A 3D bioprinted hydrogel gut-on-chip with integrated electrodes for transepithelial electrical resistance (TEER) measurements.

Conventional gut-on-chip (GOC) models typically represent the epithelial layer of the gut tissue, neglecting other important components such as the stromal compartment and the extracellular matrix (ECM) that play crucial roles in maintaining intestinal barrier integrity and function. These models often employ hard, flat porous membranes for cell culture, thus failing to recapitulate the soft environment and complex 3D architecture of the intestinal mucosa. Alternatively, hydrogels have been recently introduced in GOCs as ECM analogs to support the co-culture of intestinal cells inin vivo-like configurations, and thus opening new opportunities in the organ-on-chip field. In this work, we present an innovative GOC device that includes a 3D bioprinted hydrogel channel replicating the intestinal villi architecture containing both the epithelial and stromal compartments of the gut mucosa. The bioprinted hydrogels successfully support both the encapsulation of fibroblasts and their co-culture with intestinal epithelial cells under physiological flow conditions. Moreover, we successfully integrated electrodes into the microfluidic system to monitor the barrier formation in real time via transepithelial electrical resistance measurements.

Concurrent functional ultrasound imaging with graphene-based DC-coupled electrophysiology as a platform to study slow brain signals and cerebral blood flow under control and pathophysiological brain states.

Current methodology used to investigate how shifts in brain states associated with regional cerebral blood volume (CBV) change in deep brain areas, are limited by either the spatiotemporal resolution of the CBV techniques, and/or compatibility with electrophysiological recordings; particularly in relation to spontaneous brain activity and the study of individual events. Additionally, infraslow brain signals (<0.1 Hz), including spreading depolarisations, DC-shifts and infraslow oscillations (ISO), are poorly captured by traditional AC-coupled electrographic recordings; yet these very slow brain signals can profoundly change CBV. To gain an improved understanding of how infraslow brain signals couple to CBV we present a new method for concurrent CBV with wide bandwidth electrophysiological mapping using simultaneous functional ultrasound imaging (fUS) and graphene-based field effect transistor (gFET) DC-coupled electrophysiological acquisitions. To validate the feasibility of this methodology visually-evoked neurovascular coupling (NVC) responses were examined. gFET recordings are not affected by concurrent fUS imaging, and epidural placement of gFET arrays within the imaging window did not deteriorate fUS signal quality. To examine directly the impact of infra-slow potential shifts on CBV, cortical spreading depolarisations (CSDs) were induced. A biphasic pattern of decreased, followed by increased CBV, propagating throughout the ipsilateral cortex, and a delayed decrease in deeper subcortical brain regions was observed. In a model of acute seizures, CBV oscillations were observed prior to seizure initiation. Individual seizures occurred on the rising phase of both infraslow brain signal and CBV oscillations. When seizures co-occurred with CSDs, CBV responses were larger in amplitude, with delayed CBV decreases in subcortical structures. Overall, our data demonstrate that gFETs are highly compatible with fUS and allow concurrent examination of wide bandwidth electrophysiology and CBV. This graphene-enabled technological advance has the potential to improve our understanding of how infraslow brain signals relate to CBV changes in control and pathological brain states.

Nanoporous graphene-based thin-film microelectrodes for in vivo high-resolution neural recording and stimulation.

One of the critical factors determining the performance of neural interfaces is the electrode material used to establish electrical communication with the neural tissue, which needs to meet strict electrical, electrochemical, mechanical, biological and microfabrication compatibility requirements. This work presents a nanoporous graphene-based thin-film technology and its engineering to form flexible neural interfaces. The developed technology allows the fabrication of small microelectrodes (25 µm diameter) while achieving low impedance (∼25 kΩ) and high charge injection (3-5 mC cm-2). In vivo brain recording performance assessed in rodents reveals high-fidelity recordings (signal-to-noise ratio >10 dB for local field potentials), while stimulation performance assessed with an intrafascicular implant demonstrates low current thresholds (<100 µA) and high selectivity (>0.8) for activating subsets of axons within the rat sciatic nerve innervating tibialis anterior and plantar interosseous muscles. Furthermore, the tissue biocompatibility of the devices was validated by chronic epicortical (12 week) and intraneural (8 week) implantation. This work describes a graphene-based thin-film microelectrode technology and demonstrates its potential for high-precision and high-resolution neural interfacing.

Recording physiological and pathological cortical activity and exogenous electric fields using graphene microtransistor arrays in vitro.

Graphene-based solution-gated field-effect transistors (gSGFETs) allow the quantification of the brain's full-band signal. Extracellular alternating current (AC) signals include local field potentials (LFP, population activity within a reach of hundreds of micrometers), multiunit activity (MUA), and ultimately single units. Direct current (DC) potentials are slow brain signals with a frequency under 0.1 Hz, and commonly filtered out by conventional AC amplifiers. This component conveys information about what has been referred to as "infraslow" activity. We used gSGFET arrays to record full-band patterns from both physiological and pathological activity generated by the cerebral cortex. To this end, we used an in vitro preparation of cerebral cortex that generates spontaneous rhythmic activity, such as that occurring in slow wave sleep. This examination extended to experimentally induced pathological activities, including epileptiform discharges and cortical spreading depression. Validation of recordings obtained via gSGFETs, including both AC and DC components, was accomplished by cross-referencing with well-established technologies, thereby quantifying these components across different activity patterns. We then explored an additional gSGFET potential application, which is the measure of externally induced electric fields such as those used in therapeutic neuromodulation in humans. Finally, we tested the gSGFETs in human cortical slices obtained intrasurgically. In conclusion, this study offers a comprehensive characterization of gSGFETs for brain recordings, with a focus on potential clinical applications of this emerging technology.

Single-Step Functionalization Strategy of Graphene Microtransistor Array with Chemically Modified Aptamers for Biosensing Applications.

Graphene solution-gated field-effect transistors (gSGFETs) offer high potential for chemical and biochemical sensing applications. Among the current trends to improve this technology, the functionalization processes are gaining relevance for its crucial impact on biosensing performance. Previous efforts are focused on simplifying the attachment procedure from standard multi-step to single-step strategies, but they still suffer from overreaction, and impurity issues and are limited to a particular ligand. Herein, a novel strategy for single-step immobilization of chemically modified aptamers with fluorenylmethyl and acridine moieties, based on a straightforward synthetic route to overcome the aforementioned limitations is presented. This approach is benchmarked versus a standard multi-step strategy using thrombin as detection model. In order to assess the reliability of the functionalization strategies 48-gSGFETs arrays are employed to acquire large datasets with multiple replicas. Graphene surface characterization demonstrates robust and higher efficiency in the chemical coupling of the aptamers with the single-step strategy, while the electrical response evaluation validates the sensing capability, allowing to implement different alternatives for data analysis and reduce the sensing variability. In this work, a new tool capable of overcome the functionalization challenges of graphene surfaces is provided, paving the way toward the standardization of gSGFETs for biosensing purposes.

Covalent functionalisation controlled by molecular design for the aptameric recognition of serotonin in graphene-based field-effect transistors.

In the last decade, solution-gated graphene field effect transistors (GFETs) showed their versatility in the development of a miniaturized multiplexed platform for electrophysiological recordings and sensing. Due to their working mechanism, the surface functionalisation and immobilisation of receptors are pivotal to ensure the proper functioning of devices. Herein, we present a controlled covalent functionalisation strategy based on molecular design and electrochemical triggering, which provide a monolayer-like functionalisation of micro-GFET arrays retaining the electronic properties of graphenes. The functionalisation layer as a receptor was then employed as the linker for serotonin aptamer conjugation. The micro-GFET arrays display sensitivity toward the target analyte in the micromolar range in a physiological buffer (PBS 10 mM). The sensor allows the in-flow real-time monitoring of serotonin transient concentrations with fast and reversible responses.

Correction: Organ-on-a-chip with integrated semitransparent organic electrodes for barrier function monitoring.

Correction for 'Organ-on-a-chip with integrated semitransparent organic electrodes for barrier function monitoring' by Denise Marrero et al., Lab Chip, 2023, https://doi.org/10.1039/d2lc01097f.

Organ-on-a-chip with integrated semitransparent organic electrodes for barrier function monitoring.

Organs-on-a-chip (OoC) are cell culture platforms that replicate key functional units of tissues in vitro. Barrier integrity and permeability evaluation are of utmost importance when studying barrier-forming tissues. Impedance spectroscopy is a powerful tool and is widely used to monitor barrier permeability and integrity in real-time. However, data comparison across devices is misleading due to the generation of a non-homogenous field across the tissue barrier, making impedance data normalization very challenging. In this work, we address this issue by integrating PEDOT:PSS electrodes for barrier function monitoring with impedance spectroscopy. The semitransparent PEDOT:PSS electrodes cover the entire cell culture membrane providing a homogenous electric field across the entire membrane making the cell culture area equally accountable to the measured impedance. To the best of our knowledge, PEDOT:PSS has never been used solely to monitor the impedance of cellular barriers while enabling optical inspection in the OoC. The performance of the device is demonstrated by lining the device with intestinal cells where we monitored barrier formation under flow conditions, as well as barrier disruption and recovery under exposure to a permeability enhancer. The barrier tightness and integrity, and the intercellular cleft have been evaluated by analyzing the full impedance spectrum. Furthermore, the device is autoclavable paving the way toward more sustainable OoC options.

Full-bandwidth electrophysiology of seizures and epileptiform activity enabled by flexible graphene microtransistor depth neural probes.

Mapping the entire frequency bandwidth of brain electrophysiological signals is of paramount importance for understanding physiological and pathological states. The ability to record simultaneously DC-shifts, infraslow oscillations (<0.1 Hz), typical local field potentials (0.1-80 Hz) and higher frequencies (80-600 Hz) using the same recording site would particularly benefit preclinical epilepsy research and could provide clinical biomarkers for improved seizure onset zone delineation. However, commonly used metal microelectrode technology suffers from instabilities that hamper the high fidelity of DC-coupled recordings, which are needed to access signals of very low frequency. In this study we used flexible graphene depth neural probes (gDNPs), consisting of a linear array of graphene microtransistors, to concurrently record DC-shifts and high-frequency neuronal activity in awake rodents. We show here that gDNPs can reliably record and map with high spatial resolution seizures, pre-ictal DC-shifts and seizure-associated spreading depolarizations together with higher frequencies through the cortical laminae to the hippocampus in a mouse model of chemically induced seizures. Moreover, we demonstrate the functionality of chronically implanted devices over 10 weeks by recording with high fidelity spontaneous spike-wave discharges and associated infraslow oscillations in a rat model of absence epilepsy. Altogether, our work highlights the suitability of this technology for in vivo electrophysiology research, and in particular epilepsy research, by allowing stable and chronic DC-coupled recordings.

A 1024-Channel 10-Bit 36- µW/ch CMOS ROIC for Multiplexed GFET-Only Sensor Arrays in Brain Mapping.

This paper presents a 1024-channel neural read-out integrated circuit (ROIC) for solution-gated GFET sensing probes in massive µECoG brain mapping. The proposed time-domain multiplexing of GFET-only arrays enables low-cost and scalable hybrid headstages. Low-power CMOS circuits are presented for the GFET analog frontend, including a CDS mechanism to improve preamplifier noise figures and 10-bit 10-kS/s A/D conversion. The 1024-channel ROIC has been fabricated in a standard 1.8-V 0.18- µm CMOS technology with 0.012 mm 2 and 36 µ W per channel. An automated methodology for the in-situ calibration of each GFET sensor is also proposed. Experimental ROIC tests are reported using a custom FPGA-based µECoG headstage with 16×32 and 32×32 GFET probes in saline solution and agar substrate. Compared to state-of-art neural ROICs, this work achieves the largest scalability in hybrid platforms and it allows the recording of infra-slow neural signals.

Characterization of optogenetically-induced cortical spreading depression in awake mice using graphene micro-transistor arrays.

Objective.The development of experimental methodology utilizing graphene micro-transistor arrays to facilitate and advance translational research into cortical spreading depression (CSD) in the awake brain.Approach.CSDs were reliably induced in awake nontransgenic mice using optogenetic methods. High-fidelity DC-coupled electrophysiological mapping of propagating CSDs was obtained using flexible arrays of graphene soultion-gated field-effect transistors (gSGFETs).Main results.Viral vectors targetted channelrhopsin expression in neurons of the motor cortex resulting in a transduction volume ⩾1 mm3. 5-10 s of continous blue light stimulation induced CSD that propagated across the cortex at a velocity of 3.0 ± 0.1 mm min-1. Graphene micro-transistor arrays enabled high-density mapping of infraslow activity correlated with neuronal activity suppression across multiple frequency bands during both CSD initiation and propagation. Localized differences in the CSD waveform could be detected and categorized into distinct clusters demonstrating the spatial resolution advantages of DC-coupled recordings. We exploited the reliable and repeatable induction of CSDs using this preparation to perform proof-of-principle pharmacological interrogation studies using NMDA antagonists. MK801 (3 mg kg-1) suppressed CSD induction and propagation, an effect mirrored, albeit transiently, by ketamine (15 mg kg-1), thus demonstrating this models' applicability as a preclinical drug screening platform. Finally, we report that CSDs could be detected through the skull using graphene micro-transistors, highlighting additional advantages and future applications of this technology.Significance.CSD is thought to contribute to the pathophysiology of several neurological diseases. CSD research will benefit from technological advances that permit high density electrophysiological mapping of the CSD waveform and propagation across the cortex. We report anin vivoassay that permits minimally invasive optogenetic induction, combined with multichannel DC-coupled recordings enabled by gSGFETs in the awake brain. Adoption of this technological approach could facilitate and transform preclinical investigations of CSD in disease relevant models.

Novel Graphene Electrode for Retinal Implants: An in vivo Biocompatibility Study.

Evaluating biocompatibility is a core essential step to introducing a new material as a candidate for brain-machine interfaces. Foreign body reactions often result in glial scars that can impede the performance of the interface. Having a high conductivity and large electrochemical window, graphene is a candidate material for electrical stimulation with retinal prosthesis. In this study, non-functional devices consisting of chemical vapor deposition (CVD) graphene embedded onto polyimide/SU-8 substrates were fabricated for a biocompatibility study. The devices were implanted beneath the retina of blind P23H rats. Implants were monitored by optical coherence tomography (OCT) and eye fundus which indicated a high stability in vivo up to 3 months before histology studies were done. Microglial reconstruction through confocal imaging illustrates that the presence of graphene on polyimide reduced the number of microglial cells in the retina compared to polyimide alone, thereby indicating a high biocompatibility. This study highlights an interesting approach to assess material biocompatibility in a tissue model of central nervous system, the retina, which is easily accessed optically and surgically.

Gut-on-a-chip: Mimicking and monitoring the human intestine.

Over the last few years, the intestine has been extensively studied using in vitro microfluidic systems, commonly known as gut-on-a-chip (GOC) devices. This interest has been due not only to the importance of the intestine's proper functions but also to the relationship that this organ and the microbiota that inhabits it has with the rest of the body's organs. The increased complexity of these in vitro systems, together with the need to improve our understanding of intestinal physiology interdependencies, has led to greater focus on the integration of biosensors within these devices. However, the current number of GOC devices with integrated sensors for monitoring relevant physiological parameters are very limited and demand the use of external analytical techniques that delay the analysis and prevent real-time decision-making. This paper reviews the various materials, technologies, and structures that have been used both for mimicking the physiology of the intestine and monitoring relevant physiological parameters, such as permeability of the gut barrier, dissolved oxygen concentration, cytokines profile and the production of microbial short-chain fatty acids. We also propose alternative biosensing techniques demonstrated in other in vitro and lab-on-a-chip devices that could be translated to GOC models. A critical analysis of the requirements, limitations, and current challenges on the microenvironment replication and monitorization of GOC models is included, with a particular focus on the physiological parameters and biomarkers that should be detected simultaneously in real-time to get a proper framework of the gut function that until now, have not received the necessary attention.

Switchless Multiplexing of Graphene Active Sensor Arrays for Brain Mapping.

Sensor arrays used to detect electrophysiological signals from the brain are paramount in neuroscience. However, the number of sensors that can be interfaced with macroscopic data acquisition systems currently limits their bandwidth. This bottleneck originates in the fact that, typically, sensors are addressed individually, requiring a connection for each of them. Herein, we present the concept of frequency-division multiplexing (FDM) of neural signals by graphene sensors. We demonstrate the high performance of graphene transistors as mixers to perform amplitude modulation (AM) of neural signals in situ, which is used to transmit multiple signals through a shared metal line. This technology eliminates the need for switches, remarkably simplifying the technical complexity of state-of-the-art multiplexed neural probes. Besides, the scalability of FDM graphene neural probes has been thoroughly evaluated and their sensitivity demonstrated in vivo. Using this technology, we envision a new generation of high-count conformal neural probes for high bandwidth brain machine interfaces.

Distortion-Free Sensing of Neural Activity Using Graphene Transistors.

Graphene solution-gated field-effect transistors (g-SGFETs) are promising sensing devices to transduce electrochemical potential signals in an electrolyte bath. However, distortion mechanisms in g-SGFET, which can affect signals of large amplitude or high frequency, have not been evaluated. Here, a detailed characterization and modeling of the harmonic distortion and non-ideal frequency response in g-SGFETs is presented. This accurate description of the input-output relation of the g-SGFETs allows to define the voltage- and frequency-dependent transfer functions, which can be used to correct distortions in the transduced signals. The effect of signal distortion and its subsequent calibration are shown for different types of electrophysiological signals, spanning from large amplitude and low frequency cortical spreading depression events to low amplitude and high frequency action potentials. The thorough description of the distortion mechanisms presented in this article demonstrates that g-SGFETs can be used as distortion-free signal transducers not only for neural sensing, but also for a broader range of applications in which g-SGFET sensors are used.

Bias dependent variability of low-frequency noise in single-layer graphene FETs.

Low-frequency noise (LFN) variability in graphene transistors (GFETs) is for the first time researched in this work under both experimental and theoretical aspects. LFN from an adequate statistical sample of long-channel solution-gated single-layer GFETs is measured in a wide range of operating conditions while a physics-based analytical model is derived that accounts for the bias dependence of LFN variance with remarkable performance. LFN deviations in GFETs stem from the variations of the parameters of the physical mechanisms that generate LFN, which are the number of traps (N tr) for the carrier number fluctuation effect (ΔN) due to trapping/detrapping process and the Hooge parameter (α H) for the mobility fluctuations effect (Δµ). ΔN accounts for an M-shape of normalized LFN variance versus gate bias with a minimum at the charge neutrality point (CNP) as it was the case for normalized LFN mean value while Δµ contributes only near the CNP for both variance and mean value. Trap statistical nature of the devices under test is experimentally shown to differ from classical Poisson distribution noticed at silicon-oxide devices, and this might be caused both by the electrolyte interface in GFETs under study and by the premature stage of the GFET technology development which could permit external factors to influence the performance. This not fully advanced GFET process growth might also cause pivotal inconsistencies affecting the scaling laws in GFETs of the same process.

A Minimally Invasive Microsensor Specially Designed for Simultaneous Dissolved Oxygen and pH Biofilm Profiling.

A novel sensing device for simultaneous dissolved oxygen (DO) and pH monitoring specially designed for biofilm profiling is presented in this work. This device enabled the recording of instantaneous DO and pH dynamic profiles within biofilms, improving the tools available for the study and the characterization of biological systems. The microsensor consisted of two parallel arrays of microelectrodes. Microelectrodes used for DO sensing were bare gold electrodes, while microelectrodes used for pH sensing were platinum-based electrodes modified using electrodeposited iridium oxide. The device was fabricated with a polyimide (Kapton®) film of 127 µm as a substrate for minimizing the damage caused on the biofilm structure during its insertion. The electrodes were covered with a Nafion® layer to increase sensor stability and repeatability and to avoid electrode surface fouling. DO microelectrodes showed a linear response in the range 0-8 mg L-1, a detection limit of 0.05 mg L-1, and a sensitivity of 2.06 nA L mg-1. pH electrodes showed a linear super-Nernstian response (74.2 ± 0.7 mV/pH unit) in a wide pH range (pH 4-9). The multi-analyte sensor array was validated in a flat plate bioreactor where simultaneous and instantaneous pH and DO profiles within a sulfide oxidizing biofilm were recorded. The electrodes spatial resolution, the monitoring sensitivity, and the minimally invasive features exhibited by the proposed microsensor improved biofilm monitoring performance, enabling the quantification of mass transfer resistances and the assessment of biological activity.

High-resolution mapping of infraslow cortical brain activity enabled by graphene microtransistors.

Recording infraslow brain signals (<0.1 Hz) with microelectrodes is severely hampered by current microelectrode materials, primarily due to limitations resulting from voltage drift and high electrode impedance. Hence, most recording systems include high-pass filters that solve saturation issues but come hand in hand with loss of physiological and pathological information. In this work, we use flexible epicortical and intracortical arrays of graphene solution-gated field-effect transistors (gSGFETs) to map cortical spreading depression in rats and demonstrate that gSGFETs are able to record, with high fidelity, infraslow signals together with signals in the typical local field potential bandwidth. The wide recording bandwidth results from the direct field-effect coupling of the active transistor, in contrast to standard passive electrodes, as well as from the electrochemical inertness of graphene. Taking advantage of such functionality, we envision broad applications of gSGFET technology for monitoring infraslow brain activity both in research and in the clinic.

Slow Waves in Cortical Slices: How Spontaneous Activity is Shaped by Laminar Structure.

Cortical slow oscillations (SO) of neural activity spontaneously emerge and propagate during deep sleep and anesthesia and are also expressed in isolated brain slices and cortical slabs. We lack full understanding of how SO integrate the different structural levels underlying local excitability of cell assemblies and their mutual interaction. Here, we focus on ongoing slow waves (SWs) in cortical slices reconstructed from a 16-electrode array designed to probe the neuronal activity at multiple spatial scales. In spite of the variable propagation patterns observed, we reproducibly found a smooth strip of loci leading the SW fronts, overlapping cortical layers 4 and 5, along which Up states were the longest and displayed the highest firing rate. Propagation modes were uncorrelated in time, signaling a memoryless generation of SWs. All these features could be modeled by a multimodular large-scale network of spiking neurons with a specific balance between local and intermodular connectivity. Modules work as relaxation oscillators with a weakly stable Down state and a peak of local excitability to model layers 4 and 5. These conditions allow for both optimal sensitivity to the network structure and richness of propagation modes, both of which are potential substrates for dynamic flexibility in more general contexts.

Quantification of Signal-to-Noise Ratio in Cerebral Cortex Recordings Using Flexible MEAs With Co-localized Platinum Black, Carbon Nanotubes, and Gold Electrodes.

Developing new standardized tools to characterize brain recording devices is critical to evaluate neural probes and for translation to clinical use. The signal-to-noise ratio (SNR) measurement is the gold standard for quantifying the performance of brain recording devices. Given the drawbacks with the SNR measure, our first objective was to devise a new method to calculate the SNR of neural signals to distinguish signal from noise. Our second objective was to apply this new SNR method to evaluate electrodes of three different materials (platinum black, Pt; carbon nanotubes, CNTs; and gold, Au) co-localized in tritrodes to record from the same cortical area using specifically designed multielectrode arrays. Hence, we devised an approach to calculate SNR at different frequencies based on the features of cortical slow oscillations (SO). Since SO consist in the alternation of silent periods (Down states) and active periods (Up states) of neuronal activity, we used these as noise and signal, respectively. The spectral SNR was computed as the power spectral density (PSD) of Up states (signal) divided by the PSD of Down states (noise). We found that Pt and CNTs electrodes have better recording performance than Au electrodes for the explored frequency range (5-1500 Hz). Together with two proposed SNR estimators for the lower and upper frequency limits, these results substantiate our SNR calculation at different frequency bands. Our results provide a new validated SNR measure that provides rich information of the performance of recording devices at different brain activity frequency bands (<1500 Hz).