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Silicon-based microelectronics can scalably record and modulate neural activity at high spatiotemporal resolution, but their planar form factor poses challenges in targeting 3D neural structures. A method for fabricating tissue-penetrating 3D microelectrodes directly onto planar microelectronics using high-resolution 3D printing via 2-photon polymerization and scalable microfabrication technologies are presented. This approach enables customizable electrode shape, height, and positioning for precise targeting of neuron populations distributed in 3D. The effectiveness of this approach is demonstrated in tackling the critical challenge of interfacing with the retina-specifically, selectively targeting retinal ganglion cell (RGC) somas while avoiding the axon bundle layer. 6,600-microelectrode, 35 µm pitch, tissue-penetrating arrays are fabricated to obtain high-fidelity, high-resolution, and large-scale retinal recording that reveals little axonal interference, a capability previously undemonstrated. Confocal microscopy further confirms the precise placement of the microelectrodes. This technology can be a versatile solution for interfacing silicon microelectronics with neural structures at a large scale and cellular resolution., (© 2024 The Author(s). Advanced Science published by Wiley‐VCH GmbH.)

End-stage liver diseases have an increasing impact worldwide, exacerbated by the shortage of transplantable organs. Recognized as one of the promising solutions, tissue engineering aims at recreating functional tissues and organs in vitro . The integration of bioprinting technologies with biological 3D models, such as multi-cellular spheroids, has enabled the fabrication of tissue constructs that better mimic complex structures and in vivo functionality of organs. However, the lack of methods for large-scale production of homogeneous spheroids has hindered the upscaling of tissue fabrication. In this work, we introduce a fully automated platform, designed for high-throughput sorting of 3D spheroids based on label-free analysis of brightfield images. The compact platform is compatible with standard biosafety cabinets and includes a custom-made microscope and two fluidic systems that optimize single spheroid handling to enhance sorting speed. We use machine learning to classify spheroids based on their bioprinting compatibility. This approach enables complex morphological analysis, including assessing spheroid viability, without relying on invasive fluorescent labels. Furthermore, we demonstrate the efficacy of transfer learning for biological applications, for which acquiring large datasets remains challenging. Utilizing this platform, we efficiently sort mono-cellular and multi-cellular liver spheroids, the latter being used in bioprinting applications, and confirm that the sorting process preserves viability and functionality of the spheroids. By ensuring spheroid homogeneity, our sorting platform paves the way for standardized and scalable tissue fabrication, advancing regenerative medicine applications., Competing Interests: AlM is working at Kuglemeiers Ltd. developing and commercializing SP5D culture plates used in the context of this study. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Sampaio da Silva, Boos, Goldowsky, Blache, Schmid, Heinemann, Netsch, Luongo, Boder-Pasche, Weder, Pueyo Moliner, Samsom, Marsee, Schneeberger, Mirsaidi, Spee, Valentin, Hierlemann and Revol.)

With the use of high-density multi-electrode recording devices, electrophysiological signals resulting from action potentials of individual neurons can now be reliably detected on multiple adjacent recording electrodes. Spike sorting assigns these signals to putative neural sources. However, until now, spike sorting can only be performed after completion of the recording, preventing true real time usage of spike sorting algorithms. Utilizing the unique propagation patterns of action potentials along axons detected as high-fidelity sequential activations on adjacent electrodes, together with a convolutional neural network-based spike detection algorithm, we introduce RT-Sort (Real Time Sorting), a spike sorting algorithm that enables the sorted detection of action potentials within 7.5ms±1.5ms (mean±STD) after the waveform trough while the recording remains ongoing. RT-Sort's true real-time spike sorting capabilities enable closed loop experiments with latencies comparable to synaptic delay times. We show RT-Sort's performance on both Multi-Electrode Arrays as well as Neuropixels probes to exemplify RT-Sort's functionality on different types of recording hardware and electrode configurations., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 van der Molen et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Introduction: In recent years, high-density microelectrode arrays (HD-MEAs) have emerged as a valuable tool in preclinical research for characterizing the electrophysiology of human induced pluripotent stem-cell-derived cardiomyocytes (iPSC-CMs). HD-MEAs enable the capturing of both extracellular and intracellular signals on a large scale, while minimizing potential damage to the cell. However, despite technological advancements of HD-MEAs, there is a lack of effective data-analysis platforms that are capable of processing and analyzing the data, particularly in the context of cardiac arrhythmias and drug testing., Methods: To address this need, we introduce CardioMEA, a comprehensive data-analysis platform designed specifically for HD-MEA data that have been obtained from iPSCCMs. CardioMEA features scalable data processing pipelines and an interactive web-based dashboard for advanced visualization and analysis. In addition to its core functionalities, CardioMEA incorporates modules designed to discern crucial electrophysiological features between diseased and healthy iPSC-CMs. Notably, CardioMEA has the unique capability to analyze both extracellular and intracellular signals, thereby facilitating customized analyses for specific research tasks., Results and Discussion: We demonstrate the practical application of CardioMEA by analyzing electrophysiological signals from iPSC-CM cultures exposed to seven antiarrhythmic drugs. CardioMEA holds great potential as an intuitive, userfriendly platform for studying cardiac diseases and assessing drug effects., Competing Interests: AS received educational grants through his institution from Abbott, Bayer Healthcare, Biosense Webster, Biotronik, Boston Scientific, BMS/Pfizer, and Medtronic; and speaker/advisory board/consulting fees from Bayer Healthcare, Biotronik, Medtronic, Novartis, Pfizer, Stride Bio Inc., and Zoll Medical. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Lee, Duperrex, El-Battrawy, Hohn, Saguner, Duru, Emmenegger, Cyganek, Hierlemann and Ulusan.)

Bio-signal sensing is pivotal in medical bioelectronics. Traditional methods focus on high sampling rates, leading to large amounts of irrelevant data and high energy consumption. We introduce a self-clocked microelectrode array (MEA) that digitizes bio-signals at the pixel level by encoding changes as asynchronous digital address-events only when they exceed a threshold, significantly reducing off-chip data transmission. This novel MEA comprises a 64 × 64 electrode array, an asynchronous 2D-arbiter, and an Address-Event Representation (AER) communication block. Each pixel operates autonomously, monitoring voltage fluctuations from cellular activity and producing digital pulses for significant changes. Positive and negative signal changes are encoded as "up" and "down" events and are routed off-chip via the asynchronous arbiter. We present results from chip characterization and experimental measurements using electrogenic cells. Additionally, we interface the MEA to a mixed-signal neuromorphic processor, demonstrating a prototype for end-to-end event-based bio-signal sensing and processing., (© 2024. The Author(s).)

In computational neuroscience, multicompartment models are among the most biophysically realistic representations of single neurons. Constructing such models usually involves the use of the patch-clamp technique to record somatic voltage signals under different experimental conditions. The experimental data are then used to fit the many parameters of the model. While patching of the soma is currently the gold-standard approach to build multicompartment models, several studies have also evidenced a richness of dynamics in dendritic and axonal sections. Recording from the soma alone makes it hard to observe and correctly parameterize the activity of nonsomatic compartments. In order to provide a richer set of data as input to multicompartment models, we here investigate the combination of somatic patch-clamp recordings with recordings of high-density microelectrode arrays (HD-MEAs). HD-MEAs enable the observation of extracellular potentials and neural activity of neuronal compartments at subcellular resolution. In this work, we introduce a novel framework to combine patch-clamp and HD-MEA data to construct multicompartment models. We first validate our method on a ground-truth model with known parameters and show that the use of features extracted from extracellular signals, in addition to intracellular ones, yields models enabling better fits than using intracellular features alone. We also demonstrate our procedure using experimental data by constructing cell models from in vitro cell cultures. The proposed multimodal fitting procedure has the potential to augment the modeling efforts of the computational neuroscience community and provide the field with neuronal models that are more realistic and can be better validated., (© 2024 Alessio Paolo Buccino, Tanguy Damart, Julian Bartram, Darshan Mandge, Xiaohan Xue, Mickael Zbili, Tobias Gänswein, Aurélien Jaquier, Vishalini Emmenegger, Henry Markram, Andreas Hierlemann, Werner Van Geit. Published under a Creative Commons Attribution 4.0 International (CC BY 4.0) license.)

A growing consensus that the brain is a mechanosensitive organ is driving the need for tools that mechanically stimulate and simultaneously record the electrophysiological response of neurons within neuronal networks. Here we introduce a synchronized combination of atomic force microscopy, high-density microelectrode array and fluorescence microscopy to monitor neuronal networks and to mechanically characterize and stimulate individual neurons at piconewton force sensitivity and nanometre precision while monitoring their electrophysiological activity at subcellular spatial and millisecond temporal resolution. No correlation is found between mechanical stiffness and electrophysiological activity of neuronal compartments. Furthermore, spontaneously active neurons show exceptional functional resilience to static mechanical compression of their soma. However, application of fast transient (∼500 ms) mechanical stimuli to the neuronal soma can evoke action potentials, which depend on the anchoring of neuronal membrane and actin cytoskeleton. Neurons show higher responsivity, including bursts of action potentials, to slower transient mechanical stimuli (∼60 s). Moreover, transient and repetitive application of the same compression modulates the neuronal firing rate. Seemingly, neuronal networks can differentiate and respond to specific characteristics of mechanical stimulation. Ultimately, the developed multiparametric tool opens the door to explore manifold nanomechanobiological responses of neuronal systems and new ways of mechanical control., (© 2024. The Author(s).)

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., Competing Interests: The authors declare no competing interests., (Copyright: © 2024 Donner et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

The multifactorial nature of inflammatory bowel disease (IBD) necessitates reliable and practical experimental models to elucidate its etiology and pathogenesis. To model the intestinal microenvironment at the onset of IBD in vitro, it is important to incorporate relevant cellular and noncellular components before inducing stepwise pathogenic developments. A novel intestine-on-chip system for investigating multiple aspects of IBD's immunopathogenesis is presented. The system includes an array of tight and polarized barrier models formed from intestinal epithelial cells on an in-vivo-like subepithelial matrix within one week. The dynamic remodeling of the subepithelial matrix by cells or their secretome demonstrates the physiological relevance of the on-chip barrier models. The system design enables introduction of various immune cell types and inflammatory stimuli at specific locations in the same barrier model, which facilitates investigations of the distinct roles of each cell type in intestinal inflammation development. It is showed that inflammatory behavior manifests in an upregulated expression of inflammatory markers and cytokines (TNF-α). The neutralizing effect of the anti-inflammatory antibody Infliximab on levels of TNF-α and its inducible cytokines could be explicitly shown. Overall, an innovative approach to systematically developing a microphysiological system to comprehend immune-system-mediated disorders of IBD and to identify new therapeutic strategies is presented., (© 2024 The Authors. Advanced Healthcare Materials published by Wiley-VCH GmbH.)

Reproducible functional assays to study in vitro neuronal networks represent an important cornerstone in the quest to develop physiologically relevant cellular models of human diseases. Here, we introduce DeePhys, a MATLAB-based analysis tool for data-driven functional phenotyping of in vitro neuronal cultures recorded by high-density microelectrode arrays. DeePhys is a modular workflow that offers a range of techniques to extract features from spike-sorted data, allowing for the examination of functional phenotypes both at the individual cell and network levels, as well as across development. In addition, DeePhys incorporates the capability to integrate novel features and to use machine-learning-assisted approaches, which facilitates a comprehensive evaluation of pharmacological interventions. To illustrate its practical application, we apply DeePhys to human induced pluripotent stem cell-derived dopaminergic neurons obtained from both patients and healthy individuals and showcase how DeePhys enables phenotypic screenings., Competing Interests: Declaration of interests M.F. is a cofounder of MaxWell Biosystems AG, which commercializes HD-MEA technology. The other authors declare no competing interests., (Copyright © 2023 The Authors. Published by Elsevier Inc. All rights reserved.)

Human cellular models of neurodegeneration require reproducibility and longevity, which is necessary for simulating age-dependent diseases. Such systems are particularly needed for TDP-43 proteinopathies 1 , which involve human-specific mechanisms 2-5 that cannot be directly studied in animal models. Here, to explore the emergence and consequences of TDP-43 pathologies, we generated induced pluripotent stem cell-derived, colony morphology neural stem cells (iCoMoNSCs) via manual selection of neural precursors 6 . Single-cell transcriptomics and comparison to independent neural stem cells 7 showed that iCoMoNSCs are uniquely homogenous and self-renewing. Differentiated iCoMoNSCs formed a self-organized multicellular system consisting of synaptically connected and electrophysiologically active neurons, which matured into long-lived functional networks (which we designate iNets). Neuronal and glial maturation in iNets was similar to that of cortical organoids 8 . Overexpression of wild-type TDP-43 in a minority of neurons within iNets led to progressive fragmentation and aggregation of the protein, resulting in a partial loss of function and neurotoxicity. Single-cell transcriptomics revealed a novel set of misregulated RNA targets in TDP-43-overexpressing neurons and in patients with TDP-43 proteinopathies exhibiting a loss of nuclear TDP-43. The strongest misregulated target encoded the synaptic protein NPTX2, the levels of which are controlled by TDP-43 binding on its 3' untranslated region. When NPTX2 was overexpressed in iNets, it exhibited neurotoxicity, whereas correcting NPTX2 misregulation partially rescued neurons from TDP-43-induced neurodegeneration. Notably, NPTX2 was consistently misaccumulated in neurons from patients with amyotrophic lateral sclerosis and frontotemporal lobar degeneration with TDP-43 pathology. Our work directly links TDP-43 misregulation and NPTX2 accumulation, thereby revealing a TDP-43-dependent pathway of neurotoxicity., (© 2024. The Author(s).)

Neuronal firing sequences are thought to be the basic building blocks of neural coding and information broadcasting within the brain. However, when sequences emerge during neurodevelopment remains unknown. We demonstrate that structured firing sequences are present in spontaneous activity of human brain organoids and ex vivo neonatal brain slices from the murine somatosensory cortex. We observed a balance between temporally rigid and flexible firing patterns that are emergent phenomena in human brain organoids and early postnatal murine somatosensory cortex, but not in primary dissociated cortical cultures. Our findings suggest that temporal sequences do not arise in an experience-dependent manner, but are rather constrained by an innate preconfigured architecture established during neurogenesis. These findings highlight the potential for brain organoids to further explore how exogenous inputs can be used to refine neuronal circuits and enable new studies into the genetic mechanisms that govern assembly of functional circuitry during early human brain development., Competing Interests: Competing interests: All authors declare no competing interests.

Counteracting the overactivation of glucocorticoid receptors (GR) is an important therapeutic goal in stress-related psychiatry and beyond. The only clinically approved GR antagonist lacks selectivity and induces unwanted side effects. To complement existing tools of small-molecule-based inhibitors, we present a highly potent, catalytically-driven GR degrader, KH-103, based on proteolysis-targeting chimera technology. This selective degrader enables immediate and reversible GR depletion that is independent of genetic manipulation and circumvents transcriptional adaptations to inhibition. KH-103 achieves passive inhibition, preventing agonistic induction of gene expression, and significantly averts the GR's genomic effects compared to two currently available inhibitors. Application in primary-neuron cultures revealed the dependency of a glucocorticoid-induced increase in spontaneous calcium activity on GR. Finally, we present a proof of concept for application in vivo. KH-103 opens opportunities for a more lucid interpretation of GR functions with translational potential., (© 2023. The Author(s).)

Integrating flowing cells, such as immune cells or circulating tumour cells, within a microphysiological system is crucial for body-on-a-chip applications. However, ensuring unimpeded recirculation of cells is a significant challenge. Closed microfluidic devices have a no-slip boundary condition along channel walls and a defined chip geometry (laminar flow) that hinders the ability to freely control cell flow. Open microfluidic devices, where the bottom device boundary is an air-liquid interface (ALI), e.g. , hanging drop networks (HDNs), offer the advantage of an easily-actuatable fluid-phase geometry, where cells can either flow or stagnate. In this paper, we optimized a hanging-drop-integrated pneumatic-pump system for closed-loop recirculation of particles ( i.e. , beads or cells). Experiments with both beads and cells in cell culture medium initially resulted in particle stagnation, which was suggestive of a pseudo-no-slip boundary condition at the ALI. Transmission electron microscopy and dynamic light scattering measurements of the ALI suggested that aggregation of submicron-scale cell-culture-medium components is the cause of the pseudo-no-slip boundary condition. We used the finite element method to study the forces on particles at the ALI and to optimize HDN design (drop aperture) and operation (drop height) parameters. Based on this analysis, we report a phase diagram delineating the conditions for free flow or stagnation of particles at the ALI of hanging drops. Using our experimental setup with 3.5 mm drop apertures, we conducted particle flow experiments while actuating drop heights. We confirmed the ability to control the flow or stagnation of particles by actuating the height of hanging drops: a drop height over 300 μm led to particle stagnation and a drop height under 300 μm allowed for particle flow. This particle-flow control, combined with the ease of integrating scaffold-free organ models (microtissues or organoids) in HDNs, constitutes the basis for an experimental setup enabling the control of the residence time of single cells around 3D organ models.

Perception, thoughts, and actions are encoded by the coordinated activity of large neuronal populations spread over large areas. However, existing electrophysiological devices are limited by their scalability in capturing this cortex-wide activity. Here, we developed an electrode connector based on an ultra-conformable thin-film electrode array that self-assembles onto silicon microelectrode arrays enabling multithousand channel counts at a millimeter scale. The interconnects are formed using microfabricated electrode pads suspended by thin support arms, termed Flex2Chip. Capillary-assisted assembly drives the pads to deform toward the chip surface, and van der Waals forces maintain this deformation, establishing Ohmic contact. Flex2Chip arrays successfully measured extracellular action potentials ex vivo and resolved micrometer scale seizure propagation trajectories in epileptic mice. We find that seizure dynamics in absence epilepsy in the Scn8a +/- model do not have constant propagation trajectories.

CMOS neural interfaces are aimed at studying the electrical activity of neurons and may help to restore lost functions of the nervous system in the future. The central function of most neural interfaces is the detection of extracellular electrical potentials by means of numerous microelectrodes positioned in close vicinity to the neurons. Modern neural interfaces require compact low-power, low-noise readout circuits, capable of recording from thousands of electrodes simultaneously without excessive area consumption and heat dissipation. In this article, we propose a novel readout technique for neural interfaces. The readout is based on a voltage-controlled oscillator (VCO), the frequency of which is modulated by the input voltage. The novelty of this work lies in the postprocessing of the VCO output, which is based on generating digital timestamps that contain temporal information about the oscillation. This method is potentially advantageous, because it requires mostly digital circuitry, which is more scalable than analog circuitry. Furthermore, most of the digital circuitry required for VCO-timestamping can be shared among several VCOs, rendering the architecture efficient for multi-channel architectures. This article introduces the VCO-timestamping concept, including theoretical derivations and simulations, and presents measurements of a prototype fabricated in 0.18-μm CMOS technology. The measured input-referred noise in the 300 Hz-5 kHz band was 5.7 μV rms , and the prototype was able to detect pre-recorded extracellular action potentials.

Blood-brain-barrier (BBB) disruption has been associated with a variety of central-nervous-system diseases. In vitro BBB models enable to investigate how the barrier reacts to external injury events, commonly referred to as insults. Here, a human-cell-based BBB platform with integrated, transparent electrodes to monitor barrier tightness in real time at high resolution is presented. The BBB model includes human cerebral endothelial cells and primary pericytes and astrocytes in a 3D arrangement within a pump-free, open-microfluidic platform. With this platform, this study demonstrates that oxygen-glucose deprivation (OGD), which mimics the characteristics of an ischemic insult, induces a rapid remodeling of the cellular actin structures and subsequent morphological changes in the endothelial cells. High-resolution live imaging shows the formation of large actin stress-fiber bundles in the endothelial layer during OGD application, which ultimately leads to cell shrinkage and barrier breakage. Simultaneous electrical measurements evidence a rapid decrease of the barrier electrical resistance before the appearance of stress fibers, which indicates that the barrier function is compromised already before the appearance of drastic morphological changes. The results demonstrate that the BBB platform recapitulates the main barrier functions in vitro and can be used to investigate rapid reorganization of the BBB upon application of external stimuli., (© 2023 The Authors. Advanced Science published by Wiley-VCH GmbH.)

Modern Graph Neural Networks (GNNs) provide opportunities to study the determinants underlying the complex activity patterns of biological neuronal networks. In this study, we applied GNNs to a large-scale electrophysiological dataset of rodent primary neuronal networks obtained by means of high-density microelectrode arrays (HD-MEAs). HD-MEAs allow for long-term recording of extracellular spiking activity of individual neurons and networks and enable the extraction of physiologically relevant features at the single-neuron and population level. We employed established GNNs to generate a combined representation of single-neuron and connectivity features obtained from HD-MEA data, with the ultimate goal of predicting changes in single-neuron firing rate induced by a pharmacological perturbation. The aim of the main prediction task was to assess whether single-neuron and functional connectivity features, inferred under baseline conditions, were informative for predicting changes in neuronal activity in response to a perturbation with Bicuculline, a GABA A receptor antagonist. Our results suggest that the joint representation of node features and functional connectivity, extracted from a baseline recording, was informative for predicting firing rate changes of individual neurons after the perturbation. Specifically, our implementation of a GNN model with inductive learning capability (GraphSAGE) outperformed other prediction models that relied only on single-neuron features. We tested the generalizability of the results on two additional datasets of HD-MEA recordings-a second dataset with cultures perturbed with Bicuculline and a dataset perturbed with the GABA A receptor antagonist Gabazine. GraphSAGE models showed improved prediction accuracy over other prediction models. Our results demonstrate the added value of taking into account the functional connectivity between neurons and the potential of GNNs to study complex interactions between neurons., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Kim, Chen, Hornauer, Emmenegger, Bartram, Ronchi, Hierlemann, Schröter and Roqueiro.)

Despite increasing survival rates of pediatric leukemia patients over the past decades, the outcome of some leukemia subtypes has remained dismal. Drug sensitivity and resistance testing on patient-derived leukemia samples provide important information to tailor treatments for high-risk patients. However, currently used well-based drug screening platforms have limitations in predicting the effects of prodrugs, a class of therapeutics that require metabolic activation to become effective. To address this issue, a microphysiological drug-testing platform is developed that enables co-culturing of patient-derived leukemia cells, human bone marrow mesenchymal stromal cells, and human liver microtissues within the same microfluidic platform. This platform also enables to control the physical interaction between the diverse cell types. Herein, it is made possible to recapitulate hepatic prodrug activation of ifosfamide in their platform, which is very difficult in traditional well-based assays. By testing the susceptibility of primary patient-derived leukemia samples to the prodrug ifosfamide, sample-specific sensitivities to ifosfamide in primary leukemia samples are identified. The microfluidic platform is found to enable the recapitulation of physiologically relevant conditions and the testing of prodrugs including short-lived and unstable metabolites. The platform holds great potential for clinical translation and precision chemotherapy selection., (© 2023 The Authors. Advanced Healthcare Materials published by Wiley-VCH GmbH.)

Chimeric antigen receptors (CARs) consist of an antigen-binding region fused to intracellular signaling domains, enabling customized T cell responses against targets. Despite their major role in T cell activation, effector function and persistence, only a small set of immune signaling domains have been explored. Here we present speedingCARs, an integrated method for engineering CAR T cells via signaling domain shuffling and pooled functional screening. Leveraging the inherent modularity of natural signaling domains, we generate a library of 180 unique CAR variants genomically integrated into primary human T cells by CRISPR-Cas9. In vitro tumor cell co-culture, followed by single-cell RNA sequencing (scRNA-seq) and single-cell CAR sequencing (scCAR-seq), enables high-throughput screening for identifying several variants with tumor killing properties and T cell phenotypes markedly different from standard CARs. Mapping of the CAR scRNA-seq data onto that of tumor infiltrating lymphocytes further helps guide the selection of variants. These results thus help expand the CAR signaling domain combination space, and supports speedingCARs as a tool for the engineering of CARs for potential therapeutic development., (© 2022. The Author(s).)

To enable accurate, high-throughput and longer-term studies of the immunopathogenesis of type 1 diabetes (T1D), we established three in-vitro islet-immune injury models by culturing spheroids derived from primary human islets with proinflammatory cytokines, activated peripheral blood mononuclear cells or HLA-A2-restricted preproinsulin-specific cytotoxic T lymphocytes. In all models, β-cell function declined as manifested by increased basal and decreased glucose-stimulated insulin release (GSIS), and decreased intracellular insulin content. Additional hallmarks of T1D progression such as loss of the first-phase insulin response (FFIR), increased proinsulin-to-insulin ratios, HLA-class I expression, and inflammatory cytokine release were also observed. Using these models, we show that liraglutide, a glucagon-like peptide 1 receptor agonist, prevented loss of GSIS under T1D-relevant stress, by preserving the FFIR and decreasing immune cell infiltration and cytokine secretion. Our results corroborate that liraglutide mediates an anti-inflammatory effect that aids in protecting β-cells from the immune-mediated attack that leads to T1D., Competing Interests: Declaration of Competing Interest J.M.C., A.N., C.R., M.K., A.B., F.F. and A.T. are or were employees of InSphero AG, a company commercializing islet microtissues and relates services. B.Y. is a member of the management team of InSphero AG. M.G.v.H. is on the scientific advisory board of InSphero AG. C.B.G, F.F.K., J.W., N.P., and M.G.v.H. are employees of Novo Nordisk A/S, a company commercializing liraglutide and other GLP-1 RAs., (Copyright © 2022. Published by Elsevier Inc.)

Pharmaceutical compounds may have cardiotoxic properties, triggering potentially life-threatening arrhythmias. To investigate proarrhythmic effects of drugs, the patch clamp technique has been used as the gold standard for characterizing the electrophysiology of cardiomyocytes in vitro . However, the applicability of this technology for drug screening is limited, as it is complex to use and features low throughput. Recent studies have demonstrated that 3D-nanostructured electrodes enable to obtain intracellular signals from many cardiomyocytes in parallel; however, the tedious electrode fabrication and limited measurement duration still remain major issues for cardiotoxicity testing. Here, we demonstrate how porous Pt-black electrodes, arranged in high-density microelectrode arrays, can be used to record intracellular-like signals of cardiomyocytes at large scale repeatedly over an extended period of time. The developed technique, which yields highly parallelized electroporations using stimulation voltages around 1 V peak-to-peak amplitude, enabled intracellular-like recordings at high success rates without causing significant alteration in key electrophysiological features. In a proof-of-concept study, we investigated electrophysiological modulations induced by two clinically applied drugs, nifedipine and quinidine. As the obtained results were in good agreement with previously published data, we are confident that the developed technique has the potential to be routinely used in in vitro platforms for cardiotoxicity screening.

Despite being composed of highly plastic neurons with extensive positive feedback, the nervous system maintains stable overall function. To keep activity within bounds, it relies on a set of negative feedback mechanisms that can induce stabilizing adjustments and that are collectively termed "homeostatic plasticity." Recently, a highly excitable microdomain, located at the proximal end of the axon-the axon initial segment (AIS)-was found to exhibit structural modifications in response to activity perturbations. Though AIS plasticity appears to serve a homeostatic purpose, many aspects governing its expression and its functional role in regulating neuronal excitability remain elusive. A central challenge in studying the phenomenon is the rich heterogeneity of its expression (distal/proximal relocation, shortening, lengthening) and the variability of its functional role. A potential solution is to track AISs of a large number of neurons over time and attempt to induce structural plasticity in them. To this end, a promising approach is to use extracellular electrophysiological readouts to track a large number of neurons at high spatiotemporal resolution by means of high-density microelectrode arrays (HD-MEAs). However, an analysis framework that reliably identifies specific activity signatures that uniquely map on to underlying microstructural changes is missing. In this study, we assessed the feasibility of such a task and used the distal relocation of the AIS as an exemplary problem. We used sophisticated computational models to systematically explore the relationship between incremental changes in AIS positions and the specific consequences observed in simulated extracellular field potentials. An ensemble of feature changes in the extracellular fields that reliably characterize AIS plasticity was identified. We trained models that could detect these signatures with remarkable accuracy. Based on these findings, we propose a hybrid analysis framework that could potentially enable high-throughput experimental studies of activity-dependent AIS plasticity using HD-MEAs., Competing Interests: Conflict of interest The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Objective : Techniques to identify monosynaptic connections between neurons have been vital for neuroscience research, facilitating important advancements concerning network topology, synaptic plasticity, and synaptic integration, among others. Approach : Here, we introduce a novel approach to identify and monitor monosynaptic connections using high-resolution dendritic spine Ca 2+ imaging combined with simultaneous large-scale recording of extracellular electrical activity by means of high-density microelectrode arrays. Main results : We introduce an easily adoptable analysis pipeline that associates the imaged spine with its presynaptic unit and test it on in vitro recordings. The method is further validated and optimized by simulating synaptically-evoked spine Ca 2+ transients based on measured spike trains in order to obtain simulated ground-truth connections. Significance : The proposed approach offers unique advantages as (a) it can be used to identify monosynaptic connections with an accurate localization of the synapse within the dendritic tree, (b) it provides precise information of presynaptic spiking, and (c) postsynaptic spine Ca 2+ signals and, finally, (d) the non-invasive nature of the proposed method allows for long-term measurements. The analysis toolkit together with the rich data sets that were acquired are made publicly available for further exploration by the research community., (Creative Commons Attribution license.)

Human brain organoids replicate much of the cellular diversity and developmental anatomy of the human brain. However, the physiology of neuronal circuits within organoids remains under-explored. With high-density CMOS microelectrode arrays and shank electrodes, we captured spontaneous extracellular activity from brain organoids derived from human induced pluripotent stem cells. We inferred functional connectivity from spike timing, revealing a large number of weak connections within a skeleton of significantly fewer strong connections. A benzodiazepine increased the uniformity of firing patterns and decreased the relative fraction of weakly connected edges. Our analysis of the local field potential demonstrate that brain organoids contain neuronal assemblies of sufficient size and functional connectivity to co-activate and generate field potentials from their collective transmembrane currents that phase-lock to spiking activity. These results point to the potential of brain organoids for the study of neuropsychiatric diseases, drug action, and the effects of external stimuli upon neuronal networks., (© 2022. The Author(s).)

Microfluidic-drop networks consist of several stable drops-interconnected through microfluidic channels-in which organ models can be cultured long-term. Drop networks feature a versatile configuration and an air-liquid interface (ALI). This ALI provides ample oxygenation, rapid liquid turnover, passive degassing, and liquid-phase stability through capillary pressure. Mathematical modeling, e.g., by using computational fluid dynamics (CFD), is a powerful tool to design drop-based microfluidic devices and to optimize their operation. Although CFD is the most rigorous technique to model flow, it falls short in terms of computational efficiency. Alternatively, the hydraulic-electric analogy is an efficient "first-pass" method to explore the design and operation parameter space of microfluidic-drop networks. However, there are no direct electric analogs to a drop, due to the nonlinear nature of the capillary pressure of the ALI. Here, we present a circuit-based model of hanging- and standing-drop compartments. We show a phase diagram describing the nonlinearity of the capillary pressure of a hanging drop. This diagram explains how to experimentally ensure drop stability. We present a methodology to find flow rates and pressures within drop networks. Finally, we review several applications, where the method, outlined in this paper, was instrumental in optimizing design and operation.

Due to their label-free and noninvasive nature, impedance measurements have attracted increasing interest in biological research. Advances in microfabrication and integrated-circuit technology have opened a route to using large-scale microelectrode arrays for real-time, high-spatiotemporal-resolution impedance measurements of biological samples. In this review, we discuss different methods and applications of measuring impedance for cell and tissue analysis with a focus on impedance imaging with microelectrode arrays in in vitro applications. We first introduce how electrode configurations and the frequency range of the impedance analysis determine the information that can be extracted. We then delve into relevant circuit topologies that can be used to implement impedance measurements and their characteristic features, such as resolution and data-acquisition time. Afterwards, we detail design considerations for the implementation of new impedance-imaging devices. We conclude by discussing future fields of application of impedance imaging in biomedical research, in particular applications where optical imaging is not possible, such as monitoring of ex vivo tissue slices or microelectrode-based brain implants., Competing Interests: Conflicts of Interest The authors declare that there are no conflicts of interest regarding the publication of this article.

Many biomarkers including neurotransmitters are found in external body fluids, such as sweat or saliva, but at lower titration levels than they are present in blood. Efficient detection of such biomarkers thus requires, on the one hand, to use techniques offering high sensitivity, and, on the other hand, to use a miniaturized format to carry out diagnostics in a minimally invasive way. Here, we present the hybrid integration of bottom-up silicon-nanowire Schottky-junction FETs (SiNW SJ-FETs) with complementary-metal-oxide-semiconductor (CMOS) readout and amplification electronics to establish a robust biosensing platform with 32 × 32 aptasensor measurement sites at a 100 μm pitch. The applied hetero-junctions yield a selective biomolecular detection down to femtomolar concentrations. Selective and multi-site detection of dopamine is demonstrated at an outstanding sensitivity of ∼1 V/fM. The integrated platform offers great potential for detecting biomarkers at high dilution levels and could be applied, for example, to diagnosing neurodegenerative diseases or monitoring therapy progress based on patient samples, such as tear liquid, saliva, or eccrine sweat., Competing Interests: NS, TM, and WW were employed by NaMLab gGmbH. UF was employed by MaxWell Biosystems AG. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Sessi, Ibarlucea, Seichepine, Klinghammer, Ibrahim, Heinzig, Szabo, Mikolajick, Hierlemann, Frey, Weber, Baraban and Cuniberti.)

Objective: Neurons communicate with each other by sending action potentials (APs) through their axons. The velocity of axonal signal propagation describes how fast electrical APs can travel. This velocity can be affected in a human brain by several pathologies, including multiple sclerosis, traumatic brain injury and channelopathies. High-density microelectrode arrays (HD-MEAs) provide unprecedented spatio-temporal resolution to extracellularly record neural electrical activity. The high density of the recording electrodes enables to image the activity of individual neurons down to subcellular resolution, which includes the propagation of axonal signals. However, axon reconstruction, to date, mainly relies on manual approaches to select the electrodes and channels that seemingly record the signals along a specific axon, while an automated approach to track multiple axonal branches in extracellular action-potential recordings is still missing. Approach: In this article, we propose a fully automated approach to reconstruct axons from extracellular electrical-potential landscapes, so-called 'electrical footprints' of neurons. After an initial electrode and channel selection, the proposed method first constructs a graph based on the voltage signal amplitudes and latencies. Then, the graph is interrogated to extract possible axonal branches. Finally, the axonal branches are pruned, and axonal action-potential propagation velocities are computed. Main results: We first validate our method using simulated data from detailed reconstructions of neurons, showing that our approach is capable of accurately reconstructing axonal branches. We then apply the reconstruction algorithm to experimental recordings of HD-MEAs and show that it can be used to determine axonal morphologies and signal-propagation velocities at high throughput. Significance: We introduce a fully automated method to reconstruct axonal branches and estimate axonal action-potential propagation velocities using HD-MEA recordings. Our method yields highly reliable and reproducible velocity estimations, which constitute an important electrophysiological feature of neuronal preparations., (Creative Commons Attribution license.)

Schistosomiasis is a neglected tropical disease that affects over 200 million people annually. As the antischistosomal drug pipeline is currently empty, repurposing of compound libraries has become a source for accelerating drug development, which demands the implementation of high-throughput and efficient screening strategies. Here, we present a parallelized impedance-based platform for continuous and automated viability evaluation of Schistosoma mansoni schistosomula in 128 microwells during 72 h to identify antischistosomal hits in vitro . By initially screening 57 repurposed compounds against larvae, five drugs are identified, which reduce parasite viability by more than 70%. The activity profiles of the selected drugs are then investigated via real-time dose-response monitoring, and four compounds reveal high potency and rapid action, which renders them suitable candidates for follow-up tests against adult parasites. The study shows that our device is a reliable tool for real-time drug screening analysis of libraries to identify new promising therapeutics against schistosomiasis., Competing Interests: The authors declare no competing interests., (© 2022 The Authors.)

As 3D in vitro tissue models become more pervasive, their built-in nutrient, metabolite, compound, and waste gradients increase biological relevance at the cost of analysis simplicity. Investigating these gradients and the resulting metabolic heterogeneity requires invasive and time-consuming methods. An alternative is using electrochemical biosensors and measuring concentrations around the tissue model to obtain size-dependent metabolism data. With our hanging-drop-integrated enzymatic glucose biosensors, we conducted current measurements within hanging-drop compartments hosting spheroids formed from the human colorectal carcinoma cell line HCT116. We developed a physics-based mathematical model of analyte consumption and transport, considering (1) diffusion and enzymatic conversion of glucose to form hydrogen peroxide (H 2 O 2 ) by the glucose-oxidase-based hydrogel functionalization of our biosensors at the microscale; (2) H 2 O 2 oxidation at the electrode surface, leading to amperometric H 2 O 2 readout; (3) glucose diffusion and glucose consumption by cancer cells in a spherical tissue model at the microscale; (4) glucose and H 2 O 2 transport in our hanging-drop compartments at the macroscale; and (5) solvent evaporation, leading to glucose and H 2 O 2 upconcentration. Our model relates the measured currents to the glucose concentrations generating the currents. The low limit of detection of our biosensors (0.4 ± 0.1 μM), combined with our current-fitting method, enabled us to reveal glucose dynamics within our system. By measuring glucose dynamics in hanging-drop compartments populated by cancer spheroids of various sizes, we could infer glucose distributions within the spheroid, which will help translate in vitro 3D tissue model results to in vivo., Competing Interests: Conflict of interestThe authors declare no competing interests., (© The Author(s) 2022.)

Abstract: Studies have provided evidence that human cerebral organoids (hCOs) recapitulate fundamental milestones of early brain development, but many important questions regarding their functionality and electrophysiological properties persist. High-density microelectrode arrays (HD-MEAs) represent an attractive analysis platform to perform functional studies of neuronal networks at the cellular and network scale. Here, we use HD-MEAs to derive large-scale electrophysiological recordings from sliced hCOs. We record the activity of hCO slices over several weeks and probe observed neuronal dynamics pharmacologically. Moreover, we present results on how the obtained recordings can be spike-sorted and subsequently studied across scales. For example, we show how to track single neurons across several days on the HD-MEA and how to infer axonal action potential velocities. We also infer putative functional connectivity from hCO recordings. The introduced methodology will contribute to a better understanding of developing neuronal networks in brain organoids and provide new means for their functional characterization., Impact Statement: Human cerebral organoids (hCOs) represent an attractive in vitro model system to study key physiological mechanisms underlying early neuronal network formation in tissue with healthy or disease-related genetic backgrounds. Despite remarkable advances in the generation of brain organoids, knowledge on the functionality of their neuronal circuits is still scarce. Here, we used complementary metal-oxide-semiconductor (CMOS)-based high-density microelectrode arrays (HD-MEAs) to perform large-scale recordings from sliced hCOs over several weeks and quantified their activity across scales. Using single-cell and network metrics, we were able to probe aspects of hCO neurophysiology that are more difficult to obtain with other techniques, such as patch clamping (lower yield) and calcium imaging (lower temporal resolution). These metrics included, for example, extracellular action potential (AP) waveform features and axonal AP velocity at the cellular level, as well as functional connectivity at the network level. Analysis was enabled by the large sensing area and the high spatiotemporal resolution provided by HD-MEAs, which allowed recordings from hundreds of neurons and spike sorting of their activity. Our results demonstrate that HD-MEAs provide a multi-purpose platform for the functional characterization of hCOs, which will be key in improving our understanding of this model system and assessing its relevance for translational research., Supplementary Information: The online version contains supplementary material available at 10.1557/s43577-022-00282-w., Competing Interests: Conflict of interestAll authors declare that they have no competing interests., (© The Author(s) 2022.)

In extracellular neural electrophysiology, individual spikes have to be assigned to their cell of origin in a procedure called "spike sorting". Spike sorting is an unsupervised problem, since no ground-truth information is generally available. Here, we focus on improving spike sorting performance, particularly during periods of high synchronous activity or so-called "bursting". Bursting entails systematic changes in spike shapes and amplitudes and remains a challenge for current spike sorting schemes. We use realistic simulated bursting recordings of high-density micro-electrode arrays (HD-MEAs) and we present a fully automated algorithm based on template matching with a focus on recovering missed spikes during bursts. To compare and benchmark spike-sorting performance after applying our method, we used ground-truth information of simulated recordings. We show that our approach can be effective in improving spike sorting performance during bursting. Further validation with experimental recordings is necessary.

Understanding the pharmacokinetic/pharmacodynamic (PK/PD)-relationship of a drug candidate is key to determine effective, yet safe treatment regimens for patients. However, current testing strategies are inefficient in characterizing in vivo responses to fluctuating drug concentrations during multi-day treatment cycles. Methods based on animal models are resource-intensive and require time, while traditional in vitro cell-culturing methods usually do not provide temporally-resolved information on the effects of in vivo -like drug exposure scenarios. To address this issue, we developed a microfluidic system to 1) culture arrays of three-dimensional spheroids in vitro, to 2) apply specific dynamic drug exposure profiles, and to 3) in-situ analyze spheroid growth and the invoked drug effects in 3D by means of 2-photon microscopy at tissue and single-cell level. Spheroids of fluorescently-labeled T-47D breast cancer cells were monitored under perfusion-culture conditions at short time intervals over three days and exposed to either three 24 h-PK-cycles or a dose-matched constant concentration of the phosphatidylinositol 3-kinase inhibitor BYL719. While the overall efficacy of the two treatment regimens was similar, spheroids exposed to the PK profile displayed cycle-dependent oscillations between regression and regrowth. Spheroids treated with a constant BYL719 concentration regressed at a steady, albeit slower rate. At a single-cell level, the cell density in BYL719-treated spheroids oscillated in a concentration-dependent manner. Our system represents a versatile tool for in-depth preclinical characterization of PK/PD parameters, as it enables an evaluation of drug efficacy and/or toxicity under realistic exposure conditions., Competing Interests: Author OF was employed by the company InSphero AG. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Lohasz, Loretan, Sterker, Görlach, Renggli, Argast, Frey, Wiesmann, Wartmann, Rausch and Hierlemann.)

More than 20 years ago, electrical impedance spectroscopy (EIS) was proposed as a potential characterization method for flow cytometry. As the setup is comparably simple and the method is label-free, EIS has attracted considerable interest from the research community as a potential alternative to standard optical methods, such as fluorescence-activated cell sorting (FACS). However, until today, FACS remains by and large the laboratory standard with highly developed capabilities and broad use in research and clinical settings. Nevertheless, can EIS still provide a complement or alternative to FACS in specific applications? In this Perspective, we will give an overview of the current state of the art of EIS in terms of technologies and capabilities. We will then describe recent advances in EIS-based flow cytometry, compare the performance to that of FACS methods, and discuss potential prospects of EIS in flow cytometry., (© 2021 Author(s).)

Existing first-line cancer therapies often fail to cope with the heterogeneity and complexity of cancers, so that new therapeutic approaches are urgently needed. Among novel alternative therapies, adoptive cell therapy (ACT) has emerged as a promising cancer treatment in recent years. The limited clinical applications of ACT, despite its advantages over standard-of-care therapies, can be attributed to (i) time-consuming and cost-intensive procedures to screen for potent anti-tumor immune cells and the corresponding targets, (ii) difficulties to translate in-vitro and animal-derived in-vivo efficacies to clinical efficacy in humans, and (iii) the lack of systemic methods for the safety assessment of ACT. Suitable experimental models and testing platforms have the potential to accelerate the development of ACT. Immunocompetent microphysiological systems (iMPS) are microfluidic platforms that enable complex interactions of advanced tissue models with different immune cell types, bridging the gap between in-vitro and in-vivo studies. Here, we present a proof-of-concept iMPS that supports a triple culture of three-dimensional (3D) colorectal tumor microtissues, 3D cardiac microtissues, and human-derived natural killer (NK) cells in the same microfluidic network. Different aspects of tumor-NK cell interactions were characterized using this iMPS including: (i) direct interaction and NK cell-mediated tumor killing, (ii) the development of an inflammatory milieu through enrichment of soluble pro-inflammatory chemokines and cytokines, and (iii) secondary effects on healthy cardiac microtissues. We found a specific NK cell-mediated tumor-killing activity and elevated levels of tumor- and NK cell-derived chemokines and cytokines, indicating crosstalk and development of an inflammatory milieu. While viability and morphological integrity of cardiac microtissues remained mostly unaffected, we were able to detect alterations in their beating behavior, which shows the potential of iMPS for both, efficacy and early safety testing of new candidate ACTs., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Nguyen, Misun, Lohasz, Lee, Wang, Schroeder and Hierlemann.)

This article reports on a compact and low-power CMOS readout circuit for bioelectrical signals based on a second-order delta-sigma modulator. The converter uses a voltage-controlled, oscillator-based quantizer, achieving second-order noise shaping with a single opamp-less integrator and minimal analog circuitry. A prototype has been implemented using 0.18 μm CMOS technology and includes two different variants of the same modulator topology. The main modulator has been optimized for low-noise, neural-action-potential detection in the 300 Hz-6 kHz band, with an input-referred noise of 5.0 μV rms , and occupies an area of 0.0045 mm 2 . An alternative configuration features a larger input stage to reduce low-frequency noise, achieving 8.7 μV rms in the 1 Hz-10 kHz band, and occupies an area of 0.006 mm 2 . The modulator is powered at 1.8 V with an estimated power consumption of 3.5 μW.

To facilitate in situ comparative culturing of budding yeast cells in a precisely controlled microenvironment, we developed a microfluidic single-cell array (MiSCA) with 96 traps (16 rows × 6 columns) for single-cell immobilization. Through optimization of the distances between neighboring traps and the applied flow rates by using a hydraulic equivalent circuit of the fluidic network, yeast cells were delivered to each column of the array by laminar focused flows and reliably captured at the traps by hydrodynamic forces with about 90% efficiency of cell immobilization. Immobilized cells in different columns within the same device can then be cultured in parallel while being exposed to different media and compounds delivered by laminar flows. For biological validation of the comparative cell-culturing device, we used budding yeast that can express yellow fluorescent protein upon the addition of β-estradiol in cell-culturing medium. Experimental results show successful induction of fluorescence in cells immobilized in desired columns that have been dosed with β-estradiol. The MiSCA system allows for performing sets of experiments and control experiments in parallel in the same device, or for executing comparative experiments under well-defined laminar-perfusion conditions with different media, as well as in situ monitoring of dynamic cellular responses upon different analytical compounds or reagents for single-cell analysis., (Copyright © 2021 Elsevier B.V. All rights reserved.)

Electrophysiological research on neural networks and their activity focuses on the recording and analysis of large data sets that include information of thousands of neurons. CMOS microelectrode arrays (MEAs) feature thousands of electrodes at a spatial resolution on the scale of single cells and are, therefore, ideal tools to support neural-network research. Moreover, they offer high spatio-temporal resolution and signal to-noise ratio (SNR) to capture all features and subcellular resolution details of neuronal signaling. Here, we present a dual-mode (DM) MEA, which enables simultaneous: 1) full-frame readout from all electrodes and 2) high-SNR readout from an arbitrarily selectable subset of electrodes. The DM-MEA includes 19584 electrodes, 19584 full-frame recording channels with noise levels of 10.4 μ V rms in the action potential (AP) frequency band (300 Hz-5 kHz), 246 low-noise recording channels with noise levels of 3.0 μ V rms in the AP band and eight stimulation units. The capacity to simultaneously perform full-frame and high-SNR recordings endows the presented DM-MEA with great flexibility for various applications in neuroscience and pharmacology., Competing Interests: Conflict Of Interest U.F. is a co-founder of MaxWell Biosystems AG, Zürich, Switzerland.

Safety assessment of the effects of developmental toxicants on pregnant women is challenging, and systemic effects in embryo-maternal interactions are largely unknown. However, most developmental toxicity studies rely on animal trials, while in vitro platforms that recapitulate the maternal-placental-embryonic axis are missing. Here, the development of a dedicated microfluidic device for co-cultivation of a placental barrier and 3D embryoid bodies to enable systemic toxicity testing at the embryo-maternal interface is reported. The microfluidic platform features simple handling and recuperation of both tissue models, which facilitates post-hoc in-depth analysis at the tissue and single-cell level. Gravity-driven flow enables inter-tissue communication through the liquid phase as well as simple and robust operation and renders the platform parallelizable. As a proof of concept and to demonstrate platform use for systemic embryotoxicity testing in vitro, maternal exposure to plastic microparticles is emulated, and microparticle effects on the embryo-placental co-culture are investigated., (© 2021 The Authors. Advanced Biology published by Wiley-VCH GmbH.)

Schistosomiasis is a major neglected tropical disease with more than 200 million infections annually. Despite only one drug, praziquantel, being available, the drug pipeline against schistosomiasis is empty, and drug screening tools have limitations. We evaluated the potential of human liver microtissues (hLiMTs) in antischistosomal drug discovery. Because hLiMTs express all human P450 enzymes, they are an excellent tool to evaluate compounds' bioinactivation, bioactivation, and toxicity. To validate the metabolic conversion capacity of hLiMTs, we first quantified ( R )- and ( S )-praziquantel and the main metabolite trans -OH-praziquantel following incubation with 0.032-50 μM (0.01-15.62 μg/mL) praziquantel for up to 72 h by a validated LC-MS/MS method. We cocultured hLiMTs with newly transformed schistosomula (NTS) and evaluated the antischistosomal activity and cytotoxicity of three prodrugs terfenadine, tamoxifen citrate, and flutamide. HLiMTs converted 300-350 ng ( R )-praziquantel within 24 h into trans -OH-praziquantel. We observed changes in the IC 50 values for terfenadine, flutamide, and tamoxifen citrate in comparison to the standard NTS assay in vitro. Cytotoxicity was observed at high concentrations of flutamide and tamoxifen citrate. An in vitro platform containing hLiMTs could serve as an advanced drug screening tool for Schistosoma mansoni , providing information on reduced or increased activity and toxicity.

Islet perifusion systems can be used to monitor the highly dynamic insulin release of pancreatic islets in glucose-stimulated insulin secretion (GSIS) assays. Here, we present a new generation of the microfluidic hanging-drop-based islet perifusion platform that was developed to study the alterations in insulin secretion dynamics from single pancreatic islet microtissues at high temporal resolution. The platform was completely redesigned to increase experimental throughput and to reduce operational complexity. The experimental throughput was increased fourfold by implementing a network of interconnected hanging drops, which allows for performing GSIS assays with four individual islet microtissues in parallel with a sampling interval of 30 s. We introduced a self-regulating drop-height mechanism that enables continuous flow and maintains a constant liquid volume in the chip, which enables simple and robust operation. Upon glucose stimulation, reproducible biphasic insulin release was simultaneously observed from all islets in the system. The measured insulin concentrations showed low sample-to-sample variation as a consequence of precise liquid handling with stable drop volumes, equal flow rates in the channels, and accurately controlled sampling volumes in all four drops. The presented device will be a valuable tool in islet and diabetes research for studying dynamic insulin secretion from individual pancreatic islets., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Wu Jin, Rousset, Hierlemann and Misun.)

Recent advances in the field of cellular reprogramming have opened a route to studying the fundamental mechanisms underlying common neurological disorders. High-density microelectrode-arrays (HD-MEAs) provide unprecedented means to study neuronal physiology at different scales, ranging from network through single-neuron to subcellular features. In this work, HD-MEAs are used in vitro to characterize and compare human induced-pluripotent-stem-cell-derived dopaminergic and motor neurons, including isogenic neuronal lines modeling Parkinson's disease and amyotrophic lateral sclerosis. Reproducible electrophysiological network, single-cell and subcellular metrics are used for phenotype characterization and drug testing. Metrics, such as burst shape and axonal velocity, enable the distinction of healthy and diseased neurons. The HD-MEA metrics can also be used to detect the effects of dosing the drug retigabine to human motor neurons. Finally, it is shown that the ability to detect drug effects and the observed culture-to-culture variability critically depend on the number of available recording electrodes., (© 2021 Wiley-VCH GmbH.)

A major obstacle in the development of efficient therapies for progressive liver fibrosis is the lack of representative in vitro models of liver fibrosis to aid in understanding the mechanisms of the disease and to promote the development of pharmaceuticals. Our aim was to develop a relevant in vitro mouse liver fibrosis model, based on the central hypothesis that liver fibrosis in vitro cannot be studied using only hepatic stellate cells (HSCs)-the main producer of scar tissue during fibrosis-, but requires cultures in which at least hepatocytes are integrated. We established robust methods to generate co-culture spheroids from freshly isolated mouse hepatocytes and HSCs. Characteristics and functionality of these spheroids were analyzed by qPCR of cell-type specific markers, CYP induction and immunohistochemistry. Compound toxicity was determined by ATP-assays. Hepatocytes and HSCs maintained their cell-type specific marker expression over a 15-day culture period without major hepatocyte dedifferentiation or HSC activation. Exposure of spheroids to TGFβ can directly activate HSCs, while acetaminophen exposure mounts a hepatocyte damage dependent activation of HSCs. Pharmaceuticals with known anti-fibrotic properties, such as Valproic acid and Verteporfin, reduce HSC activation in response to hepatocyte damage in these cultures. A comparison between the fibrotic response of the spheroid co-cultures and in vivo activated HSCs showed that these 3D co-cultures are more representative than the commonly used 2D HSC monocultures. Finally, we showed that the 3D cultures can be integrated in microfluidic chips. We conclude that our hepatocyte-stellate cell-spheroid cultures are a robust in vitro model of liver fibrosis. This model could be used to further unravel the mechanism of HSC activation and facilitate the discovery of, or testing for novel anti-fibrotic compounds, as these spheroids better reproduce HSC in vivo activation compared to the more traditional 2D mono-culture models., (Copyright © 2020 Elsevier Ltd. All rights reserved.)

Drug-drug interactions (DDIs) occur when the pharmacological activity of one drug is altered by a second drug. As multimorbidity and polypharmacotherapy are becoming more common due to the increasing age of the population, the risk of DDIs is massively increasing. Therefore, in vitro testing methods are needed to capture such multiorgan events. Here, a scalable, gravity-driven microfluidic system featuring 3D microtissues (MTs) that represent different organs for the prediction of drug-drug interactions is used. Human liver microtissues (hLiMTs) are combined with tumor microtissues (TuMTs) and treated with drug combinations that are known to cause DDIs in vivo. The testing system is able to capture and quantify DDIs upon co-administration of the anticancer prodrugs cyclophosphamide or ifosfamide with the antiretroviral drug ritonavir. Dosage of ritonavir inhibits hepatic metabolization of the two prodrugs to different extents and decreases their efficacy in acting on TuMTs. The flexible MT compartment design of the system, the use of polystyrene as chip material, and the assembly of several chips in stackable plates offer the potential to significantly advance preclinical substance testing. The possibility of testing a broad variety of drug combinations to identify possible DDIs will improve the drug development process and increase patient safety., (© 2020 Wiley-VCH GmbH.)

Chronic imaging of neuronal networks in vitro has provided fundamental insights into mechanisms underlying neuronal function. Current labeling and optical imaging methods, however, cannot be used for continuous and long-term recordings of the dynamics and evolution of neuronal networks, as fluorescent indicators can cause phototoxicity. Here, we introduce a versatile platform for label-free, comprehensive and detailed electrophysiological live-cell imaging of various neurogenic cells and tissues over extended time scales. We report on a dual-mode high-density microelectrode array, which can simultaneously record in (i) full-frame mode with 19,584 recording sites and (ii) high-signal-to-noise mode with 246 channels. We set out to demonstrate the capabilities of this platform with recordings from primary and iPSC-derived neuronal cultures and tissue preparations over several weeks, providing detailed morpho-electrical phenotypic parameters at subcellular, cellular and network level. Moreover, we develop reliable analysis tools, which drastically increase the throughput to infer axonal morphology and conduction speed.

Microfabricated and microfluidic devices enable standardized handling, precise spatiotemporal manipulation of cells and liquids, and recapitulation of cellular environments, tissues, and organ-level biology. We asked researchers how these devices can make in vitro experiments more physiologically relevant., (Copyright © 2020. Published by Elsevier Inc.)

Human organoids recapitulating the cell-type diversity and function of their target organ are valuable for basic and translational research. We developed light-sensitive human retinal organoids with multiple nuclear and synaptic layers and functional synapses. We sequenced the RNA of 285,441 single cells from these organoids at seven developmental time points and from the periphery, fovea, pigment epithelium and choroid of light-responsive adult human retinas, and performed histochemistry. Cell types in organoids matured in vitro to a stable "developed" state at a rate similar to human retina development in vivo. Transcriptomes of organoid cell types converged toward the transcriptomes of adult peripheral retinal cell types. Expression of disease-associated genes was cell-type-specific in adult retina, and cell-type specificity was retained in organoids. We implicate unexpected cell types in diseases such as macular degeneration. This resource identifies cellular targets for studying disease mechanisms in organoids and for targeted repair in human retinas., Competing Interests: Declaration of Interests The authors declare no competing interests., (Copyright © 2020 The Author(s). Published by Elsevier Inc. All rights reserved.)