A high-performance speech neuroprosthesis.

Speech brain-computer interfaces (BCIs) have the potential to restore rapid communication to people with paralysis by decoding neural activity evoked by attempted speech into text1,2 or sound3,4. Early demonstrations, although promising, have not yet achieved accuracies sufficiently high for communication of unconstrained sentences from a large vocabulary1-7. Here we demonstrate a speech-to-text BCI that records spiking activity from intracortical microelectrode arrays. Enabled by these high-resolution recordings, our study participant-who can no longer speak intelligibly owing to amyotrophic lateral sclerosis-achieved a 9.1% word error rate on a 50-word vocabulary (2.7 times fewer errors than the previous state-of-the-art speech BCI2) and a 23.8% word error rate on a 125,000-word vocabulary (the first successful demonstration, to our knowledge, of large-vocabulary decoding). Our participant's attempted speech was decoded  at 62 words per minute, which is 3.4 times as fast as the previous record8 and begins to approach the speed of natural conversation (160 words per minute9). Finally, we highlight two aspects of the neural code for speech that are encouraging for speech BCIs: spatially intermixed tuning to speech articulators that makes accurate decoding possible from only a small region of cortex, and a detailed articulatory representation of phonemes that persists years after paralysis. These results show a feasible path forward for restoring rapid communication to people with paralysis who can no longer speak.

An Accurate and Rapidly Calibrating Speech Neuroprosthesis.

BACKGROUND: Brain-computer interfaces can enable communication for people with paralysis by transforming cortical activity associated with attempted speech into text on a computer screen. Communication with brain-computer interfaces has been restricted by extensive training requirements and limited accuracy. METHODS: A 45-year-old man with amyotrophic lateral sclerosis (ALS) with tetraparesis and severe dysarthria underwent surgical implantation of four microelectrode arrays into his left ventral precentral gyrus 5 years after the onset of the illness; these arrays recorded neural activity from 256 intracortical electrodes. We report the results of decoding his cortical neural activity as he attempted to speak in both prompted and unstructured conversational contexts. Decoded words were displayed on a screen and then vocalized with the use of text-to-speech software designed to sound like his pre-ALS voice. RESULTS: On the first day of use (25 days after surgery), the neuroprosthesis achieved 99.6% accuracy with a 50-word vocabulary. Calibration of the neuroprosthesis required 30 minutes of cortical recordings while the participant attempted to speak, followed by subsequent processing. On the second day, after 1.4 additional hours of system training, the neuroprosthesis achieved 90.2% accuracy using a 125,000-word vocabulary. With further training data, the neuroprosthesis sustained 97.5% accuracy over a period of 8.4 months after surgical implantation, and the participant used it to communicate in self-paced conversations at a rate of approximately 32 words per minute for more than 248 cumulative hours. CONCLUSIONS: In a person with ALS and severe dysarthria, an intracortical speech neuroprosthesis reached a level of performance suitable to restore conversational communication after brief training. (Funded by the Office of the Assistant Secretary of Defense for Health Affairs and others; BrainGate2 ClinicalTrials.gov number, NCT00912041.).

Single neurons in the thalamus and subthalamic nucleus process cardiac and respiratory signals in humans.

Visceral signals are constantly processed by our central nervous system, enable homeostatic regulation, and influence perception, emotion, and cognition. While visceral processes at the cortical level have been extensively studied using non-invasive imaging techniques, very few studies have investigated how this information is processed at the single neuron level, both in humans and animals. Subcortical regions, relaying signals from peripheral interoceptors to cortical structures, are particularly understudied and how visceral information is processed in thalamic and subthalamic structures remains largely unknown. Here, we took advantage of intraoperative microelectrode recordings in patients undergoing surgery for deep brain stimulation (DBS) to investigate the activity of single neurons related to cardiac and respiratory functions in three subcortical regions: ventral intermedius nucleus (Vim) and ventral caudalis nucleus (Vc) of the thalamus, and subthalamic nucleus (STN). We report that the activity of a large portion of the recorded neurons (about 70%) was modulated by either the heartbeat, the cardiac inter-beat interval, or the respiration. These cardiac and respiratory response patterns varied largely across neurons both in terms of timing and their kind of modulation. A substantial proportion of these visceral neurons (30%) was responsive to more than one of the tested signals, underlining specialization and integration of cardiac and respiratory signals in STN and thalamic neurons. By extensively describing single unit activity related to cardiorespiratory function in thalamic and subthalamic neurons, our results highlight the major role of these subcortical regions in the processing of visceral signals.

Electrochemically actuated microelectrodes for minimally invasive peripheral nerve interfaces.

Electrode arrays that interface with peripheral nerves are used in the diagnosis and treatment of neurological disorders; however, they require complex placement surgeries that carry a high risk of nerve injury. Here we leverage recent advances in soft robotic actuators and flexible electronics to develop highly conformable nerve cuffs that combine electrochemically driven conducting-polymer-based soft actuators with low-impedance microelectrodes. Driven with applied voltages as small as a few hundreds of millivolts, these cuffs allow active grasping or wrapping around delicate nerves. We validate this technology using in vivo rat models, showing that the cuffs form and maintain a self-closing and reliable bioelectronic interface with the sciatic nerve of rats without the use of surgical sutures or glues. This seamless integration of soft electrochemical actuators with neurotechnology offers a path towards minimally invasive intraoperative monitoring of nerve activity and high-quality bioelectronic interfaces.

Multifunctional Nanomaterials for Advancing Neural Interfaces: Recording, Stimulation, and Beyond.

ConspectusNeurotechnology has seen dramatic improvements in the last three decades. The major focus in the field has been to design electrical communication platforms with high spatial resolution, stability, and translatability for understanding and affecting neural pathways. The deployment of nanomaterials in bioelectronics has enhanced the capabilities of conventional approaches employing microelectrode arrays (MEAs) for electrical interfaces, allowing the construction of miniaturized, high-performance neuroelectronics (Garg, R.; et al. ACS Appl. Nano Mater. 2023, 6, 8495). While these advancements in the electrical neuronal interface have revolutionized neurotechnology both in scale and breadth, an in-depth understanding of neurons' interactions is challenging due to the complexity of the environments where the cells and tissues are laid. The activity of large, three-dimensional neuronal systems has proven difficult to accurately monitor and modulate, and chemical cell-cell communication is often completely neglected. Recent breakthroughs in nanotechnology have provided opportunities to use new nonelectric modes of communication with neurons and to significantly enhance electrical signal interface capabilities. The enhanced electrochemical activity and optical activity of nanomaterials owing to their nonbulk electronic properties and surface nanostructuring have seen extensive utilization. Nanomaterials' enhanced optical activity enables remote neural state modulation, whereas the defect-rich surfaces provide an enormous number of available electrocatalytic sites for neurochemical detection and electrochemical modulation of cell microenvironments through Faradaic processes. Such unique properties can allow multimodal neural interrogation toward generating closed-loop interfaces with access to more complete neural state descriptors. In this Account, we will review recent advances and our efforts spearheaded toward utilizing nanostructured electrodes for enhanced bidirectional interfaces with neurons, the application of unique hybrid nanomaterials for remote nongenetic optical stimulation of neurons, tunable nanomaterials for highly sensitive and selective neurotransmitter detection, and the utilization of nanomaterials as electrocatalysts toward electrochemically modulating cellular activity. We highlight applications of these technologies across cell types through nanomaterial engineering with a focus on multifunctional graphene nanostructures applied though several modes of neural modulation but also an exploration of broad material classes for maximizing the potency of closed-loop bioelectronics.

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

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

The influence of electrode types to the visually induced gamma oscillations in mouse primary visual cortex.

The local field potential (LFP) is an extracellular electrical signal associated with neural ensemble input and dendritic signaling. Previous studies have linked gamma band oscillations of the LFP in cortical circuits to sensory stimuli encoding, attention, memory, and perception. Inconsistent results regarding gamma tuning for visual features were reported, but it remains unclear whether these discrepancies are due to variations in electrode properties. Specifically, the surface area and impedance of the electrode are important characteristics in LFP recording. To comprehensively address these issues, we conducted an electrophysiological study in the V1 region of lightly anesthetized mice using two types of electrodes: one with higher impedance (1 MΩ) and a sharp tip (10 µm), while the other had lower impedance (100 KΩ) but a thicker tip (200 µm). Our findings demonstrate that gamma oscillations acquired by sharp-tip electrodes were significantly stronger than those obtained from thick-tip electrodes. Regarding size tuning, most gamma power exhibited surround suppression at larger gratings when recorded from sharp-tip electrodes. However, the majority showed enhanced gamma power at larger gratings when recorded from thick-tip electrodes. Therefore, our study suggests that microelectrode parameters play a significant role in accurately recording gamma oscillations and responsive tuning to sensory stimuli.

Understanding the local chemical environment of bioelectrocatalysis.

Bioelectrochemistry employs an array of high-surface-area meso- and macroporous electrode architectures to increase protein loading and the electrochemical current response. While the local chemical environment has been studied in small-molecule and heterogenous electrocatalysis, conditions in enzyme electrochemistry are still commonly established based on bulk solution assays, without appropriate consideration of the nonequilibrium conditions of the confined electrode space. Here, we apply electrochemical and computational techniques to explore the local environment of fuel-producing oxidoreductases within porous electrode architectures. This improved understanding of the local environment enabled simple manipulation of the electrolyte solution by adjusting the bulk pH and buffer pKa to achieve an optimum local pH for maximal activity of the immobilized enzyme. When applied to macroporous inverse opal electrodes, the benefits of higher loading and increased mass transport were employed, and, consequently, the electrolyte adjusted to reach -8.0 mA ⋅ cm-2 for the H2 evolution reaction and -3.6 mA ⋅ cm-2 for the CO2 reduction reaction (CO2RR), demonstrating an 18-fold improvement on previously reported enzymatic CO2RR systems. This research emphasizes the critical importance of understanding the confined enzymatic chemical environment, thus expanding the known capabilities of enzyme bioelectrocatalysis. These considerations and insights can be directly applied to both bio(photo)electrochemical fuel and chemical synthesis, as well as enzymatic fuel cells, to significantly improve the fundamental understanding of the enzyme-electrode interface as well as device performance.

Brain state limits propagation of neural signals in laminar cortical circuits.

Our perception of the environment relies on the efficient propagation of neural signals across cortical networks. During the time course of a day, neural responses fluctuate dramatically as the state of the brain changes to possibly influence how electrical signals propagate across neural circuits. Despite the importance of this issue, how patterns of spiking activity propagate within neuronal circuits in different brain states remains unknown. Here, we used multielectrode laminar arrays to reveal that brain state strongly modulates the propagation of neural activity across the layers of early visual cortex (V1). We optogenetically induced synchronized state transitions within a group of neurons and examined how far electrical signals travel during wakefulness and rest. Although optogenetic stimulation elicits stronger neural responses during wakefulness relative to rest, signals propagate only weakly across the cortical column during wakefulness, and the extent of spread is inversely related to arousal level. In contrast, the light-induced population activity vigorously propagates throughout the entire cortical column during rest, even when neurons are in a desynchronized wake-like state prior to light stimulation. Mechanistically, the influence of global brain state on the propagation of spiking activity across laminar circuits can be explained by state-dependent changes in the coupling between neurons. Our results impose constraints on the conclusions of causal manipulation studies attempting to influence neural function and behavior, as well as on previous computational models of perception assuming robust signal propagation across cortical layers and areas.

Free-Standing Carbon Nanotube Embroidered Graphene Film Electrode Array for Stable Neural Interfacing.

Implantable neural probes that are mechanically flexible yet robust are attractive candidates for achieving stable neural interfacing in the brain. Current flexible neural probes consist mainly of metal thin-film electrodes integrated on micrometer-thick polymer substrates, making it challenging to achieve electrode-tissue interfacing on the cellular scale. Here, we describe implantable neural probes that consist of robust carbon nanotube network embroidered graphene (CeG) films as free-standing recording microelectrodes. Our CeG film microelectrode arrays (CeG_MEAs) are ultraflexible yet mechanically robust, thus enabling cellular-scale electrode-tissue interfacing. Chronically implanted CeG_MEAs can stably track the activities of the same population of neurons over two months. Our results highlight the potential of ultraflexible and free-standing carbon nanofilms for stable neural interfacing in the brain.

Activationless Electron Transfer of Redox-DNA in Electrochemical Nanogaps.

Our recent discovery of decreased reorganization energy in electrode-tethered redox-DNA systems prompts inquiries into the origin of this phenomenon and suggests its potential use to lower the activation energy of electrochemical reactions. Here, we show that the confinement of the DNA chain in a nanogap amplifies this effect to an extent to which it nearly abolishes the intrinsic activation energy of electron transfer. Employing electrochemical atomic force microscopy (AFM-SECM), we create sub-10 nm nanogaps between a planar electrode surface bearing end-anchored ferrocenylated DNA chains and an incoming microelectrode tip. The redox cycling of the DNA's ferrocenyl (Fc) moiety between the surface and the tip generates a measurable current at the scale of ∼10 molecules. Our experimental findings are rigorously interpreted through theoretical modeling and original molecular dynamics simulations (Q-Biol code). Several intriguing findings emerge from our investigation: (i) The electron transport resulting from DNA dynamics is many times faster than predicted by simple diffusion considerations. (ii) The current in the nanogap is solely governed by the electron transfer rate at the electrodes. (iii) This rate rapidly saturates as overpotentials applied to the nanogap electrodes increase, implying near-complete suppression of the reorganization energy for the oxidation/reduction of the Fc heads within confined DNA. Furthermore, evidence is presented that this may constitute a general, previously unforeseen, behavior of redox polymer chains in electrochemical nanogaps.

Multiformity of extracellular microelectrode recordings from Aδ neurons in the dorsal root ganglia: a computational modeling study.

Microelectrodes serve as a fundamental tool in electrophysiology research throughout the nervous system, providing a means of exploring neural function with a high resolution of neural firing information. We constructed a hybrid computational model using the finite element method and multicompartment cable models to explore factors that contribute to extracellular voltage waveforms that are produced by sensory pseudounipolar neurons, specifically smaller A-type neurons, and that are recorded by microelectrodes in dorsal root ganglia. The finite element method model included a dorsal root ganglion, surrounding tissues, and a planar microelectrode array. We built a multicompartment neuron model with multiple trajectories of the glomerular initial segment found in many A-type sensory neurons. Our model replicated both the somatic intracellular voltage profile of Aδ low-threshold mechanoreceptor neurons and the unique extracellular voltage waveform shapes that are observed in experimental settings. Results from this model indicated that tortuous glomerular initial segment geometries can introduce distinct multiphasic properties into a neuron's recorded waveform. Our model also demonstrated how recording location relative to specific microanatomical components of these neurons, and recording distance from these components, can contribute to additional changes in the multiphasic characteristics and peak-to-peak voltage amplitude of the waveform. This knowledge may provide context for research employing microelectrode recordings of pseudounipolar neurons in sensory ganglia, including functional mapping and closed-loop neuromodulation. Furthermore, our simulations gave insight into the neurophysiology of pseudounipolar neurons by demonstrating how the glomerular initial segment aids in increasing the resistance of the stem axon and mitigating rebounding somatic action potentials.NEW & NOTEWORTHY We built a computational model of sensory neurons in the dorsal root ganglia to investigate factors that influence the extracellular waveforms recorded by microelectrodes. Our model demonstrates how the unique structure of these neurons can lead to diverse and often multiphasic waveform profiles depending on the location of the recording contact relative to microanatomical neural components. Our model also provides insight into the neurophysiological function of axon glomeruli that are often present in these neurons.

Rejuvenating silicon probes for acute neurophysiology.

Neurophysiological recording with a new probe often yields better signal quality than with a used probe. Why does the signal quality degrade after only a few experiments? Here, we considered silicon probes in which the contacts are densely packed, and each contact is coated with a conductive polymer that increases its surface area. We tested 12 Cambridge Neurotech silicon probes during 61 recording sessions from the brain of three marmosets. Out of the box, each probe arrived with an electrodeposited polymer coating on 64 gold contacts and an impedance of around 50 kΩ. With repeated use, the impedance increased and there was a corresponding decrease in the number of well-isolated neurons. Imaging of the probes suggested that the reduction in signal quality was due to a gradual loss of the polymer coating. To rejuvenate the probes, we first stripped the contacts, completely removing their polymer coating, and then recoated them in a solution of 10 mM 3,4-Ethylenedioxythiophene (EDOT) monomer with 11 mM Poly(sodium 4-styrenesulfonate) (PSS) using a current density of about 3 mA/cm2 for 30 s. This recoating process not only returned probe impedance to around 50 kΩ but also yielded significantly improved signal quality during neurophysiological recordings. Thus, insertion into the brain promoted the loss of the polymer that coated the contacts of the silicon probes. This led to degradation of signal quality, but recoating rejuvenated the probes.NEW & NOTEWORTHY With repeated use, a silicon probe's ability to isolate neurons degrades. As a result, the probe is often discarded after only a handful of uses. Here, we demonstrate a major source of this problem and then produce a solution to rejuvenate the probes.

A Photoelectrochemical Sensor for Real-Time Monitoring of Neurochemical Signals in the Brain of Awake Animals.

Metal ion homeostasis is imperative for normal functioning of the brain. Considering the close association between brain metal ions and various pathological processes in brain diseases, it becomes essential to track their dynamics in awake animals for accurate physiological insights. Although ion-selective microelectrodes (ISMEs) have demonstrated great advantage in recording ion signals in awake animals, their intrinsic potential drift impairs their accuracy in long-term in vivo analysis. This study addresses the challenge by integrating ISMEs with photoelectrochemical (PEC) sensing, presenting an excitation-detection separated PEC platform based on potential regulation of ISMEs. A flexible indium tin oxide (Flex-ITO) electrode, modified with MoS2 nanosheets and Au NPs, serves as the photoelectrode and is integrated with a micro-LED. The integrated photoelectrode is placed on the rat skull to remain unaffected by animal activity. The potential of ISME dependent on the concentration of target K+ serves as the modulator of the photocurrent signal of the photoelectrode. The proposed design allows deep brain detection while minimizing interference with neurons, thus enabling real-time monitoring of neurochemical signals in awake animals. It successfully monitors changes in extracellular K+ levels in the rat brain after exposure to PM2.5, presenting a valuable analytical tool for understanding the impact of environmental factors on the nervous system.

Difunctional Microelectrode Arrays for Single-Cell Electrical Stimulation and pH Detection.

Due to its direct effect on biomolecules and cells, electrical stimulation (ES) is now widely used to regulate cell proliferation, differentiation, and neurostimulation and is even used in the clinic for pain relief, treatment of nerve damage, and muscle rehabilitation. Conventional ES is mostly studied on cell populations, but the heterogeneity of cancer cells results in the inability to access the response of individual cells to ES. Therefore, detecting the extracellular pH change (ΔpHe) after ES at the single-cell level is important for the application of ES in tumor therapy. In this study, cellular ΔpHe after periodic impulse electrostimulation (IES) was monitored in situ by using a polyaniline (PANI)-modified gold microelectrode array. The PANI sensor had excellent sensitivity (53.68 mV/pH) and linear correlation coefficient (R2 = 0.999) over the pH range of 5.55-7.41. The cells showed different degrees of ΔpHe after the IES with different intervals and stimulation potential. A shorter pulse interval and a higher stimulation potential could effectively enhance stimulation and increase cellular ΔpHe. At 0.5 V potential stimulation, the cellular ΔpHe increased with decreasing pulse interval. However, if the pulse interval was long enough, even at a higher potential of 0.7 V, there was no significant additional ΔpHe due to the insufficient stimulus strength. Based on the above conclusions, the prepared PANI microelectrode arrays (MEAs) were capable of stimulating and detecting single cells, which contributed to the deeper application of ES in tumor therapy.

Developing Microelectrode Arrays for the Point-of-Care Multiplex Detection of Metabolites.

DNA-aptamer-functionalized electrode arrays can provide an intriguing method for detecting pathogen-derived exometabolites. This work addresses the limitations of previous aptamer-based pathogen detection methods by introducing a novel surface design that bridges the gap between initial efforts in this area and the demands of a point-of-care device. Specifically, the use of a diblock copolymer coating on a high-density microelectrode array and Cu-mediated cross coupling reactions that allow for the exclusive functionalization of that coating by any electrode or set of electrodes in the array provides a device that is stable for 1 year and compatible with the multiplex detection of small-molecule targets. The new chemistry developed allows one to take advantage of a large number of electrodes in the array with one experiment described herein capitalizing on the use of 960 individually addressable electrodes.

Electrochemical Monitoring of Sphingosine-1-phosphate-Induced ATP Release Using a Microsensor Based on an Entropy-Driven Bipedal DNA Walker.

Neuropathic pain is a chronic and severe syndrome for which effective therapy is insufficient and the release of ATP from microglia induced by sphingosine-1-phosphate (S1P) plays a vital role in neuropathic pain. Therefore, there is an urgent demand to develop highly sensitive and selective ATP biosensors for quantitative monitoring of low-concentration ATP in the complex nervous system, which helps in understanding the mechanism involved in neuropathic pain. Herein, we developed an electrochemical microsensor based on an entropy-driven bipedal DNA walker. First, the microsensor specifically recognized ATP via ATP aptamers, initiating the entropy-driven bipedal DNA walker. Subsequently, the bipedal DNA walker autonomously traversed the microelectrode interface, introducing methylene blue to the electrode surface and achieving cascade signal amplification. This microsensor showed excellent selectivity, stability, and a low limit of detection at 1.13 nM. The S1P-induced ATP release from BV2 cells was successfully monitored, and it was observed that dicumarol could inhibit this release, suggesting dicumarol as a potential treatment for neuropathic pain. The microsensor's small size exhibited significant potential for monitoring ATP level changes in neuropathic pain in vivo, which provides a new strategy for in situ and quantitative monitoring of nonelectroactive biomolecules associated with neurological diseases.

3D-Printed Microelectrodes for Biological Measurement.

Microelectrodes are useful electrochemical sensors that can provide spatial biological monitoring. Carbon fiber has been by far the most widely used microelectrode; however, a vast number of different materials and modification strategies have been developed to broaden the scope of microelectrodes. Carbon composite electrodes provide a simple approach to making microelectrodes with a wide range of materials, but manufacturing strategies are complex. 3D printing can provide the ability to make microelectrodes with high precision. We used fused filament fabrication to print single strands of carbon black/polylactic acid (CB/PLA) and multiwall carbon nanotube/polylactic acid (MWCNT/PLA), which were then made into microelectrodes. Microelectrodes ranged from 70 µm in diameter to 400 µm in diameter and were assessed using standard redox probes. MWCNT/PLA electrodes exhibited greater sensitivity, a lower limit of detection, and stability for the measurement of serotonin (5-HT). Both CB/PLA and MWCNT/PLA microelectrodes were able to monitor 5-HT overflow from the ex vivo ileum tissue. MWCNT/PLA microelectrodes were utilized to show differences in 5-HT overflow from ex vivo ileum and colon following exposure to odorants present in spices. These findings highlight that any conductive thermoplastic material can be fabricated into a microelectrode. This simple strategy can utilize a wide range of materials to make 3D-printed microelectrodes for a diverse range of applications.

Molecular Stratification and Treatment Monitoring of Lung Cancer Using a Small Extracellular Vesicle-Activated Nanocavity Architecture.

Development of molecular diagnostics for lung cancer stratification and monitoring is crucial for the rational planning and timely adjustment of treatments to improve clinical outcomes. In this regard, we propose a nanocavity architecture to sensitively profile the protein signature on small extracellular vesicles (sEVs) to enable accurate, noninvasive staging and treatment monitoring of lung cancer. The nanocavity architecture is formed by molecular recognition through the binding of sEVs with the nanobox-based core-shell surface-enhanced Raman scattering (SERS) barcodes and mirrorlike, asymmetric gold microelectrodes. By imposing an alternating current on the gold microelectrodes, a nanofluidic shear force was stimulated that supported the binding of sEVs and the efficient assembly of the nanoboxes. The binding of sEVs further induced a nanocavity between the nanobox and the gold microelectrode that significantly amplified the electromagnetic field to enable the simultaneous enhancement of Raman signals from four SERS barcodes and generate patient-specific molecular sEV signatures. Importantly, evaluated on a cohort of clinical samples (n = 76) on the nanocavity architecture, the acquired patient-specific sEV molecular signatures achieved accurate identification, stratification, and treatment monitoring of lung cancer patients, highlighting its potential for transition to clinical utility.

An Ultramicroelectrode Electrochemistry and Surface Plasmon Resonance Coupling Method for Cell Exocytosis Study.

Exocytosis of a single cell has been extensively researched in recent years due to its close association with numerous diseases. However, current methods only investigate exocytosis at either the single-cell or multiple-cell level, and a method for simultaneously studying exocytosis at both levels has yet to be established. In this study, a combined device incorporating ultramicroelectrode (UME) electrochemistry and surface plasmon resonance (SPR) was developed, enabling the simultaneous monitoring of single-cell and multiple-cell exocytosis. PC12 cells were cultured directly on the SPR sensing Au film, with a carboxylated carbon nanopipette (c-CNP) electrode employed for electrochemical detection in the SPR reaction cell. Upon exocytosis, the released dopamine diffuses onto the inner wall of c-CNP, undergoing an electrochemical reaction to generate a current peak. Concurrently, exocytosis can also induce changes in the refractive index of the Au film surface, leading to the SPR signal. Consequently, the device enables real-time monitoring of exocytosis from both single and multiple cells with a high spatiotemporal resolution. The c-CNP electrode exhibited excellent resistance to protein contamination, high sensitivity for dopamine detection, and the capability to continuously monitor dopamine exocytosis over an extended period. Analysis of both SPR and electrochemical signals revealed a positive correlation between changes in the SPR signal and the frequency of exocytosis. This study introduces a novel method and platform for the simultaneous investigation of single-cell and multiple-cell exocytosis.