et al., 2018; Mueller et al., 2014; Ai et al., 2018), calcium and sodium responses

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(Tyler et  al., 2008; Sato et  al., 2018), motor responses (Sato et  al., 2018; Mohammadjavadi et al., 2019; Kim et al., 2012, 2014b; Younan et al., 2013; Legon et  al., 2018a), auditory responses (Guo et  al., 2018; Braun et  al., 2020), task responses (Deffieux et al., 2013; Kubanek et al., 2020; Legon et al., 2014, 2018b), mood changes (Sanguinetti et al., 2020), sensory enhancement or suppression (Lee et  al., 2015, 2016b), and functional connectivity (Folloni et  al., 2019; Verhagen et al., 2019; Sanguinetti et al., 2020). Sensory and motor effects consistent with neural excitation have been observed with low intensity ultrasound waves (spatial-peak-time averaged intensity, Ispta  100 μm into the PDMS walls. Similar devices made of polystyrene retain no dye even without washing the device between uses (Toepke & Beebe, 2006). PDMS gels can affect gene expression of cells cultured within them. This is likely due to residual chemical contaminants. One study reported alteration in the expression of over 600 genes in neurons maintained in PDMS environments compared to neurons grown on polystyrene (Lopacińska et al., 2013). However, this perturbation of gene expression and reduced biocompatibility can be reduced by extracting the PDMS using organic solvents; the most effective solvents are diisopropylamine, triethylamine, pentane, and xylenes (Lee et al., 2003; Millet et al., 2007). While nanoscale levels of resolution are possible with PDMS, the devices typically reach resolutions of ~1 μm (Hua et al., 2004). Finally, PDMS channels become clogged within minutes when exposed to benzoyl chloride, a common reagent utilized in liquid chromatography, limiting their use for neurochemical analysis (Fleszar et al., 2018; Lee et al., 2016; Valenta et al., 2021). While the cost of constructing μFDs with a molded PDMS is quite low, fine features of the molds can become damaged after repeated use. Thus, researchers will need to reproduce the molds via soft lithography, a process requiring clean-room facilities; however, alternative methods have been devised (Zhang et al., 2015).

4.4 Additional Materials Whereas PDMS is currently the most common material used for μFDs for neuronal culture, other materials have certain advantages. Although more expensive and complicated to fabricate, glass μFDs do not autofluoresce like PDMS or polyacrylamide μFDs, nor do they suffer from potential contaminants found within PDMS during their manufacture and use. Glass μFDs also have spatial resolution down to the nanometer scale (Piruska et  al., 2005; Toepke & Beebe, 2006; Zhong et  al., 2018). These advantages, when combined with light-sheet microscopy, have enabled cellular-­level investigations of whole brains in vivo while using glass μFDs (Mattern et  al., 2020). PDMS also has limited three-dimensional options as more complicated devices must be produced one layer at a time using multiple molds.

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Stereolithographic 3D techniques using low-MW (polyethylene glycol) diacrylate (MW 250) (PEG-DA250) enable fabrication of more complicated devices that require less labor on the part of the researcher (Urrios et al., 2016). Unfortunately, inexpensive single photon stereolithographic methods offer much lower resolutions (~500 μm) than many other commonly available options. For this reason, stereolithographic methods have thus far failed to reach the level of use seen by other methods although the technology is rapidly improving (Juskova et  al., 2018). Finally, injection-molding techniques provide researchers with rapid and inexpensive microfluidic devices that can be used to culture neurons in a variety of different plastics with resolutions down from 25 μm to a single micron (Giboz et al., 2007; Ma et al., 2020). These mass-produced μFDs may be the best option for those not requiring more bespoke designs that need to vary between experiments, require multiple layers or multiple mixing chambers, or generally require more than a simple chemical isolation between two or three chambers. While injection-molded μFDs are the cheapest to produce at scale, researchers requiring models not currently available will seldom have the means or expertise of using the costly machines to produce them. Further, the price of injection-molding increases dramatically due to the up-front cost of tooling.

4.5 Evaluation of Fabrication Methods 4.5.1 Glass and Silicon Although glass and silicon μFDs have many positive qualities for studying neuronal development, construction using glass can be far more difficult. The glass or silicon must be first altered for its desired features by either surface micro-machining, the use of buried channel techniques, or bulk micro-machining, which is the most common method (Iliescu et al., 2012). Conventional methods of fusing slides together to fabricate glass μFDs often require baking temperatures of several hundred degrees and dangerous chemicals, such as hydrofluoric acid or boiling piranha (Lin et al., 2001; Mattern et al., 2020; Wang et al., 1997). Given these dangers, many researchers prefer other materials. However, progress has been made in making glass μFDs cheaper, safer, and easier to fabricate. The process of fusing glass slides, which typically takes the extreme temperatures mentioned, can be accomplished simply by application of water followed by several hours of compression or by spreading sodium silicate as an adhesive (Funano et al., 2021; Iliescu et al. (2012). The effort to create more accessible glass μFDs has even produced a method capable of constructing the devices with a microwave (Kopparthy & Crews, 2018). However, the smallest channel using this technique was 500 μm wide, which is much too large for many applications in analyzing neuronal development.

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4.5.2 PDMS Producing a PDMS μFD first requires computer-aided drawing (CAD) of the mask for use in photolithography (McDonald et al., 2000). Next, a clean room will be needed to construct the molds via photolithography using the masks (Jain & Gillette, 2015). The exact steps needed for photolithography will depend upon the type of photoresist material used as well as the design of the μFD. At this point, PDMS is mixed to produce the required elasticity, poured over the manufactured silicon mold, allowed to cure, chemically treated for optimized biocompatibility, and finally fused to a glass slide for use in experimentation (Gale et al., 2018; Lee et al., 2003; Millet et al., 2007; Wang et al., 2014). While the ability to pour PDMS μFDs at the bench is an often-cited benefit of the material, it is important to understand that the molds produced in clean rooms will degrade over time with the fine features breaking after repeated use. Eventually the need to produce PDMS μFDs will require return trips to clean rooms to replace broken silicon molds. 4.5.3 Injection Molding The ability to use injection molding for a μFD of the researcher’s own design is often, if not always, prohibitively expensive (Iliescu et al., 2012). Injection molded μFDs can be produced from various thermoplastics suitable for researchers, such as polymethyl methacrylate (PMMA), polystyrene (PS), or polycarbonate (PC) (Ma et al., 2020). While small batches of injected molded μFDs may enable production of novel designs for probing specific questions, they are typically too expensive for most applications. Overall, utilizing mass-produced devices remains the easiest and least expensive means of acquiring μFDs. 4.5.4 Stereolithography and Other Methods While the previously described fabrication methods are by far those most commonly used, there are other processes that can be considered. In addition to being amenable to injection molding, thermoplastics can also be transformed into μFDs via the use of laser micro-machining or hot embossing (Klank et al., 2002; Lin et al., 2017). 3D printing or stereolithography offers an exciting and potentially cost-­ effective means of creating complex 3D devices that are difficult to produce using layered PDMS μFDs (Juskova et al., 2018; Zhang et al., 2010). However, despite the promise of stereolithography for revolutionizing μFD production, the two-photon method typically required to achieve high-resolution devices is still a much slower and expensive process (Chizari et al., 2020; Hiroaki et al., 2019; Tang et al., 2020; Tayalia et al., 2008).

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5 Additional Uses of μFDs for Studying Neuronal Development Microfluidic devices can also benefit those who wish to use standard culturing techniques. Neurons in vivo are embedded in a complex three-dimensional environment of mixed cell types that is poorly replicated in a standard Petri dish. Researchers wishing to use conventional culture plates, but add more complex physical environments, can use microfluidic devices to pattern 1 μm wide bands of PDMS onto an otherwise standard dish to “...induce neuronal differentiation and outgrowth to aid in regeneration in neurologic injury sites” (Kim et  al., 2008). A PDMS μFD can be reversibly attached to a glass slide or dish with the channels of this device flooded by a chemotaxic molecule of choice (Hsu et al., 2005; Millet et al., 2010a; Shelly et al., 2007). Removal of the device leaves a negative pattern of the chemotaxic molecule with which neurons can then be cultured. These cultured neurons can then be observed for their reaction toward the areas patterned with the chemotaxic molecule vs. uncoated regions of the dish. This technique of substrate-­patterning has been used to pattern threedimensional cell matrices for developmental studies and explore neuron polarization, to name just a few examples (Tan & Desai, 2003). μFDs have also been used for whole brain live imaging in the presence of tightly controlled chemical cues. In this context, multiple high-speed scans of the organism or organisms would permit rapid acquisition of data in vivo (Mattern et al., 2020).

6 Conclusions There are diverse materials available for fabricating μFDs. Potential uses are many, and the range of their applications resides with the investigators’ creativity. Each researcher must weigh the benefits and drawbacks of each type of material and device design to best address their own needs. While some options may currently be cost-prohibitive or overly complicated, the techniques to produce useful μFDs are becoming increasingly less expensive and more accessible. The use of μFDs will only expand within neuroscience as the fabrication technology for μFDs continues to become cheaper and easier, and insights derived from more closely approximating the natural condition grow. Future uses of μFDs will benefit from the tight and quantifiable control of gradients, integration with cerebral organoids, or even whole brain imaging, and the lowering of costs and complexity for a wider variety of potential materials and 3D designs. The use of μFDs in analyzing neurodevelopment will increase along with more robust and quantitative results for years to come.

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Acknowledgments  The authors thank Jennifer W. Mitchell for insightful discussions. Content is solely the responsibility of the authors and does not represent the official views of the funding agencies. The authors declare no competing financial interest. Preparation of this review was supported by awards from the National Institute of Mental Health (1R21 MH 117377); the National Heart, Lung, and Blood Institute (R61 HL 159948); and the National Science Foundation (NSF DGE 17-35252 and NSF STC CBET 0939511) to M.U.G.  M.D.N. was supported by an NSF National Research Traineeship on Miniature Brain Machinery (NSF DGE 17-35252). Declaration of Interests  The authors declare no competing interests.

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Part III

Designing Therapeutic and Diagnostic Interventions for Neurological Disease

Chapter 5

Bioresponsive Nanomaterials for CNS Disease Julia A. Kudryashev, Marianne I. Madias, and Ester J. Kwon

Abstract  Diseases of the central nervous system (CNS) affect millions of people worldwide and disease burden is increasing with an aging population. Yet, there are few medicines available to diagnose and treat neurological disorders and progress on developing new medicines has been limited. One major challenge is the narrow therapeutic window of payloads that act in the CNS – significant transport barriers restrict bioavailability yet the CNS is sensitive to toxicity. Bioresponsive nanomaterials can be engineered to activate based on context and encode sophisticated functions. Contexts that activate bioresponsive nanomaterials can be specific to the temporal and spatial dynamics of healthy and pathological biological processes, and thus offer approaches to increase efficacy of payloads while mitigating off-target effects. In this chapter, environment cues specific to CNS diseases or within subcellular compartments will be discussed and examples of bioresponsive nanomaterials that have been engineered to respond to these cues will be presented. Keywords  Stimuli-responsive · Nanomaterials · Biomaterials · Receptor-mediated transcytosis · Transferrin · pH-responsive · Redox-responsive · ROS scavenging · Proteolytic · Cargo release · Activity-based nanosensing · Hypoxic conditions · Electrical impulse

J. A. Kudryashev · M. I. Madias · E. J. Kwon (*) Department of Bioengineering, University of California, San Diego, CA, USA e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2022 E. Nance (ed.), Engineering Biomaterials for Neural Applications, https://doi.org/10.1007/978-3-031-11409-0_5

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1 Introduction A major challenge in the development of CNS medicines is the narrow therapeutic window. Systemically administered therapeutics have limited bioavailability to the CNS due to transport barriers such as the blood-brain barrier (BBB), requiring large doses that can lead to off-target toxicity. One approach to navigate this narrow therapeutic window is through local, controlled release of drugs. An example of this approach that has achieved clinical translation for the treatment of malignant gliomas is the Gliadel® Wafer, a 1 mm thick, 1.45 cm diameter disc comprised of chemotherapeutic formulated with a mixture of synthetic polymers. Gliadel® Wafers are designed to be implanted in the surgical cavity created by tumor resection and slowly degrade for the controlled release of chemotherapeutic over 3 weeks. While the local implantation of a controlled release formulation is an approach that can be effective when there is surgical access to the brain (e.g., resection of brain cancers, removal of blood clots/control of bleeding, or relieving pressure after brain injury caused by traumatic injury or stroke), there are many neurological disorders where surgical intervention is not the standard of care. In addition, surgical access to the brain is typically acute and may not be appropriate for medicines that require chronic delivery. As an alternative strategy to local implantation to achieve desirable pharmacokinetics, materials have been engineered to switch between inactive and active states based on cues to control on- vs. off-target activity. This class of materials, referred to as “stimuli-responsive” or “smart” materials, has been engineered to respond to a wide range of stimuli, and in ideal cases responses can be controlled spatially and temporally within a living organism. Activating stimuli can be broadly separated into human-controlled, externally generated stimuli (e.g., heat, magnetic fields, or ultrasound) and biologically generated, endogenous stimuli (e.g., acidity, redox potential, or enzyme activity) (Mura et al., 2013; Blum et al., 2015; Lu et al., 2016). While aspects of spatial and/or temporal control of externally generated stimuli can be user-controlled, application requires a priori knowledge of the disease location and timescales. In contrast, endogenous stimuli arise from specific pathologies and/or natural biological compartments, and therefore materials that respond to these stimuli can behave autonomously to their environment once delivered into the body. Due to the biological nature of these endogenous stimuli, materials that are responsive in these contexts are referred to as “bioresponsive” materials. Some of the earliest applications of bioresponsive materials have been for drug delivery (Hoffman, 2013). One of the first examples of a pH-responsive delivery system was a pH-degradable polymer of vinyl acetate-maleic anhydride, which released drug with the ionization of carboxyl sidechains in physiological solutions (Heller et  al., 1978). Another notable example of a pH-responsive polymer is Carbopol® (polyacrylic acid), which undergoes a sol-gel transition and becomes mucoadhesive when placed in solutions above pH 5.5 (Lin & Sung, 2000). Carbopol is a component of multiple FDA-approved drug delivery systems in applications in the eye, nose, stomach, and vagina (Hoffman, 2013; Lin & Sung, 2000; Agrawal et al., 2020). Since initial designs, many advances have been made in developing

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bioresponsive materials that are tailored to disease-associated microenvironments such as wound beds, tumors, and atherosclerosis (Blum et al., 2015; Lu et al., 2016; Cook & Decuzzi, 2021). For example, injectable MMP-responsive hydrogels have been developed which can release MMP-specific inhibitors in response to elevated MMP activity within infarcted myocardial tissue (Purcell et al., 2014). In a porcine model of myocardial infarction, these hydrogels were found to attenuate postinfarction tissue remodeling with limited off-targeted effects after direct injection into the infarcted tissue. One prominent class of bioresponsive materials that have been FDA-approved or currently in clinical trials is antibody-drug conjugates that are protease-responsive for the treatment of cancer. Adcetris®, which was first approved for clinical use to treat lymphoma in 2011, is an anti-CD30 antibody which releases drug intracellularly via cathepsin-B-cleavable linkages between the antibody and the cargo (Doronina et  al., 2003). The protease-responsive linker was found to reduce off-target toxicity of antibody-drug conjugates in tumor xenograft mice compared to treatment with conjugates containing pH-sensitive hydrazone bonds (Doronina et al., 2003). In the Probody™ antibody system by CytomX, of which multiple conjugates are currently undergoing clinical trials, the antibody’s binding site is masked with a blocking domain through a protease-cleavable linker (Kavanaugh, 2020). The inclusion of this protease-sensitive masking domain drastically reduced off-target toxicity of monoclonal antibody therapies such as EGFR-­ targeted cetuximab; in healthy nonhuman primates, the safety factor of cetuximab was increased by 3- to 15-fold when it was modified with a masking domain connected via a uPA- and matriptase-cleavable linker (Desnoyers et al., 2013). These examples show how bioresponsive materials have been leveraged to improve the therapeutic efficacy of drugs by tuning elements to respond to disease-associated protease activity. Materials with dimensions on the nanometer length scale have unique and emergent physical and biological properties that have been exploited to create tools, diagnostics, and therapeutics in numerous disease contexts, including cancer, infections, and CNS diseases (Kwon et al., 2015; Shi et al., 2017). The material composition of these “nanomaterials” can be varied and includes metals, ceramics, synthetic polymers, biomolecules, and composites thereof. Since the FDA approval of Doxil in 1995, an increasing number of nanomaterial drug delivery systems have been translated into the clinic over the past decades (Anselmo & Mitragotri, 2016; Attenello et al., 2008). One reason for why nanomaterials are attractive platforms for drug delivery is that they can widen the therapeutic window. For example, Doxil is a lipid/polymer formulation of the chemotherapeutic doxorubicin which was designed to mitigate off-target effects through altering drug biodistribution based on physicochemical properties. Encapsulation of doxorubicin in the interior of the ~100  nm liposome resulted in decreased cardiotoxicity and nephrotoxicity compared to free drug (Safra et al., 2000; Lyass et al., 2001). Nanomaterials can also increase the efficacy of therapeutics. Nucleic acid drugs are charged, labile macromolecules that require intracellular localization to be active, usually to the cytosol or nucleus. Due to the physicochemical properties of nucleic acids, transport to intracellular compartments is negligible without a delivery carrier. The first

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synthetic nanomaterial for nucleic acid delivery approved by the FDA was patisiran, approved in 2018 for the intravenous delivery of siRNA to treat hereditary transthyretin-­mediated amyloidosis, a rare life-threatening disease caused by mutations in transthyretin (Adams et  al., 2018). In 2020, similar lipid nanoparticle designs were granted emergency approval by the FDA as mRNA-based vaccines for COVID-19 (Polack et al., 2020). A crucial component to these lipid nanoparticle technologies is an ionizable lipid that can become protonated in the endosomal-­ lysosomal pathway to mediate cargo release into the cytoplasm (Kulkarni et al., 2019). We focus on the discussion of bioresponsive nanomaterials engineered for CNS diseases. Nanomaterials are useful platforms to create bioresponsive systems because they are often supramolecular assemblies, which allows for the design of sophisticated, multicomponent systems. Bioresponsive nanomaterials ~10–200 nm in size can be assembled from ~1–5  nm stimuli-responsive elements that collectively lead to a state change across the greater nanomaterial structure. At the molecular level, the stimuli-responsive elements that make up the fundamental building blocks in the greater nanomaterial structure can be categorized to have two types of responses: cleavage of covalent bonds or changes in physicochemical properties (Fig. 5.1). Depending on the organization of these fundamental building blocks in the greater nanomaterial structure, a large diversity of responses can be engineered. Systems can directly respond to stimuli (Fig. 5.2) or translate stimuli to nanomaterial state changes that trigger programmable functions (Fig. 5.3). Because of the major transport barriers to and within the brain and the narrow therapeutic window of CNS therapeutics, numerous bioresponsive nanomaterial systems have been developed to improve delivery by responding to environmental cues present in biological barriers and/or in disease-specific contexts. The BBB is a major biological barrier for systemically delivered nanomaterials and is estimated to exclude >99% of all therapeutics (Daneman, 2012; Pardridge, 2005), although disease-specific dysregulation of BBB function may be exploited for therapeutic delivery (Kandell et al., 2021). Due to the major bottleneck presented by the BBB, bioresponsive systems have been engineered to utilize endogenous transcellular transport pathways (Fig. 5.4). Bioresponsive nanomaterials designed for the CNS can also capitalize on environmental cues that change depending on disease-­ associated pathological processes or subcellular compartments. Environmental cues exploited by bioresponsive nanomaterials designed for the CNS broadly include pH, redox potential, and enzymatic activity, and changes in these cues can arise in CNS diseases such as brain injuries, neurodegenerative diseases, and cancer. Subcellular compartments such as the endosome or the cytosol also have distinct chemical environments that can be exploited by bioresponsive nanomaterials. In this chapter, the BBB and major environmental cues that are perturbed in CNS disease (pH, redox, proteases, electrical impulses, and hypoxia) will be discussed. For each cue or context present in the CNS, examples of bioresponsive nanomaterials will be presented (Table 5.1).

5  Bioresponsive Nanomaterials for CNS Disease

Fig. 5.1  Fundamental stimuli-responsive elements in bioresponsive nanomaterials

Fig. 5.2  Bioresponsive nanomaterials that directly respond to stimuli

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Fig. 5.3  Bioresponsive nanomaterials that translate stimuli to a state change

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Fig. 5.4  Bioresponsive nanomaterials that traverse the BBB through transcellular pathways

2 BBB Targeting Strategies A significant challenge in the development of therapies for CNS pathologies has been the effective delivery of intravenously injected agents into the brain. The BBB is a physical and functional barrier that is estimated to exclude ~100% of macromolecules and greater than 98% of small molecules from the brain. Major components of the barrier include tight junctions between cells, low rates of transcytosis across cells, and the expression of efflux pumps (Pardridge, 2005). In recent decades, nanomaterials have emerged as a promising approach to create drug delivery systems that cross the BBB due to their ability to be rationally designed, oftentimes independently from their drug cargo. Numerous strategies have been devised to facilitate the transport of nanomaterials across the BBB, including targeting BBB receptors for receptor-mediated endocytosis, activating transporters for carrier-­ mediated transport, and changing nanomaterial surface charge or lipophilicity to target adsorptive-mediated endocytosis (Fig.  5.4) (Liu & Lu, 2012; Khan et  al., 2018; Furtado et  al., 2018). These delivery strategies help widen the therapeutic window by increasing the bioavailability of cargo in the brain, thereby reducing the administered dosage necessary to achieve therapeutic efficacy. In order to exploit receptor-mediated transcytosis, nanomaterials are typically modified with ligands that specifically target endocytotic receptors present on the BBB. Ligands presented on nanomaterial structures are typically multivalent,

Cue pH

Cancer

Cancer

Chronic pain

Cancer

Cancer

Cancer

Disease Cancer

Chemistry of response Cleavage of hydrazone bond between cargo and micelle in tumor microenvironment Cleavage of boronate ester bond between targeting ligands in tumor microenvironment

State change Dissociation of micelle

Outcome Cargo release of vinblastine derivative in a mouse glioma model Polymer micelle Dissociation of Enhanced levels and specificity micellar network, of accumulation in a mouse exposure of targeting glioma model ligands against glioma cells Polymer/iron oxide Protonation of block Shrinking of NPs Prolonged blood circulation nanoparticle copolymer in tumor time, enhanced accumulation in microenvironment tumor, extended MRI time window in a rat glioma model Polymer micelle Protonation of block Dissociation of Enhanced levels and specificity copolymer in tumor micelle, dequenching of PET cargo uptake in tumor microenvironment of fluorescent dye cells, imaging of tumor in a mouse glioma model Polymer micelle Protonation of block Dissociation of Release of therapeutic to inhibit copolymer in endosome micelle pain signaling initiated in the endosome in a rat model of chronic pain Gold nanoparticle Cleavage of hydrazone bonds Cargo release of between cargo and chemotherapeutic doxorubicin, nanoparticle in endosome decreased off-target toxicity in a mouse glioma model Poly-L-lysine Cleavage of diamino ketal Release of Increased BBB exocytosis and dendrigraft linker between Tf and dendrigraft from accumulation in tumor, cargo dendrigraft in endosome Tf-TfR complex release of doxorubicin in a mouse glioma model Cleavage of imine linker between doxorubicin cargo and dendrigraft

Nanomaterial Polymer micelle

Table 5.1  Examples of bioresponsive nanomaterials applied to CNS pathologies

Ruan et al. (2018)

Ruan et al. (2015)

RamírezGarcía et al. (2019)

Huang et al. (2020)

Jiang et al. (2013)

Wu et al. (2020)

References Quader et al. (2021)

196 J. A. Kudryashev et al.

Cue Redox

Stroke

Stroke

Alzheimer’s disease

Alzheimer’s disease

Spinal cord injury

TBI

Disease Stroke

Chemistry of response ROS-mediated oxidation of sulfide groups in inflammatory microenvironment Polymer ROS-mediated oxidation of nanoparticle thioether groups in inflammatory microenvironment Polymer ROS-mediated oxidation of nanoparticle thioether groups in inflammatory microenvironment Mesoporous silica H2O2-mediated oxidation and capped with gold cleavage of boronate ester nanoparticle or IgG linker between AuNP/IgG and mesoporous silica Polymer micelle H2O2-mediated oxidation and cleavage of phenylboronic groups in inflammatory microenvironment Polymer micelle H2O2-mediated oxidation and cleavage of phenylboronic groups in inflammatory microenvironment H2O2-mediated oxidation and Polymer nanoparticle with cleavage of phenylboronic RBC membrane groups in intracellular space shell

Nanomaterial Polymer nanoparticle

Destabilization of hydrophobic core

Destabilization of hydrophobic core

Destabilization of hydrophobic core

Uncapping of MSN pores

ROS scavenging

State change ROS scavenging, swelling of NP, shedding of PEG surface layer ROS scavenging Yoo et al. (2017)

Cargo release of NR2B9C in a rat stroke model

Cargo release of rapamycin in a rat stroke model

Cargo release of metal chelator clioquinol and decreased cytotoxicity in vitro in PC12 cells Cargo release of curcumin in a mouse AD model

(continued)

Lv et al. (2018)

Lu et al. (2019a, b)

Yang et al. (2016) and Geng et al. (2012) Lu et al. (2019a, b)

Zhang et al. Decreased inflammation, improvement in motor skills in a (2021) rat spinal cord injury model

Decreased tissue levels of ROS in a mouse TBI model

Outcome References Decreased neuroinflammation in Rajkovic et al. a mouse stroke model (2019)

5  Bioresponsive Nanomaterials for CNS Disease 197

Protease

Peptide/polymer micelle

Polymer nanoparticle with platelet membrane shell

Stroke

Gold nanoparticle

Stroke

Cancer

Polymer nanocapsule

Nanomaterial Polymer micelle

Cancer

Table 5.1 (continued) Cue Disease Cancer

Thrombin-mediated cleavage of a LTPRGWRLGGC peptide linker between rtPA and TAT peptide pH-mediated degradation of dextran core in ischemic tissue

Chemistry of response H2O2-mediated oxidation and cleavage of phenylboronic groups in intracellular space GSH-mediated reduction and cleavage of cystamine disulfide cross-linker in intracellular space ROS and hyaluronidase-­ mediated degradation of hyaluronic acid linker between FAM and AuNP in inflammatory microenvironment MMP-2/9-mediated cleavage of PLGLAG peptide linker between protamine and TAT peptide Increased delivery of paclitaxel cargo to tumor, reduced CPP-mediated off-target accumulation in a mouse glioblastoma model Cargo release of rtPA at blood clot and ZL006e in ischemic brain, increased BBB transport and accumulation in ischemic tissue in a rat stroke model

Activation of CPPs TAT

Degradation of NP

Dissociation of NP, activation of CPP TAT

Imaging of ROS levels in the brain in a rat stroke model

Cargo release of siRNA in a mouse glioblastoma model

Degradation of nanocapsule

Dequenching of FAM

Outcome Cargo release of siRNA in a mouse glioma model

State change Destabilization of hydrophobic core

Xu et al. (2019)

Gu et al. (2013)

Hyun et al. (2013)

Zou et al. (2020)

References Zheng et al. (2019)

198 J. A. Kudryashev et al.

Cue

Nanomaterial Gold nanoparticle

Peptide/polymer micelle

Peptide/polymer micelle

Peptide/polymer micelle

Polymer micelle with prodrug gene

Disease Cancer

Alzheimer’s disease

Stroke

Cancer

Cancer

State change Aggregation of gold via click cycloaddition between 1,2-thiolamino group and CABT on separate AuNPs

Aggregation of micelles via click cycloaddition between 1,2-thiolamino group and CABT on separate micelles Thrombin-mediated cleavage Removal of PCL to restructure and of a norleucine-­TPRSFL shrink micelles or peptide linker or MMP-9removal of PEG to mediated cleavage of a LGRMGLPGK peptide linker destabilize and between PEG and PCL blocks aggregate micelles Neutrophil elastase-mediated Removal of PCL to restructure and cleavage of a RLQLKL shrink micelles peptide linker between PEG and PCL blocks MMP-2-mediated cleavage of Cargo activation of promelittin to PLGLAG peptide linkers melittin between promelittin and vector sequences

pH-mediated cleavage of hydrazone bonds between cargo and surface of AuNP in endosome Legumain-mediated cleavage of a AANCK peptide for exposure of 1,2-thiolamino group on peptidefunctionalized micelle

Chemistry of response Legumain-mediated cleavage of a AANCK peptide for exposure of 1,2-thiolamino group on peptidefunctionalized AuNP

References Ruan et al. (2016)

Zhang et al. (2020) Enhanced delivery of doxorubicin cargo in a mouse metastatic tumor model

(continued)

Zhou et al. Activation of melittin in tumor with limited off-target toxicity in (2020) a mouse metastatic tumor model

Guo et al. (2018)

Enhanced delivery of glyburide cargo to ischemic brain tissue with shrinking thrombin-­ responsive micelles in a mouse stroke model

Increased retention of paclitaxel, Ren et al. donepezil, and insulin cargos in (2020) a mouse AD model

Outcome Increased retention and specificity of doxorubicin cargo delivery in a mouse glioma model

5  Bioresponsive Nanomaterials for CNS Disease 199

Epilepsy

Polymer/lipid micelle

Polymer hydrogel nanoparticle

Polymer/peptide conjugate

TBI

Hypoxia Cancer

Electric field

Quantum dot

Nanomaterial Polymer/peptide nanocapsule

Cancer

Table 5.1 (continued) Cue Disease Cancer

Hypoxic reduction of nitro groups to amino groups on metronidazole core in intracellular space

Chemistry of response MMP-2-mediated cleavage of VPLGVRTK peptide cross-linker MMP-2-mediated cleavage of PLGVR peptide linker between low molecular weight protamine and QSY21 Calpain-1-mediated cleavage of QEVYGAMP linker between quencher and fluorophore Ionization of sulfonate groups during seizure Dequenching of FRET peptide

Destabilization of hydrophobic core

Cargo release of anti-seizure drug phenytoin sodium in a mouse seizure model Enhanced delivery of doxorubicin cargo and sensitized tumor to radiotherapy in a mouse glioma model

Imaging of calpain-1 activity in a mouse TBI model

Dequenching of quantum dot

Swelling of NPs

Outcome Delivery of antibody cargo across BBB in a glioma mouse model Imaging of tumor in a mouse glioma model

State change Degradation of nanocapsule

Hua et al. (2018)

Wang et al. (2016)

Kudryashev et al. (2020)

Wang et al. (2015)

References Han et al. (2019)

200 J. A. Kudryashev et al.

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leading to an increase in the overall binding strength of the nanomaterial, termed avidity. The functionalized nanomaterial is endocytosed after binding to receptors on the luminal side of the BBB, after which it can then be released into the brain parenchyma on the abluminal side or trafficked into a lysosome for degradation (Fig.  5.4a) (Furtado et  al., 2018). Transferrin receptor-mediated endocytosis has been one of the most well-studied pathways for exploitation by drug delivery; however, the binding avidity of materials must be finely tuned to optimize transport. As an example of this challenge, in a study of systemically administered transferrin antibodies, antibodies with a high affinity for the transferrin receptor were found to have limited transport into the brain parenchyma despite a high level of uptake into the BBB. The high-affinity interaction of these antibodies with their receptor leads to a high fraction of antibodies remaining bound to transferrin receptors within the endosome and minimal release into the brain parenchyma. Simultaneously, tightly bound antibodies also reduce the number of available transferrin receptors for additional antibody binding (Yu et al., 2011). This delivery traffic jam was resolved by engineering antibodies with moderate binding affinity for the transferrin receptor, which promoted release into the parenchyma at the cost of lower initial receptor binding in the lumen. As an alternate strategy to the precise balancing of receptor binding affinity, a nanomaterial can undergo a stimulus-triggered state change between high avidity and low avidity binding to membrane receptors to maintain both a high rate of uptake into the BBB and a high rate of release into the brain. This strategy was first demonstrated with gold nanoparticles (AuNPs) which were functionalized with transferrin via pH-cleavable linkages to improve receptor-mediated transcytosis across the BBB in mice (Clark & Davis, 2015). During endocytosis, the acidic environment within the endosome cleaves the diamino ketal linkers between the AuNP and transferrin, triggering a release of the AuNP from the transferrin/transferrin receptor complex. Thus, the AuNPs have a high avidity for the transferrin receptor on the luminal side to promote entry into the BBB and then undergo a pH-induced dissociation on the abluminal side to promote release from the BBB. In another technology which built upon the pH-triggered change for transferrin receptor avidity, a glucose analog which acted as an additional targeting ligand against glucose transporter 1 (GLUT1) was incorporated to increase the rate of nanomaterial exocytosis into the brain parenchyma (Ruan et  al., 2018). After internalization via the transferrin receptor, pH-mediated cleavage of the transferrin ligand in the endosome allowed dissociation from the transferrin receptor complex and an increased rate of exocytosis. The glucose analog could then promote subsequent uptake by GLUT1-­ expressing glioma cells. In a C6 glioma mouse model, nanoparticles modified with glucose analog, pH-cleavable transferrin, and pH-triggered doxorubicin release increased doxorubicin delivery to the glioma, increased the specificity of delivery to glioma over healthy brain tissue, and led to prolonged survival times in mice compared to nanoparticles modified with glucose analog and non-cleavable transferrin and nanoparticles modified with only pH-cleavable transferrin. Adsorptive-mediated endocytosis is receptor-independent and is instead based on physicochemical properties. In order to exploit adsorptive-mediated endocytosis,

202

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nanomaterials have been functionalized with positive charges to promote electrostatic interactions with negatively charged proteoglycans on the luminal side of the BBB (Fig. 5.4b) (Furtado et al., 2018). Cationic, amphipathic cell-penetrating peptides (CPPs) such as transcriptional activator (TAT) peptide are one category of materials used to facilitate receptor-independent endocytosis of nanomaterial across the BBB. While this strategy can improve intracellular delivery of nanomaterials, the charge-based interactions mediated by CPPs can also lead to nonspecific targeting to multiple cell types, increased clearance from the liver, and increased systemic toxicity with intravenous administration (Aguilera et al., 2009). In responsive materials, these drawbacks can be tempered with the incorporation of a domain which masks CPP activity with a neutralizing negative charge or steric hindrance (Aguilera et al., 2009). Masking domains are linked to the CPP via a cleavable moiety so that the CPP is inert in circulation until the mask is removed by local tissue- and/or disease-specific cues, revealing CPPs and triggering electrostatic interaction with the cell membrane. This strategy was used to improve drug delivery to ischemic brain tissue in stroke with a CPP-functionalized nanoplatelet which could activate CPP in the proximity of a blood clot (Xu et al., 2019). A ~167 nm nanoplatelet was engineered from a dextran core, a platelet membrane shell, and surface coating of a CPP which was masked by thrombolytic recombinant tissue plasminogen activator (rtPA) via a thrombin-cleavable linker. After systemic administration in a rat stroke model, the nanoplatelet could first localize to the thrombus, where active thrombin was available to cleave peptide linkers on the surface. Cleavage triggered both release of therapeutic rtPA to induce proteolytic degradation of the blood clot and exposure of the CPP on the nanoplatelet surface for entry into the BBB. With the exposed CPP, the nanoplatelet could transcytose across the BBB into the ischemic penumbra, where the acidic microenvironment then degraded the dextran core to prompt the release of a second payload of neuroprotectant ZL006e into the parenchyma. Compared to nanoplatelets with non-cleavable peptides and free drug, systemically administered activatable nanoplatelets were able to cross the BBB more efficiently in rats with stroke and led to a > two-fold decrease in brain infarct volume, greater decrease in brain ROS levels, and improvement in neurological scores with minimal off-target toxicity. Thus, receptor-independent adsorptive-mediated transcytosis could be exploited by the thrombin-mediated unveiling of CPP in proximity to disease-associated BBB.

3 pH 3.1 pH in CNS Pathology pH gradients occur within the body at the tissue and cellular level in both healthy and disease conditions. While the normal pH of blood is slightly alkaline at ~7.4, the pH in other tissues can be more acidic or basic depending on the specific needs

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for biological function. At the cellular level, in comparison to the slightly alkaline extracellular pH (7.3–7.4), cytosolic pH is more acidic (pH  7.2) due to cellular metabolism, often leading to local acidosis in disease states where cellular metabolism is dysregulated (Gerweck & Seetharaman, 1996; Anderson & Sundt, 1983). In the brain, extracellular pH is measured to be 7.1–7.3 in microelectrode recordings in animal models (Zhou et al., 2016; Chesler, 2003). In CNS pathologies such as gliomas and ischemic stroke, hypoxia and acidosis in the tissue microenvironment can lead to abnormal pH gradients that can be exploited by engineered nanomaterials. Cancer cells have a unique “reversed” pH gradient where their intracellular pH is above normal (>7.2) and extracellular pH is lower (~6.7–7.1) (Webb et al., 2011). High intracellular pH aids in tumor cell proliferation and evasion of apoptosis, while low extracellular pH promotes cell-matrix remodeling and increases the activity of acid-activated proteases. This pH gradient is a result of the increased expression and activity of passive and active plasma membrane transporters that release lactate and H+ ions in the tumor microenvironment (Corbet & Feron, 2017). The extracellular accumulation of protons in the tumor microenvironment can be further exacerbated by dysregulated tumor vasculature and poor lymphatic drainage. Extracellular pH can be heterogeneous throughout the tumor (Harris et al., 2018), and differential pH is hypothesized to decrease over time as the tumors progress (Korenchan & Flavell, 2019). An acidic extracellular environment can also occur in ischemic stroke and in TBI. After vessel blockage in the brain, the lack of effective perfusion directly causes local tissue acidosis. Hypoperfused tissue rapidly becomes hypoxic, and the resulting anaerobic metabolism leads to the accumulation of lactic acid (Siesjö, 1992). In this process, both intracellular and extracellular H+ concentrations increase; local pH in the peri-infarct penumbra ranges from 6.5 to 6.9 and can be as low as 6.0 in the ischemic core (Tóth, 2020). Ischemic tissue acidosis leads to increased risk of cell dysfunction and cell death due to activation of pH-sensitive ion channels linked to intracellular Ca2+ accumulation and cytotoxic edema (Tóth, 2020). Within TBI, acidic extracellular pH (pH