A modular brain-on-a-chip for modelling epileptic seizures with functionally connected human neuronal networks

Tailoring epilepsy treatment: personalized micro-physiological systems illuminate individual drug responses

Introduction

Approximately 50 million people worldwide have epilepsy, with many not achieving seizure freedom. Organ-on-chip technology, which mimics organ-level physiology, could revolutionize drug development for epilepsy by replacing animal models in preclinical studies. The authors' goal is to determine if customized micro-physiological systems can lead to tailored drug treatments for epileptic patients.

Materials and methods

A comprehensive literature search was conducted utilizing various databases, including PubMed, Ebscohost, Medline, and the National Library of Medicine, using a predetermined search strategy. The authors focused on articles that addressed the role of personalized micro-physiological systems in individual drug responses and articles that discussed different types of epilepsy, diagnosis, and current treatment options. Additionally, articles that explored the components and design considerations of micro-physiological systems were reviewed to identify challenges and opportunities in drug development for challenging epilepsy cases.

Results

The micro-physiological system offers a more accurate and cost-effective alternative to traditional models for assessing drug effects, toxicities, and disease mechanisms. Nevertheless, designing patient-specific models presents critical considerations, including the integration of analytical biosensors and patient-derived cells, while addressing regulatory, material, and biological complexities. Material selection, standardization, integration of vascular systems, cost efficiency, real-time monitoring, and ethical considerations are also crucial to the successful use of this technology in drug development.

Conclusion

The future of organ-on-chip technology holds great promise, with the potential to integrate artificial intelligence and machine learning for personalized treatment of epileptic patients.

Unraveling brain diseases: The promise of brain-on-a-chip models

Brain disorders, encompassing a wide spectrum of neurological and psychiatric conditions, present a formidable challenge in modern medicine. Despite decades of research, the intricate complexity of the human brain still eludes comprehensive understanding, impeding the development of effective treatments. Recent advancements in microfluidics and tissue engineering have led to the development of innovative platforms known as "Brain-on-a-Chip" (BoC) i.e., advanced in vitro systems that aim to replicate the microenvironment of the brain with the highest possible fidelity. This technology offers a promising test-bed for studying brain disorders at the cellular and network levels, providing insights into disease mechanisms, drug screening, and, in perspective, the development of personalized therapeutic strategies. In this review, we provide an overview of the BoC models developed over the years to model and understand the onset and progression of some of the most severe neurological disorders in terms of incidence and debilitation (stroke, Parkinson's, Alzheimer's, and epilepsy). We also report some of the cutting-edge therapeutic approaches whose effects were evaluated by means of these technologies. Finally, we discuss potential challenges, and future perspectives of the BoC models.

Electrophysiological and morphological modulation of neuronal-glial network by breast cancer and nontumorigenic mammary cell conditioned medium

Breast cancer is a significant global health concern, with the overexpression of human epidermal growth factor receptor 2 (HER2/ERBB2) being a driver oncogene in 20%-30% of cases. Indeed, HER2/ERBB2 plays a crucial role in regulating cell growth, differentiation, and survival via a complex signaling network. Overexpression of HER2/ERBB2 is associated with more aggressive behavior and increased risk of brain metastases, which remains a significant clinical challenge for treatment. Recent research has highlighted the role of breast cancer secretomes in promoting tumor progression, including excessive proliferation, immune invasion, and resistance to anti-cancer therapy, and their potential as cancer biomarkers. In this study, we investigated the impact of ERBB2+ breast cancer SKBR-3 cell line compared with MCF10-A mammary non-tumorigenic cell conditioned medium on the electrophysiological activity and morphology of neural networks derived from neurons differentiated from human induced pluripotent stem cells. Our findings provide evidence of active modulation of neuronal-glial networks by SKBR-3 and MCF10-A conditioned medium. These results provide insights into the complex interactions between breast cancer cells and the surrounding microenvironment. Further research is necessary to identify the specific factors within breast cancer conditioned medium that mediate these effects and to develop targeted therapies that disrupt this interaction.

Ensemble learning and ground-truth validation of synaptic connectivity inferred from spike trains

Probing the architecture of neuronal circuits and the principles that underlie their functional organization remains an important challenge of modern neurosciences. This holds true, in particular, for the inference of neuronal connectivity from large-scale extracellular recordings. Despite the popularity of this approach and a number of elaborate methods to reconstruct networks, the degree to which synaptic connections can be reconstructed from spike-train recordings alone remains controversial. Here, we provide a framework to probe and compare connectivity inference algorithms, using a combination of synthetic ground-truth and in vitro data sets, where the connectivity labels were obtained from simultaneous high-density microelectrode array (HD-MEA) and patch-clamp recordings. We find that reconstruction performance critically depends on the regularity of the recorded spontaneous activity, i.e., their dynamical regime, the type of connectivity, and the amount of available spike-train data. We therefore introduce an ensemble artificial neural network (eANN) to improve connectivity inference. We train the eANN on the validated outputs of six established inference algorithms and show how it improves network reconstruction accuracy and robustness. Overall, the eANN demonstrated strong performance across different dynamical regimes, worked well on smaller datasets, and improved the detection of synaptic connectivity, especially inhibitory connections. Results indicated that the eANN also improved the topological characterization of neuronal networks. The presented methodology contributes to advancing the performance of inference algorithms and facilitates our understanding of how neuronal activity relates to synaptic connectivity.

Microfluidic Brain-on-a-Chip: From Key Technology to System Integration and Application

As an ideal in vitro model, brain-on-chip (BoC) is an important tool to comprehensively elucidate brain characteristics. However, the in vitro model for the definition scope of BoC has not been universally recognized. In this review, BoC is divided into brain cells-on-a- chip, brain slices-on-a-chip, and brain organoids-on-a-chip according to the type of culture on the chip. Although these three microfluidic BoCs are constructed in different ways, they all use microfluidic chips as carrier tools. This method can better meet the needs of maintaining high culture activity on a chip for a long time. Moreover, BoC has successfully integrated cell biology, the biological material platform technology of microenvironment on a chip, manufacturing technology, online detection technology on a chip, and so on, enabling the chip to present structural diversity and high compatibility to meet different experimental needs and expand the scope of applications. Here, the relevant core technologies, challenges, and future development trends of BoC are summarized.

Single neurons on microelectrode array chip: manipulation and analyses

Chips-based platforms intended for single-cell manipulation are considered powerful tools to analyze intercellular interactions and cellular functions. Although the conventional cell co-culture models could investigate cell communication to some extent, the role of a single cell requires further analysis. In this study, a precise intercellular interaction model was built using a microelectrode array [microelectrode array (MEA)]-based and dielectrophoresis-driven single-cell manipulation chip. The integrated platform enabled precise manipulation of single cells, which were either trapped on or transferred between electrodes. Each electrode was controlled independently to record the corresponding cellular electrophysiology. Multiple parameters were explored to investigate their effects on cell manipulation including the diameter and depth of microwells, the geometry of cells, and the voltage amplitude of the control signal. Under the optimized microenvironment, the chip was further evaluated using 293T and neural cells to investigate the influence of electric field on cells. An examination of the inappropriate use of electric fields on cells revealed the occurrence of oncosis. In the end of the study, electrophysiology of single neurons and network of neurons, both differentiated from human induced pluripotent stem cells (iPSC), was recorded and compared to demonstrate the functionality of the chip. The obtained preliminary results extended the nature growing model to the controllable level, satisfying the expectation of introducing more elaborated intercellular interaction models.

Multiple neuron clusters on Micro-Electrode Arrays as an in vitro model of brain network

Understanding the brain functioning is essential for governing brain processes with the aim of managing pathological network dysfunctions. Due to the morphological and biochemical complexity of the central nervous system, the development of general models with predictive power must start from in vitro brain network engineering. In the present work, we realized a micro-electrode array (MEA)-based in vitro brain network and studied its emerging dynamical properties. We obtained four-neuron-clusters (4N) assemblies by plating rat embryo cortical neurons on 60-electrode MEA with cross-shaped polymeric masks and compared the emerging dynamics with those of sister single networks (1N). Both 1N and 4N assemblies exhibited spontaneous electrical activity characterized by spiking and bursting signals up to global activation by means of network bursts. Data revealed distinct patterns of network activity with differences between 1 and 4N. Rhythmic network bursts and dominant initiator clusters suggested pacemaker activities in both assembly types, but the propagation of activation sequences was statistically influenced by the assembly topology. We proved that this rhythmic activity was ivabradine sensitive, suggesting the involvement of hyperpolarization-activated cyclic nucleotide-gated (HCN) channels, and propagated across the real clusters of 4N, or corresponding virtual clusters of 1N, with dominant initiator clusters, and nonrandom cluster activation sequences. The occurrence of nonrandom series of identical activation sequences in 4N revealed processes possibly ascribable to neuroplasticity. Hence, our multi-network dissociated cortical assemblies suggest the relevance of pacemaker neurons as essential elements for generating brain network electrophysiological patterns; indeed, such evidence should be considered in the development of computational models for envisaging network behavior both in physiological and pathological conditions.

Portrait of intense communications within microfluidic neural networks

In vitro model networks could provide cellular models of physiological relevance to reproduce and investigate the basic function of neural circuits on a chip in the laboratory. Several tools and methods have been developed since the past decade to build neural networks on a chip; among them, microfluidic circuits appear to be a highly promising approach. One of the numerous advantages of this approach is that it preserves stable somatic and axonal compartments over time due to physical barriers that prevent the soma from exploring undesired areas and guide neurites along defined pathways. As a result, neuron compartments can be identified and isolated, and their interconnectivity can be modulated to build a topological neural network (NN). Here, we have assessed the extent to which the confinement imposed by the microfluidic environment can impact cell development and shape NN activity. Toward that aim, microelectrode arrays have enabled the monitoring of the short- and mid-term evolution of neuron activation over the culture period at specific locations in organized (microfluidic) and random (control) networks. In particular, we have assessed the spike and burst rate, as well as the correlations between the extracted spike trains over the first stages of maturation. This study enabled us to observe intense neurite communications that would have been weaker and more delayed within random networks; the spiking rate, burst and correlations being reinforced over time in terms of number and amplitude, exceeding the electrophysiological features of standard cultures. Beyond the enhanced detection efficiency that was expected from the microfluidic channels, the confinement of cells seems to reinforce neural communications and cell development throughout the network.

Building blocks of microphysiological system to model physiology and pathophysiology of human heart

Microphysiological systems (MPS) are drawing increasing interest from academia and from biomedical industry due to their improved capability to capture human physiology. MPS offer an advanced in vitro platform that can be used to study human organ and tissue level functions in health and in diseased states more accurately than traditional single cell cultures or even animal models. Key features in MPS include microenvironmental control and monitoring as well as high biological complexity of the target tissue. To reach these qualities, cross-disciplinary collaboration from multiple fields of science is required to build MPS. Here, we review different areas of expertise and describe essential building blocks of heart MPS including relevant cardiac cell types, supporting matrix, mechanical stimulation, functional measurements, and computational modelling. The review presents current methods in cardiac MPS and provides insights for future MPS development with improved recapitulation of human physiology.

Progress in Nano-Biosensors for Non-Invasive Monitoring of Stem Cell Differentiation

Non-invasive, non-destructive, and label-free sensing techniques are required to monitor real-time stem cell differentiation. However, conventional analysis methods, such as immunocytochemistry, polymerase chain reaction, and Western blot, involve invasive processes and are complicated and time-consuming. Unlike traditional cellular sensing methods, electrochemical and optical sensing techniques allow non-invasive qualitative identification of cellular phenotypes and quantitative analysis of stem cell differentiation. In addition, various nano- and micromaterials with cell-friendly properties can greatly improve the performance of existing sensors. This review focuses on nano- and micromaterials that have been reported to improve sensing capabilities, including sensitivity and selectivity, of biosensors towards target analytes associated with specific stem cell differentiation. The information presented aims to motivate further research into nano-and micromaterials with advantageous properties for developing or improving existing nano-biosensors to achieve the practical evaluation of stem cell differentiation and efficient stem cell-based therapies.

Biosensor integrated brain-on-a-chip platforms: Progress and prospects in clinical translation

Because of the brain's complexity, developing effective treatments for neurological disorders is a formidable challenge. Research efforts to this end are advancing as in vitro systems have reached the point that they can imitate critical components of the brain's structure and function. Brain-on-a-chip (BoC) was first used for microfluidics-based systems with small synthetic tissues but has expanded recently to include in vitro simulation of the central nervous system (CNS). Defining the system's qualifying parameters may improve the BoC for the next generation of in vitro platforms. These parameters show how well a given platform solves the problems unique to in vitro CNS modeling (like recreating the brain's microenvironment and including essential parts like the blood-brain barrier (BBB)) and how much more value it offers than traditional cell culture systems. This review provides an overview of the practical concerns of creating and deploying BoC systems and elaborates on how these technologies might be used. Not only how advanced biosensing technologies could be integrated with BoC system but also how novel approaches will automate assays and improve point-of-care (PoC) diagnostics and accurate quantitative analyses are discussed. Key challenges providing opportunities for clinical translation of BoC in neurodegenerative disorders are also addressed.

Recent Progress and Perspectives on Neural Chip Platforms Integrating PDMS-Based Microfluidic Devices and Microelectrode Arrays

Recent years have witnessed a spurt of progress in the application of the encoding and decoding of neural activities to drug screening, diseases diagnosis, and brain-computer interactions. To overcome the constraints of the complexity of the brain and the ethical considerations of in vivo research, neural chip platforms integrating microfluidic devices and microelectrode arrays have been raised, which can not only customize growth paths for neurons in vitro but also monitor and modulate the specialized neural networks grown on chips. Therefore, this article reviews the developmental history of chip platforms integrating microfluidic devices and microelectrode arrays. First, we review the design and application of advanced microelectrode arrays and microfluidic devices. After, we introduce the fabrication process of neural chip platforms. Finally, we highlight the recent progress on this type of chip platform as a research tool in the field of brain science and neuroscience, focusing on neuropharmacology, neurological diseases, and simplified brain models. This is a detailed and comprehensive review of neural chip platforms. This work aims to fulfill the following three goals: (1) summarize the latest design patterns and fabrication schemes of such platforms, providing a reference for the development of other new platforms; (2) generalize several important applications of chip platforms in the field of neurology, which will attract the attention of scientists in the field; and (3) propose the developmental direction of neural chip platforms integrating microfluidic devices and microelectrode arrays.

In Vitro Tumor Models on Chip and Integrated Microphysiological Analysis Platform (MAP) for Life Sciences and High-Throughput Drug Screening

The evolution of preclinical in vitro cancer models has led to the emergence of human cancer-on-chip or microphysiological analysis platforms (MAPs). Although it has numerous advantages compared to other models, cancer-on-chip technology still faces several challenges such as the complexity of the tumor microenvironment and integrating multiple organs to be widely accepted in cancer research and therapeutics. In this review, we highlight the advancements in cancer-on-chip technology in recapitulating the vital biological features of various cancer types and their applications in life sciences and high-throughput drug screening. We present advances in reconstituting the tumor microenvironment and modeling cancer stages in breast, brain, and other types of cancer. We also discuss the relevance of MAPs in cancer modeling and precision medicine such as effect of flow on cancer growth and the short culture period compared to clinics. The advanced MAPs provide high-throughput platforms with integrated biosensors to monitor real-time cellular responses applied in drug development. We envision that the integrated cancer MAPs has a promising future with regard to cancer research, including cancer biology, drug discovery, and personalized medicine.

An Overview of In Vitro Biological Neural Networks for Robot Intelligence

In vitro biological neural networks (BNNs) interconnected with robots, so-called BNN-based neurorobotic systems, can interact with the external world, so that they can present some preliminary intelligent behaviors, including learning, memory, robot control, etc. This work aims to provide a comprehensive overview of the intelligent behaviors presented by the BNN-based neurorobotic systems, with a particular focus on those related to robot intelligence. In this work, we first introduce the necessary biological background to understand the 2 characteristics of the BNNs: nonlinear computing capacity and network plasticity. Then, we describe the typical architecture of the BNN-based neurorobotic systems and outline the mainstream techniques to realize such an architecture from 2 aspects: from robots to BNNs and from BNNs to robots. Next, we separate the intelligent behaviors into 2 parts according to whether they rely solely on the computing capacity (computing capacity-dependent) or depend also on the network plasticity (network plasticity-dependent), which are then expounded respectively, with a focus on those related to the realization of robot intelligence. Finally, the development trends and challenges of the BNN-based neurorobotic systems are discussed.

Human In Vitro Models of Epilepsy Using Embryonic and Induced Pluripotent Stem Cells

The challenges in making animal models of complex human epilepsy phenotypes with varied aetiology highlights the need to develop alternative disease models that can address the limitations of animal models by effectively recapitulating human pathophysiology. The advances in stem cell technology provide an opportunity to use human iPSCs to make disease-in-a-dish models. The focus of this review is to report the current information and progress in the generation of epileptic patient-specific iPSCs lines, isogenic control cell lines, and neuronal models. These in vitro models can be used to study the underlying pathological mechanisms of epilepsies, anti-seizure medication resistance, and can also be used for drug testing and drug screening with their isogenic control cell lines.

Biomedical Applications of Microfluidic Devices: A Review

Both passive and active microfluidic chips are used in many biomedical and chemical applications to support fluid mixing, particle manipulations, and signal detection. Passive microfluidic devices are geometry-dependent, and their uses are rather limited. Active microfluidic devices include sensors or detectors that transduce chemical, biological, and physical changes into electrical or optical signals. Also, they are transduction devices that detect biological and chemical changes in biomedical applications, and they are highly versatile microfluidic tools for disease diagnosis and organ modeling. This review provides a comprehensive overview of the significant advances that have been made in the development of microfluidics devices. We will discuss the function of microfluidic devices as micromixers or as sorters of cells and substances (e.g., microfiltration, flow or displacement, and trapping). Microfluidic devices are fabricated using a range of techniques, including molding, etching, three-dimensional printing, and nanofabrication. Their broad utility lies in the detection of diagnostic biomarkers and organ-on-chip approaches that permit disease modeling in cancer, as well as uses in neurological, cardiovascular, hepatic, and pulmonary diseases. Biosensor applications allow for point-of-care testing, using assays based on enzymes, nanozymes, antibodies, or nucleic acids (DNA or RNA). An anticipated development in the field includes the optimization of techniques for the fabrication of microfluidic devices using biocompatible materials. These developments will increase biomedical versatility, reduce diagnostic costs, and accelerate diagnosis time of microfluidics technology.

A Neural Sensor with a Nanocomposite Interface for the Study of Spike Characteristics of Hippocampal Neurons under Learning Training

Both the cellular- and population-level properties of involved neurons are essential for unveiling the learning and memory functions of the brain. To give equal attention to these two aspects, neural sensors based on microelectrode arrays (MEAs) have been in the limelight due to their noninvasive detection and regulation capabilities. Here, we fabricated a neural sensor using carboxylated graphene/3,4-ethylenedioxythiophene:polystyrenesulfonate (cGO/PEDOT:PSS), which is effective in sensing and monitoring neuronal electrophysiological activity in vitro for a long time. The cGO/PEDOT:PSS-modified microelectrodes exhibited a lower electrochemical impedance (7.26 ± 0.29 kΩ), higher charge storage capacity (7.53 ± 0.34 mC/cm²), and improved charge injection (3.11 ± 0.25 mC/cm²). In addition, their performance was maintained after 2 to 4 weeks of long-term cell culture and 50,000 stimulation pulses. During neural network training, the sensors were able to induce learning function in hippocampal neurons through precise electrical stimulation and simultaneously detect changes in neural activity at multiple levels. At the cellular level, not only were three kinds of transient responses to electrical stimulation sensed, but electrical stimulation was also found to affect inhibitory neurons more than excitatory neurons. As for the population level, changes in connectivity and firing synchrony were identified. The cGO/PEDOT:PSS-based neural sensor offers an excellent tool in brain function development and neurological disease treatment.

An Insight of Nanomaterials in Tissue Engineering from Fabrication to Applications

Tissue engineering is a research domain that deals with the growth of various kinds of tissues with the help of synthetic composites. With the culmination of nanotechnology and bioengineering, tissue engineering has emerged as an exciting domain. Recent literature describes its various applications in biomedical and biological sciences, such as facilitating the growth of tissue and organs, gene delivery, biosensor-based detection, etc. It deals with the development of biomimetics to repair, restore, maintain and amplify or strengthen several biological functions at the level of tissue and organs. Herein, the synthesis of nanocomposites based on polymers, along with their classification as conductive hydrogels and bioscaffolds, is comprehensively discussed. Furthermore, their implementation in numerous tissue engineering and regenerative medicine applications is also described. The limitations of tissue engineering are also discussed here. The present review highlights and summarizes the latest progress in the tissue engineering domain directed at functionalized nanomaterials.

Breakthroughs and Applications of Organ-on-a-Chip Technology

Organ-on-a-chip (OOAC) is an emerging technology based on microfluid platforms and in vitro cell culture that has a promising future in the healthcare industry. The numerous advantages of OOAC over conventional systems make it highly popular. The chip is an innovative combination of novel technologies, including lab-on-a-chip, microfluidics, biomaterials, and tissue engineering. This paper begins by analyzing the need for the development of OOAC followed by a brief introduction to the technology. Later sections discuss and review the various types of OOACs and the fabrication materials used. The implementation of artificial intelligence in the system makes it more advanced, thereby helping to provide a more accurate diagnosis as well as convenient data management. We introduce selected OOAC projects, including applications to organ/disease modelling, pharmacology, personalized medicine, and dentistry. Finally, we point out certain challenges that need to be surmounted in order to further develop and upgrade the current systems.

Coupling of in vitro Neocortical-Hippocampal Coculture Bursts Induces Different Spike Rhythms in Individual Networks

Brain-state alternation is important for long-term memory formation. Each brain state can be identified with a specific process in memory formation, e.g., encoding during wakefulness or consolidation during sleeping. The hippocampal-neocortical dialogue was proposed as a hypothetical framework for systems consolidation, which features different cross-frequency couplings between the hippocampus and distributed neocortical regions in different brain states. Despite evidence supporting this hypothesis, little has been reported about how information is processed with shifts in brain states. To address this gap, we developed an in vitro neocortical-hippocampal coculture model to study how activity coupling can affect connections between coupled networks. Neocortical and hippocampal neurons were cultured in two different compartments connected by a micro-tunnel structure. The network activity of the coculture model was recorded by microelectrode arrays underlying the substrate. Rhythmic bursting was observed in the spontaneous activity and electrical evoked responses. Rhythmic bursting activity in one compartment could couple to that in the other via axons passing through the micro-tunnels. Two types of coupling patterns were observed: slow-burst coupling (neocortex at 0.1–0.5 Hz and hippocampus at 1 Hz) and fast burst coupling (neocortex at 20–40 Hz and hippocampus at 4–10 Hz). The network activity showed greater synchronicity in the slow-burst coupling, as indicated by changes in the burstiness index. Network synchronicity analysis suggests the presence of different information processing states under different burst activity coupling patterns. Our results suggest that the hippocampal-neocortical coculture model possesses multiple modes of burst activity coupling between the cortical and hippocampal parts. With the addition of external stimulation, the neocortical-hippocampal network model we developed can elucidate the influence of state shifts on information processing.

Human iPSC Modeling of Genetic Febrile Seizure Reveals Aberrant Molecular and Physiological Features Underlying an Impaired Neuronal Activity

Mutations in SCN1A gene, encoding the voltage-gated sodium channel (VGSC) NaV1.1, are widely recognized as a leading cause of genetic febrile seizures (FS), due to the decrease in the Na+ current density, mainly affecting the inhibitory neuronal transmission. Here, we generated induced pluripotent stem cells (iPSCs)-derived neurons (idNs) from a patient belonging to a genetically well-characterized Italian family, carrying the c.434T > C mutation in SCN1A gene (hereafter SCN1AM145T). A side-by-side comparison of diseased and healthy idNs revealed an overall maturation delay of SCN1AM145T cells. Membranes isolated from both diseased and control idNs were injected into Xenopus oocytes and both GABA and AMPA currents were successfully recorded. Patch-clamp measurements on idNs revealed depolarized action potential for SCN1AM145T, suggesting a reduced excitability. Expression analyses of VGSCs and chloride co-transporters NKCC1 and KCC2 showed a cellular “dysmaturity” of mutated idNs, strengthened by the high expression of SCN3A, a more fetal-like VGSC isoform, and a high NKCC1/KCC2 ratio, in mutated cells. Overall, we provide strong evidence for an intrinsic cellular immaturity, underscoring the role of mutant NaV1.1 in the development of FS. Furthermore, our data are strengthening previous findings obtained using transfected cells and recordings on human slices, demonstrating that diseased idNs represent a powerful tool for personalized therapy and ex vivo drug screening for human epileptic disorders.

Comparative microelectrode array data of the functional development of hPSC-derived and rat neuronal networks

We present a dataset of microelectrode array (MEA) recordings from human pluripotent stem cell (hPSC)-derived and rat embryonic cortical neurons during their in vitro maturation. The data were prepared to assess extracellularly recorded spontaneous activity and to compare the functional development of these neuronal networks. In addition to recordings of spontaneous activity, we provide pharmacological responses of hPSC-derived and rat cortical cultures at their mature stage. Together with the recorded electrode raw data, we share the analysis code to form a comprehensive dataset including spike times, spike waveforms, burst activity and network synchronization metrics calculated with two different connectivity estimators. Moreover, we provide the analysis code that produced the key scientific findings published previously with this dataset. This large dataset enables investigation of the functional aspects of maturing cortical neuronal networks and provides substantial parameters to assess the differences and similarities between hPSC-derived and rat cortical networks in vitro. This publicly available dataset will be beneficial, especially for experimental and computational neuroscientists.

Measurement(s)	extracellular electrophysiological activity
Technology Type(s)	microelectrode array
Factor Type(s)	days in vitro • dosage
Sample Characteristic - Organism	hPSC-derived neuronal cultures • rat neuronal cultures
Sample Characteristic - Environment	functional development • pharmacological response

Human Neurons Form Axon-Mediated Functional Connections with Human Cardiomyocytes in Compartmentalized Microfluidic Chip

The cardiac autonomic nervous system (cANS) regulates cardiac function by innervating cardiac tissue with axons, and cardiomyocytes (CMs) and neurons undergo comaturation during the heart innervation in embryogenesis. As cANS is essential for cardiac function, its dysfunctions might be fatal; therefore, cardiac innervation models for studying embryogenesis, cardiac diseases, and drug screening are needed. However, previously reported neuron-cardiomyocyte (CM) coculture chips lack studies of functional neuron–CM interactions with completely human-based cell models. Here, we present a novel completely human cell-based and electrophysiologically functional cardiac innervation on a chip in which a compartmentalized microfluidic device, a 3D3C chip, was used to coculture human induced pluripotent stem cell (hiPSC)-derived neurons and CMs. The 3D3C chip enabled the coculture of both cell types with their respective culture media in their own compartments while allowing the neuronal axons to traverse between the compartments via microtunnels connecting the compartments. Furthermore, the 3D3C chip allowed the use of diverse analysis methods, including immunocytochemistry, RT-qPCR and video microscopy. This system resembled the in vivo axon-mediated neuron–CM interaction. In this study, the evaluation of the CM beating response during chemical stimulation of neurons showed that hiPSC-neurons and hiPSC-CMs formed electrophysiologically functional axon-mediated interactions.

Lab-on-Chip Microsystems for Ex Vivo Network of Neurons Studies: A Review

Increasing population is suffering from neurological disorders nowadays, with no effective therapy available to treat them. Explicit knowledge of network of neurons (NoN) in the human brain is key to understanding the pathology of neurological diseases. Research in NoN developed slower than expected due to the complexity of the human brain and the ethical considerations for in vivo studies. However, advances in nanomaterials and micro-/nano-microfabrication have opened up the chances for a deeper understanding of NoN ex vivo, one step closer to in vivo studies. This review therefore summarizes the latest advances in lab-on-chip microsystems for ex vivo NoN studies by focusing on the advanced materials, techniques, and models for ex vivo NoN studies. The essential methods for constructing lab-on-chip models are microfluidics and microelectrode arrays. Through combination with functional biomaterials and biocompatible materials, the microfluidics and microelectrode arrays enable the development of various models for ex vivo NoN studies. This review also includes the state-of-the-art brain slide and organoid-on-chip models. The end of this review discusses the previous issues and future perspectives for NoN studies.

Biomaterial-assisted biotherapy: A brief review of biomaterials used in drug delivery, vaccine development, gene therapy, and stem cell therapy

Biotherapy has recently become a hotspot research topic with encouraging prospects in various fields due to a wide range of treatments applications, as demonstrated in preclinical and clinical studies. However, the broad applications of biotherapy have been limited by critical challenges, including the lack of safe and efficient delivery systems and serious side effects. Due to the unique potentials of biomaterials, such as good biocompatibility and bioactive properties, biomaterial-assisted biotherapy has been demonstrated to be an attractive strategy. The biomaterial-based delivery systems possess sufficient packaging capacity and versatile functions, enabling a sustained and localized release of drugs at the target sites. Furthermore, the biomaterials can provide a niche with specific extracellular conditions for the proliferation, differentiation, attachment, and migration of stem cells, leading to tissue regeneration. In this review, the state-of-the-art studies on the applications of biomaterials in biotherapy, including drug delivery, vaccine development, gene therapy, and stem cell therapy, have been summarized. The challenges and an outlook of biomaterial-assisted biotherapies have also been discussed.

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Biomaterials possess unique advantages to improve the efficacy and safety of biotherapy.

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Various types of biomaterials can be used in a wide range of biotherapy.

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The functions of biomaterials can be tuned by changing their inherent properties or the surrounding environment.

Functional Characterization of Human Pluripotent Stem Cell-Derived Models of the Brain with Microelectrode Arrays

Human pluripotent stem cell (hPSC)-derived neuron cultures have emerged as models of electrical activity in the human brain. Microelectrode arrays (MEAs) measure changes in the extracellular electric potential of cell cultures or tissues and enable the recording of neuronal network activity. MEAs have been applied to both human subjects and hPSC-derived brain models. Here, we review the literature on the functional characterization of hPSC-derived two- and three-dimensional brain models with MEAs and examine their network function in physiological and pathological contexts. We also summarize MEA results from the human brain and compare them to the literature on MEA recordings of hPSC-derived brain models. MEA recordings have shown network activity in two-dimensional hPSC-derived brain models that is comparable to the human brain and revealed pathology-associated changes in disease models. Three-dimensional hPSC-derived models such as brain organoids possess a more relevant microenvironment, tissue architecture and potential for modeling the network activity with more complexity than two-dimensional models. hPSC-derived brain models recapitulate many aspects of network function in the human brain and provide valid disease models, but certain advancements in differentiation methods, bioengineering and available MEA technology are needed for these approaches to reach their full potential.

Building on a Solid Foundation: Adding Relevance and Reproducibility to Neurological Modeling Using Human Pluripotent Stem Cells

The brain is our most complex and least understood organ. Animal models have long been the most versatile tools available to dissect brain form and function; however, the human brain is highly distinct from that of standard model organisms. In addition to existing models, access to human brain cells and tissues is essential to reach new frontiers in our understanding of the human brain and how to intervene therapeutically in the face of disease or injury. In this review, we discuss current and developing culture models of human neural tissue, outlining advantages over animal models and key challenges that remain to be overcome. Our principal focus is on advances in engineering neural cells and tissue constructs from human pluripotent stem cells (PSCs), though primary human cell and slice culture are also discussed. By highlighting studies that combine animal models and human neural cell culture techniques, we endeavor to demonstrate that clever use of these orthogonal model systems produces more reproducible, physiological, and clinically relevant data than either approach alone. We provide examples across a range of topics in neuroscience research including brain development, injury, and cancer, neurodegenerative diseases, and psychiatric conditions. Finally, as testing of PSC-derived neurons for cell replacement therapy progresses, we touch on the advancements that are needed to make this a clinical mainstay.

Novel test strategies for in vitro seizure liability assessment

INTRODUCTION

The increasing incidence of mental illnesses and neurodegenerative diseases results in a high demand for drugs targeting the central nervous system (CNS). These drugs easily reach the CNS, have a high affinity for CNS targets, and are prone to cause seizures as an adverse drug reaction. Current seizure liability assessment heavily depends on in vivo or ex vivo animal models and is therefore ethically debated, labor intensive, expensive, and not always predictive for human risk.

AREAS COVERED

The demand for CNS drugs urges the development of alternative safety assessment strategies. Yet, the complexity of the CNS hampers reliable detection of compound-induced seizures. This review provides an overview of the requirements of in vitro seizure liability assays and highlights recent advances, including micro-electrode array (MEA) recordings using rodent and human cell models.

EXPERT OPINION

Successful and cost-effective replacement of in vivo and ex vivo models for seizure liability screening can reduce animal use for drug development, while increasing the predictive value of the assays, particularly if human cell models are used. However, these novel test strategies require further validation and standardization as well as additional refinements to better mimic the human in vivo situation and increase their predictive value.

Comprehensive Development in Organ-On-A-Chip Technology

The expeditious advancement in the organ on chip technology provided a phase change to the conventional in vitro tests used to evaluate absorption, distribution, metabolism, excretion (ADME) studies and toxicity assessments. The demand for an accurate predictive model for assessing toxicity and reducing the potential risk factors became the prime area of any drug delivery process. Researchers around the globe are welcoming the incorporation of organ-on-a-chips for ADME and toxicity evaluation. Organ-on-a-chip (OOC) is an interdisciplinary technology that evolved as a contemporary in vitro model for the pharmacokinetics and pharmacodynamics (PK-PD) studies of a proposed drug candidate in the pre-clinical phases of drug development. The OOC provides a platform that mimics the physiological functions occurring in the human body. The precise flow control systems and the rapid sample processing makes OOC more advanced than the conventional two-dimensional (2D) culture systems. The integration of various organs as in the multi organs-on-a-chip provides more significant ideas about the time and dose dependant effects occurring in the body when a new drug molecule is administered as part of the pre-clinical times. This review outlines the comprehensive development in the organ-on-a-chip technology, various OOC models and its drug development applications, toxicity evaluation and efficacy studies.

Microfluidics for Drug Development: From Synthesis to Evaluation

Drug development is a long process whose main content includes drug synthesis, drug delivery, and drug evaluation. Compared with conventional drug development procedures, microfluidics has emerged as a revolutionary technology in that it offers a miniaturized and highly controllable environment for bio(chemical) reactions to take place. It is also compatible with analytical strategies to implement integrated and high-throughput screening and evaluations. In this review, we provide a comprehensive summary of the entire microfluidics-based drug development system, from drug synthesis to drug evaluation. The challenges in the current status and the prospects for future development are also discussed. We believe that this review will promote communications throughout diversified scientific and engineering communities that will continue contributing to this burgeoning field.

Collective dynamics of neuronal activities in various modular networks

Modularity is a key feature of structural and functional brain networks. However, the association between the structure and function of modular brain networks has not been revealed. We constructed three types of modular cortical networks in vitro and investigated their neuronal activities. The modular networks comprising 4, 3, or 2 modules were constructed using polydimethylsiloxane (PDMS) microstructures fabricated directly on a multi-electrode array (MEA) without transfer. The 4-module network had the strongest modular connectivity, followed by the 3-module and 2-module networks. To investigate how neuronal activities were affected by the modular network structure, spontaneous neuronal activities were recorded on different days in vitro and analyzed based on spike amplitudes, network bursts, and the propagation properties of individual spikes. Different characteristics were observed depending on the network topology and modular connectivity. Moreover, when an electrode was stimulated by biphasic voltage pulses, bursts were elicited for the 4-module network, whereas spikes were elicited for the 3-module and 2-module networks. Direct fabrication of the PDMS microstructures on the MEA without transfer allows microscale construction of modular networks and high-density functional recording; therefore, the technique utilizing the PDMS microstructures can be applied to the systematic study of the dynamics of modular neuronal networks in vitro.