RNA adapts its flexibility to efficiently fold and resist unfolding.

Recent studies have demonstrated that the mechanisms through which biopolymers like RNA interconvert between multiple folded structures are critical for their cellular functions. A major obstacle to elucidating these mechanisms is the lack of experimental approaches that can resolve these interconversions between functionally relevant biomolecular structures. Here, using a nano-electronic device with microsecond time resolution, we dissect the complete set of structural rearrangements executed by an ultra-stable RNA, the UUCG stem-loop, at the single-molecule level. We show that the stem-loop samples at least four conformations along two folding pathways leading to two distinct folded structures, only one of which has been previously observed. By modulating its flexibility, the stem-loop can adaptively select between these pathways, enabling it to both fold rapidly and resist unfolding. This paradigm of stabilization through compensatory changes in flexibility broadens our understanding of stable RNA structures and is expected to serve as a general strategy employed by all biopolymers.

Stable, chronic in-vivo recordings from a fully wireless subdural-contained 65,536-electrode brain-computer interface device.

Minimally invasive, high-bandwidth brain-computer-interface (BCI) devices can revolutionize human applications. With orders-of-magnitude improvements in volumetric efficiency over other BCI technologies, we developed a 50-µm-thick, mechanically flexible micro-electrocorticography (µECoG) BCI, integrating 256×256 electrodes, signal processing, data telemetry, and wireless powering on a single complementary metal-oxide-semiconductor (CMOS) substrate containing 65,536 recording and 16,384 stimulation channels, from which we can simultaneously record up to 1024 channels at a given time. Fully implanted below the dura, our chip is wirelessly powered, communicating bi-directionally with an external relay station outside the body. We demonstrated chronic, reliable recordings for up to two weeks in pigs and up to two months in behaving non-human primates from somatosensory, motor, and visual cortices, decoding brain signals at high spatiotemporal resolution.

Time-domain event detection using single-instruction, multiple-thread gpGPU architectures in single-molecule biophysical data.

Discrete amplitude levels in ordered, time-domain data often represent different underlying latent states of the system that is being interrogated. Analysis and feature extraction from these data sets generally require considering the order of each individual point; this approach cannot take advantage of contemporary general-purpose graphics processing units (gpGPU) and single-instruction multiple-data (SIMD) instruction set architectures. Two sources of such data from single-molecule biological measurements are nanopores and single-molecule field effect transistor (smFET) nanotube devices; both generate streams of time-ordered current or voltage data, typically sampled near 1 MS/s, with run times of minutes, yielding terabyte-scale datasets. Here, we present three gpGPU-based algorithms to overcome limitations associated with serial event detection in time series data, resulting in a 250× improvement in the rate with which we can detect salient features in nanopore and smFET datasets. The code is freely available.

Complementary integration of organic electrochemical transistors for front-end amplifier circuits of flexible neural implants.

The ability to amplify, translate, and process small ionic potential fluctuations of neural processes directly at the recording site is essential to improve the performance of neural implants. Organic front-end analog electronics are ideal for this application, allowing for minimally invasive amplifiers owing to their tissue-like mechanical properties. Here, we demonstrate fully organic complementary circuits by pairing depletion- and enhancement-mode p- and n-type organic electrochemical transistors (OECTs). With precise geometry tuning and a vertical device architecture, we achieve overlapping output characteristics and integrate them into amplifiers with single neuronal dimensions (20 micrometers). Amplifiers with combined p- and n-OECTs result in voltage-to-voltage amplification with a gain of >30 decibels. We also leverage depletion and enhancement-mode p-OECTs with matching characteristics to demonstrate a differential recording capability with high common mode rejection rate (>60 decibels). Integrating OECT-based front-end amplifiers into a flexible shank form factor enables single-neuron recording in the mouse cortex with on-site filtering and amplification.

Carbon-nanotube field-effect transistors for resolving single-molecule aptamer-ligand binding kinetics.

Small molecules such as neurotransmitters are critical for biochemical functions in living systems. While conventional ultraviolet-visible spectroscopy and mass spectrometry lack portability and are unsuitable for time-resolved measurements in situ, techniques such as amperometry and traditional field-effect detection require a large ensemble of molecules to reach detectable signal levels. Here we demonstrate the potential of carbon-nanotube-based single-molecule field-effect transistors (smFETs), which can detect the charge on a single molecule, as a new platform for recognizing and assaying small molecules. smFETs are formed by the covalent attachment of a probe molecule, in our case a DNA aptamer, to a carbon nanotube. Conformation changes on binding are manifest as discrete changes in the nanotube electrical conductance. By monitoring the kinetics of conformational changes in a binding aptamer, we show that smFETs can detect and quantify serotonin at the single-molecule level, providing unique insights into the dynamics of the aptamer-ligand system. In particular, we show the involvement of G-quadruplex formation and the disruption of the native hairpin structure in the conformational changes of the serotonin-aptamer complex. The smFET is a label-free approach to analysing molecular interactions at the single-molecule level with high temporal resolution, providing additional insights into complex biological processes.

Flexible switch matrix addressable electrode arrays with organic electrochemical transistor and pn diode technology.

Due to their effective ionic-to-electronic signal conversion and mechanical flexibility, organic neural implants hold considerable promise for biocompatible neural interfaces. Current approaches are, however, primarily limited to passive electrodes due to a lack of circuit components to realize complex active circuits at the front-end. Here, we introduce a p-n organic electrochemical diode using complementary p- and n-type conducting polymer films embedded in a 15-µm -diameter vertical stack. Leveraging the efficient motion of encapsulated cations inside this polymer stack and the opposite doping mechanisms of the constituent polymers, we demonstrate high current rectification ratios ([Formula: see text]) and fast switching speeds (230 µs). We integrate p-n organic electrochemical diodes with organic electrochemical transistors in the front-end pixel of a recording array. This configuration facilitates the access of organic electrochemical transistor output currents within a large network operating in the same electrolyte, while minimizing crosstalk from neighboring elements due to minimized reverse-biased leakage. Furthermore, we use these devices to fabricate time-division-multiplexed amplifier arrays. Lastly, we show that, when fabricated in a shank format, this technology enables the multiplexing of amplified local field potentials directly in the active recording pixel (26-µm diameter) in a minimally invasive form factor with shank cross-sectional dimensions of only 50×8 [Formula: see text].

A Wireless, Mechanically Flexible, 25µm-Thick, 65,536-Channel Subdural Surface Recording and Stimulating Microelectrode Array with Integrated Antennas.

This paper presents a fully wireless microelectrode array (MEA) system-on-chip (SoC) with 65,536 electrodes for non-penetrative cortical recording and stimulation, featuring a total sensing area of 6.8mm×7.4mm with a 26.5µm×29µm electrode pitch. Sensing, data telemetry, and powering are monolithically integrated on a single chip, which is made mechanically flexible to conform to the surface of the brain by substrate removal to a total thickness of 25µm allowing it to be contained entirely in the subdural space under the skull.

High-Density Integration of Ultrabright OLEDs on a Miniaturized Needle-Shaped CMOS Backplane.

Direct deposition of organic light-emitting diodes (OLEDs) on silicon-based complementary metal-oxide-semiconductor (CMOS) chips has enabled self-emissive microdisplays with high resolution and fill-factor. Emerging applications of OLEDs in augmented and virtual reality (AR/VR) displays and in biomedical applications, e.g., as brain implants for cell-specific light delivery in optogenetics, require light intensities orders of magnitude above those found in traditional displays. Further requirements often include a microscopic device footprint, a specific shape and ultrastable passivation, e.g., to ensure biocompatibility and minimal invasiveness of OLED-based implants. In this work, up to 1024 ultrabright, microscopic OLEDs are deposited directly on needle-shaped CMOS chips. Transmission electron microscopy and energy-dispersive X-ray spectroscopy are performed on the foundry-provided aluminum contact pads of the CMOS chips to guide a systematic optimization of the contacts. Plasma treatment and implementation of silver interlayers lead to ohmic contact conditions and thus facilitate direct vacuum deposition of orange- and blue-emitting OLED stacks leading to micrometer-sized pixels on the chips. The electronics in each needle allow each pixel to switch individually. The OLED pixels generate a mean optical power density of 0.25 mW mm-2 , corresponding to >40 000 cd m-2 , well above the requirement for daylight AR applications and optogenetic single-unit activation in the brain.

Perturbation of the host cell Ca2+ homeostasis and ER-mitochondria contact sites by the SARS-CoV-2 structural proteins E and M.

Coronavirus disease (COVID-19) is a contagious respiratory disease caused by the SARS-CoV-2 virus. The clinical phenotypes are variable, ranging from spontaneous recovery to serious illness and death. On March 2020, a global COVID-19 pandemic was declared by the World Health Organization (WHO). As of February 2023, almost 670 million cases and 6,8 million deaths have been confirmed worldwide. Coronaviruses, including SARS-CoV-2, contain a single-stranded RNA genome enclosed in a viral capsid consisting of four structural proteins: the nucleocapsid (N) protein, in the ribonucleoprotein core, the spike (S) protein, the envelope (E) protein, and the membrane (M) protein, embedded in the surface envelope. In particular, the E protein is a poorly characterized viroporin with high identity amongst all the ß-coronaviruses (SARS-CoV-2, SARS-CoV, MERS-CoV, HCoV-OC43) and a low mutation rate. Here, we focused our attention on the study of SARS-CoV-2 E and M proteins, and we found a general perturbation of the host cell calcium (Ca2+) homeostasis and a selective rearrangement of the interorganelle contact sites. In vitro and in vivo biochemical analyses revealed that the binding of specific nanobodies to soluble regions of SARS-CoV-2 E protein reversed the observed phenotypes, suggesting that the E protein might be an important therapeutic candidate not only for vaccine development, but also for the clinical management of COVID designing drug regimens that, so far, are very limited.

Charge Mapping of Pseudomonas aeruginosa Using a Hopping Mode Scanning Ion Conductance Microscopy Technique.

Scanning ion conductance microscopy (SICM) is a topographic imaging technique capable of probing biological samples in electrolyte conditions. SICM enhancements have enabled surface charge detection based on voltage-dependent signals. Here, we show how the hopping mode SICM method (HP-SICM) can be used for rapid and minimally invasive surface charge mapping. We validate our method usingPseudomonas aeruginosaPA14 (PA) cells and observe a surface charge density of σPA = -2.0 ± 0.45 mC/m2 that is homogeneous within the ∼80 nm lateral scan resolution. This biological surface charge is detected from at least 1.7 µm above the membrane (395× the Debye length), and the long-range charge detection is attributed to electroosmotic amplification. We show that imaging with a nanobubble-plugged probe reduces perturbation of the underlying sample. We extend the technique to PA biofilms and observe a charge density exceeding -20 mC/m2. We use a solid-state calibration to quantify surface charge density and show that HP-SICM cannot be quantitatively described by a steady-state finite element model. This work contributes to the body of scanning probe methods that can uniquely contribute to microbiology and cellular biology.

Subdural CMOS optical probe (SCOPe) for bidirectional neural interfacing.

Optical neurotechnologies use light to interface with neurons and can monitor and manipulate neural activity with high spatial-temporal precision over large cortical extents. While there has been significant progress in miniaturizing microscope for head-mounted configurations, these existing devices are still very bulky and could never be fully implanted. Any viable translation of these technologies to human use will require a much more noninvasive, fully implantable form factor. Here, we leverage advances in microelectronics and heterogeneous optoelectronic packaging to develop a transformative, ultrathin, miniaturized device for bidirectional optical stimulation and recording: the subdural CMOS Optical Probe (SCOPe). By being thin enough to lie entirely within the subdural space of the primate brain, SCOPe defines a path for the eventual human translation of a new generation of brain-machine interfaces based on light.

Characterizing the Conformational Free-Energy Landscape of RNA Stem-Loops Using Single-Molecule Field-Effect Transistors.

We have developed and used single-molecule field-effect transistors (smFETs) to characterize the conformational free-energy landscape of RNA stem-loops. Stem-loops are one of the most common RNA structural motifs and serve as building blocks for the formation of complex RNA structures. Given their prevalence and integral role in RNA folding, the kinetics of stem-loop (un)folding has been extensively characterized using both experimental and computational approaches. Interestingly, these studies have reported vastly disparate timescales of (un)folding, which has been interpreted as evidence that (un)folding of even simple stem-loops occurs on a highly rugged conformational energy landscape. Because smFETs do not rely on fluorophore reporters of conformation or mechanical (un)folding forces, they provide a unique approach that has allowed us to directly monitor tens of thousands of (un)folding events of individual stem-loops at a 200 µs time resolution. Our results show that under our experimental conditions, stem-loops (un)fold over a 1-200 ms timescale during which they transition between ensembles of unfolded and folded conformations, the latter of which is composed of at least two sub-populations. The 1-200 ms timescale of (un)folding we observe here indicates that smFETs report on complete (un)folding trajectories in which unfolded conformations of the RNA spend long periods of time wandering the free-energy landscape before sampling one of several misfolded conformations or the natively folded conformation. Our findings highlight the extremely rugged landscape on which even the simplest RNA structural elements fold and demonstrate that smFETs are a unique and powerful approach for characterizing the conformational free-energy of RNA.

Spatially controlled, bipolar, cortical stimulation with high-capacitance, mechanically flexible subdural surface microelectrode arrays.

Most neuromodulation approaches rely on extracellular electrical stimulation with penetrating electrodes at the cost of cortical damage. Surface electrodes, in contrast, are much less invasive but are challenged by the lack of proximity to axonal processes, leading to poor resolution. Here, we demonstrate that high-density (40-µm pitch), high-capacitance (>1 nF), single neuronal resolution PEDOT:PSS electrodes can be programmed to shape the charge injection front selectively at depths approaching 300 micrometers with a lateral resolution better than 100 micrometers. These electrodes, patterned on thin-film parylene substrate, can be subdurally implanted and adhere to the pial surface in chronic settings. By leveraging surface arrays that are optically transparent with PEDOT:PSS local interconnects and integrated with depth electrodes, we are able to combine surface stimulation and recording with calcium imaging and depth recording to demonstrate these spatial limits of bidirectional communication with pyramidal neurons in mouse visual cortex both laterally and at depth from the surface.

Flexible ultrasound transceiver array for non-invasive surface-conformable imaging enabled by geometric phase correction.

Ultrasound imaging provides the means for non-invasive real-time diagnostics of the internal structure of soft tissue in living organisms. However, the majority of commercially available ultrasonic transducers have rigid interfaces which cannot conform to highly-curved surfaces. These geometric limitations can introduce a signal-quenching air gap for certain topographies, rendering accurate imaging difficult or impractical. Here, we demonstrate a 256-element flexible two-dimensional (2D) ultrasound piezoelectric transducer array with geometric phase correction. We show surface-conformable real-time B-mode imaging, down to an extreme radius of curvature of 1.5 cm, while maintaining desirable performance metrics such as high signal-to-noise ratio (SNR) and minimal elemental cross-talk at all stages of bending. We benchmark the array capabilities by resolving reflectors buried at known locations in a medical-grade tissue phantom, and demonstrate how phase correction can improve image reconstruction on curved surfaces. With the current array design, we achieve an axial resolution of ≈ 2 mm at clinically-relevant depths in tissue, while operating the array at 1.4 MHz with a bandwidth of ≈ 41%. We use our prototype to image the surface of the human humerus at different positions along the arm, demonstrating proof-of-concept applicability for real-time diagnostics using phase-corrected flexible ultrasound probes.

Augmented ultrasonography with implanted CMOS electronic motes.

Modern clinical practice benefits significantly from imaging technologies and much effort is directed toward making this imaging more informative through the addition of contrast agents or reporters. Here, we report the design of a battery-less integrated circuit mote acting as an electronic reporter during medical ultrasound imaging. When implanted within the field-of-view of a brightness-mode (B-mode) ultrasound imager, this mote transmits information from its location through backscattered acoustic energy which is captured within the ultrasound image itself. We prototype and characterize the operation of such motes in vitro and in vivo. Performing with a static power consumption of less than 57 pW, the motes operate at duty cycles for receiving acoustic energy as low as 50 ppm. Motes within the same field-of-view during imaging have demonstrated signal-to-noise ratios of more than 19.1 dB at depths of up to 40 mm in lossy phantom. Physiological information acquired through such motes, which is beyond what is measurable with endogenous ultrasound backscatter and which is biogeographically located within an image, has the potential to provide an augmented ultrasonography.

Dissipation-enabled hydrodynamic conductivity in a tunable bandgap semiconductor.

Electronic transport in the regime where carrier-carrier collisions are the dominant scattering mechanism has taken on new relevance with the advent of ultraclean two-dimensional materials. Here, we present a combined theoretical and experimental study of ambipolar hydrodynamic transport in bilayer graphene demonstrating that the conductivity is given by the sum of two Drude-like terms that describe relative motion between electrons and holes, and the collective motion of the electron-hole plasma. As predicted, the measured conductivity of gapless, charge-neutral bilayer graphene is sample- and temperature-independent over a wide range. Away from neutrality, the electron-hole conductivity collapses to a single curve, and a set of just four fitting parameters provides quantitative agreement between theory and experiment at all densities, temperatures, and gaps measured. This work validates recent theories for dissipation-enabled hydrodynamic conductivity and creates a link between semiconductor physics and the emerging field of viscous electronics.

Electroluminescence of atoms in a graphene nanogap.

Here, we report light emission from single atoms bridging a graphene nanogap that emit bright visible light based on fluorescence of ionized atoms. Oxygen atoms in the gap shows a peak emission wavelength of 569 nm with a full width at half maximum (FWHM) of 208 nm. The energy states produced by these ionized oxygen atoms bridging carbon atoms in the gap also produce a large negative differential resistance (NDR) in the transport across the gap with the highest peak-to-valley current ratio (PVR = 45) and highest peak current density (~90 kA/cm2) ever reported in a solid-state tunneling device. While tunneling transport has been previously observed in graphene nanogaps, the bridging of ionized oxygen observed here shows a low excess current, leading to the observed PVR. On the basis of the highly reproducible light emission and NDR from these structures, we demonstrate a 65,536-pixel light-emitting nanogap array.

Toward implantable devices for angle-sensitive, lens-less, multifluorescent, single-photon lifetime imaging in the brain using Fabry-Perot and absorptive color filters.

Implantable image sensors have the potential to revolutionize neuroscience. Due to their small form factor requirements; however, conventional filters and optics cannot be implemented. These limitations obstruct high-resolution imaging of large neural densities. Recent advances in angle-sensitive image sensors and single-photon avalanche diodes have provided a path toward ultrathin lens-less fluorescence imaging, enabling plenoptic sensing by extending sensing capabilities to include photon arrival time and incident angle, thereby providing the opportunity for separability of fluorescence point sources within the context of light-field microscopy (LFM). However, the addition of spectral sensitivity to angle-sensitive LFM reduces imager resolution because each wavelength requires a separate pixel subset. Here, we present a 1024-pixel, 50 µm thick implantable shank-based neural imager with color-filter-grating-based angle-sensitive pixels. This angular-spectral sensitive front end combines a metal-insulator-metal (MIM) Fabry-Perot color filter and diffractive optics to produce the measurement of orthogonal light-field information from two distinct colors within a single photodetector. The result is the ability to add independent color sensing to LFM while doubling the effective pixel density. The implantable imager combines angular-spectral and temporal information to demix and localize multispectral fluorescent targets. In this initial prototype, this is demonstrated with 45 µm diameter fluorescently labeled beads in scattering medium. Fluorescent lifetime imaging is exploited to further aid source separation, in addition to detecting pH through lifetime changes in fluorescent dyes. While these initial fluorescent targets are considerably brighter than fluorescently labeled neurons, further improvements will allow the application of these techniques to in-vivo multifluorescent structural and functional neural imaging.