Radical generation and bactericidal activity of nanobubbles produced by ultrasonic irradiation of carbonated water.

Our previous study showed that nanobubbles (NBs) encapsulating CO2 gas have bactericidal activity due to reactive oxygen species (ROS) (Yamaguchi et al., 2020). Here, we report that bulk NBs encapsulating CO2 can be efficiently generated by ultrasonically irradiating carbonated water using a piezoelectric transducer with a frequency of 1.7 MHz. The generated NBs were less than 100 nm in size and had a lifetime of 500 h. Furthermore, generation of ROS in the NB suspension was investigated using electron spin resonance spectroscopy and fluorescence spectrometry. The main ROS was found to be the hydroxyl radical, which is consistent with our previous observations. The bactericidal activity lasted for at least one week. Furthermore, a mist generated by atomizing the NB suspension with ultrasonic waves was confirmed to have the same bactericidal activity as the suspension itself. We believe that the strong, persistent bactericidal activity and radical generation phenomenon are unique to NBs produced by ultrasonic irradiation of carbonated water. We propose that entrapped CO2 molecules strongly interact with water at the NB interface to weaken the interface, and high-pressure CO2 gas erupts from this weakened interface to generate ROS with bactericidal activity.

Enhanced responses to inflammatory cytokine interleukin-6 in micropatterned networks of cultured cortical neurons.

Cortical neurons in dissociated cultures are an indispensable model system for pharmacological research that provides insights into chemical responses in well-defined environments. However, cortical neurons plated on homogeneous substrates develop an unstructured network that exhibits excessively synchronized activity, which occasionally masks the consequences induced by external substances. Here, we show that hyperactivity and excessive synchrony in cultured cortical networks can be effectively suppressed by growing neurons in microfluidic devices. These devices feature a hierarchically modular design that resembles the in vivo network. We focused on interleukin-6, a pro-inflammatory cytokine, and assessed its acute and chronic effects. Fluorescence calcium imaging of spontaneous neural activity for up to 20 days of culture showed detectable modulation of collective activity events and neural correlation in micropatterned neurons, which was not apparent in neurons cultured on homogeneous substrates. Our results indicate that engineered neuronal networks provide a unique platform for detecting and understanding the fundamental effects of biochemical compounds on neuronal networks.

Two-dimensional water-molecule-cluster layers at nanobubble interfaces.

HYPOTHESIS: Bulk nanobubbles (NBs) have high surface charge densities and long lifetimes. Despite several attempts to understand the lifetime of NBs, their interfacial layer structure remains unknown. It is hypothesized that a specific interfacial layer exists with a hydrogen bond network that stabilizes NBs. EXPERIMENTS: In situ infrared reflectance-absorption spectroscopy and density functional theory were used to determine the interfacial layer structure of NBs. Furthermore, nuclear magnetic resonance spectroscopy was used to examine the interfacial layer hardness of bubbles filled with N2, O2, and CO2, which was expected to depend on the encapsulated gas species. FINDINGS: The interfacial layer was composed of three-, four-, and five-membered ring clusters of water molecules. An interface model was proposed in which a two-dimensional layer of clusters with large electric dipole moments is oriented toward the endohedral gas, and the hydrophobic surface is adjacent to the free water. The interfacial layer hardness was dependent on the interaction with the gas (N2 > O2 > CO2), which supports the proposed interface model. These findings can be generalized to the structure of water at gas-water interfaces.

Modular architecture facilitates noise-driven control of synchrony in neuronal networks.

High-level information processing in the mammalian cortex requires both segregated processing in specialized circuits and integration across multiple circuits. One possible way to implement these seemingly opposing demands is by flexibly switching between states with different levels of synchrony. However, the mechanisms behind the control of complex synchronization patterns in neuronal networks remain elusive. Here, we use precision neuroengineering to manipulate and stimulate networks of cortical neurons in vitro, in combination with an in silico model of spiking neurons and a mesoscopic model of stochastically coupled modules to show that (i) a modular architecture enhances the sensitivity of the network to noise delivered as external asynchronous stimulation and that (ii) the persistent depletion of synaptic resources in stimulated neurons is the underlying mechanism for this effect. Together, our results demonstrate that the inherent dynamical state in structured networks of excitable units is determined by both its modular architecture and the properties of the external inputs.

Model-free idealization: Adaptive integrated approach for idealization of ion-channel currents.

Single-channel electrophysiological recordings provide insights into transmembrane ion permeation and channel gating mechanisms. The first step in the analysis of the recorded currents involves an "idealization" process, in which noisy raw data are classified into two discrete levels corresponding to the open and closed states of channels. This provides valuable information on the gating kinetics of ion channels. However, the idealization step is often challenging in cases of currents with poor signal-to-noise ratios and baseline drifts, especially when the gating model of the target channel is not identified. We report herein on a highly robust model-free idealization method for achieving this goal. The algorithm, called adaptive integrated approach for idealization of ion-channel currents (AI2), is composed of Kalman filter and Gaussian mixture model clustering and functions without user input. AI2 automatically determines the noise reduction setting based on the degree of separation between the open and closed levels. We validated the method on pseudo-channel-current datasets that contain either computed or experimentally recorded noise. We also investigated the relationship between the noise reduction parameter of the Kalman filter and the cutoff frequency of the low-pass filter. The AI2 algorithm was then tested on actual experimental data for biological channels including gramicidin A, a voltage-gated sodium channel, and other unidentified channels. We compared the idealization results with those obtained by the conventional methods, including the 50%-threshold-crossing method.

Biological neurons act as generalization filters in reservoir computing.

Reservoir computing is a machine learning paradigm that transforms the transient dynamics of high-dimensional nonlinear systems for processing time-series data. Although the paradigm was initially proposed to model information processing in the mammalian cortex, it remains unclear how the nonrandom network architecture, such as the modular architecture, in the cortex integrates with the biophysics of living neurons to characterize the function of biological neuronal networks (BNNs). Here, we used optogenetics and calcium imaging to record the multicellular responses of cultured BNNs and employed the reservoir computing framework to decode their computational capabilities. Micropatterned substrates were used to embed the modular architecture in the BNNs. We first show that the dynamics of modular BNNs in response to static inputs can be classified with a linear decoder and that the modularity of the BNNs positively correlates with the classification accuracy. We then used a timer task to verify that BNNs possess a short-term memory of several 100 ms and finally show that this property can be exploited for spoken digit classification. Interestingly, BNN-based reservoirs allow categorical learning, wherein a network trained on one dataset can be used to classify separate datasets of the same category. Such classification was not possible when the inputs were directly decoded by a linear decoder, suggesting that BNNs act as a generalization filter to improve reservoir computing performance. Our findings pave the way toward a mechanistic understanding of information representation within BNNs and build future expectations toward the realization of physical reservoir computing systems based on BNNs.

Filtration-processed biomass nanofiber electrodes for flexible bioelectronics.

An increasing demand for bioelectronics that interface with living systems has driven the development of materials to resolve mismatches between electronic devices and biological tissues. So far, a variety of different polymers have been used as substrates for bioelectronics. Especially, biopolymers have been investigated as next-generation materials for bioelectronics because they possess interesting characteristics such as high biocompatibility, biodegradability, and sustainability. However, their range of applications has been restricted due to the limited compatibility of classical fabrication methods with such biopolymers. Here, we introduce a fabrication process for thin and large-area films of chitosan nanofibers (CSNFs) integrated with conductive materials. To this end, we pattern carbon nanotubes (CNTs), silver nanowires, and poly (3,4-ethylenedioxythiophene):poly (styrenesulfonate) (PEDOT:PSS) by a facile filtration process that uses polyimide masks fabricated via laser ablation. This method yields feedlines of conductive material on nanofiber paper and demonstrates compatibility with conjugated and high-aspect-ratio materials. Furthermore, we fabricate a CNT neural interface electrode by taking advantage of this fabrication process and demonstrate peripheral nerve stimulation to the rapid extensor nerve of a live locust. The presented method might pave the way for future bioelectronic devices based on biopolymer nanofibers.

New Aspects of Bilayer Lipid Membranes for the Analysis of Ion Channel Functions.

The bilayer lipid membrane (BLM) is the main structural component of cell membranes, in which various membrane proteins are embedded. Artificially formed BLMs have been used as a platform in studies of the functions of membrane proteins, including various ion channels. In this review, we summarize recent advances that have been made on artificial BLM systems for the analysis of ion channel functions. We focus on two BLM-based systems, cell-membrane mimicry and four-terminal BLM systems. As a cell-membrane-mimicking system, an efficient screening platform for the evaluation of drug side effects that act on a cell-free synthesized channel has been developed, and its prospects for use in personalized medicine will be discussed. In the four-terminal BLMs, we introduce "lateral voltage" to BLM systems as a novel input to regulate channel activities, in addition to the traditional transmembrane voltages. Such state-of-the-art technologies and new system setups are predicted to pave the way for a variety of applications, in both fundamental physiology and in drug discovery.

Lateral voltage as a new input for artificial lipid bilayer systems.

In this work, we propose lateral voltage as a new input for use in artificial lipid bilayer systems in addition to the commonly used transmembrane voltage. To apply a lateral voltage to bilayer lipid membranes, we fabricated electrode-equipped silicon and Teflon chips. The Si chips could be used for photodetector devices based on fullerene-doped lipid bilayers, and the Teflon chips were used in a study of the ion channel functions in the lipid bilayer. The findings indicate that the lateral voltage effectively regulates the transmembrane current, in both ion-channel-incorporated and fullerene-incorporated lipid bilayer systems, suggesting that the lateral voltage is a practicable and useful additional input for use in lipid bilayer systems.

Microfluidic cell engineering on high-density microelectrode arrays for assessing structure-function relationships in living neuronal networks.

Neuronal networks in dissociated culture combined with cell engineering technology offer a pivotal platform to constructively explore the relationship between structure and function in living neuronal networks. Here, we fabricated defined neuronal networks possessing a modular architecture on high-density microelectrode arrays (HD-MEAs), a state-of-the-art electrophysiological tool for recording neural activity with high spatial and temporal resolutions. We first established a surface coating protocol using a cell-permissive hydrogel to stably attach a polydimethylsiloxane microfluidic film on the HD-MEA. We then recorded the spontaneous neural activity of the engineered neuronal network, which revealed an important portrait of the engineered neuronal network-modular architecture enhances functional complexity by reducing the excessive neural correlation between spatially segregated modules. The results of this study highlight the impact of HD-MEA recordings combined with cell engineering technologies as a novel tool in neuroscience to constructively assess the structure-function relationships in neuronal networks.

Bactericidal Activity of Bulk Nanobubbles through Active Oxygen Species Generation.

We investigated the bactericidal activity of bulk nanobubbles (NBs) using E. coli, a model bacterium. Bulk NBs were produced by forcing gas through a porous alumina membrane with an ordered arrangement of nanoscale straight holes in contact with water. NBs with different gas contents, including CO2, O2, and N2, were generated and evaluated for their bactericidal effects. The survival rate of E. coli was significantly reduced in a suspension of CO2-containing NB (CO2-NB water). The N2-NB water demonstrated a small amount of bactericidal behavior, but its impact was not as significant as that of CO2-NB water. When E. coli was retained in O2-NB water, the survival rate was even higher than that in pure water (PW). We investigated the generation of reactive oxygen species (ROS) in NB suspensions by electron spin resonance spectroscopy. The main ROS generated in the NB water were hydroxyl radicals and OH·, and the production of ROS was the strongest in CO2-NB water, which was consistent with the results of the bactericidal effect measurements. We assumed that NB mediated by ROS would exhibit bactericidal behavior and proposed a kinetic model to explain the retention time variation of the survival rate. The results calculated based on the proposed model matched closely with the experimental results.

Parallel Recordings of Transmembrane hERG Channel Currents Based on Solvent-Free Lipid Bilayer Microarray.

The reconstitution of ion-channel proteins in artificially formed bilayer lipid membranes (BLMs) forms a well-defined system for the functional analysis of ion channels and screening of the effects of drugs that act on these proteins. To improve the efficiency of the BLM reconstitution system, we report on a microarray of stable solvent-free BLMs formed in microfabricated silicon (Si) chips, where micro-apertures with well-defined nano- and micro-tapered edges were fabricated. Sixteen micro-wells were manufactured in a chamber made of Teflon®, and the Si chips were individually embedded in the respective wells as a recording site. Typically, 11 to 16 BLMs were simultaneously formed with an average BLM number of 13.1, which corresponded to a formation probability of 82%. Parallel recordings of ion-channel activities from multiple BLMs were successfully demonstrated using the human ether-a-go-go-related gene (hERG) potassium channel, of which the relation to arrhythmic side effects following drug treatment is well recognized.

Optical transport of sub-micron lipid vesicles along a nanofiber.

Enhanced manipulation and analysis of bio-particles using light confined in nano-scale dielectric structures has proceeded apace in the last several years. Small mode volumes, along with the lack of a need for bulky optical elements give advantages in sensitivity and scalability relative to conventional optical manipulation. However, manipulation of lipid vesicles (liposomes) remains difficult, particularly in the sub-micron diameter regime. Here we demonstrate the optical trapping and transport of sub-micron diameter liposomes along an optical nanofiber using the nanofiber mode's evanescent field. We find that nanofiber diameters below a nominal diffraction limit give optimal results. Our results pave the way for integrated optical transport and analysis of liposome-like bio-particles, as well as their coupling to nano-optical resonators.

Contribution of AMPA and NMDA receptors in the spontaneous firing patterns of single neurons in autaptic culture.

Single neurons in an autaptic culture exhibit various types of firing pattern with different firing durations and rhythms. However, a neuron with autapses has often been modeled as an oscillator providing a monotonic firing pattern with a constant periodicity because of the lack of a mathematical model. In the work described in this study, we use computational simulation and whole-cell patch-clamp recording to elucidate and model the mechanism by which such neurons generate various firing pattens. In the computational simulation, three types of spontaneous firing pattern, i.e., short, long-lasting, and periodic burst firing patterns are realized by changing the combination ratio of N-methyl-d-aspartate (NMDA) to α-amino-3-hydroxyl-5-methyl-4-isoxazole-propionate (AMPA) conductance. These three types of firing patterns are also observed in the experiments where neurons are cultured in isolation on micropatterned substrates. Using the AMPA and NMDA current models, we discuss that, in principle, autapses can regulate rhythmicity and information selection in neuronal networks.

Bactericidal Activity of TiO2 Nanotube Thin Films on Si by Photocatalytic Generation of Active Oxygen Species.

The photocatalytic bactericidal activity of titanium dioxide (TiO2) thin films has been extensively studied. In this study, we investigated the bactericidal activities of TiO2 nanotube (NT) thin films using Escherichia coli and Staphylococcus aureus cells as the model bacteria. Metallic titanium (Ti) thin films were anodized on a silicon (Si) wafer substrate to form TiO2 NT thin films. To evaluate the bactericidal activity of the TiO2 NT thin films, bacteria on the TiO2 NT thin films were irradiated with near-ultraviolet light (UV-A) at a wavelength of 365 nm. The bactericidal activity was estimated by the survival rate derived from the number of live cells, which form colonies on the cell culture medium. We demonstrated that the survival rate of the two types of bacteria investigated in this study was significantly reduced by UV light irradiation and that there was a difference in the temporal change in the survival rate between the two types of bacteria. Furthermore, we investigated the generation of reactive oxygen species (ROSs) by UV light irradiation of TiO2 NT thin films using electron spin resonance spectroscopy and fluorescence analysis. We found that the main ROS generated on the surface of the TiO2 NT film was the hydroxyl radical, OH•. In addition, the generation of ROSs increased with an increase in the UV irradiation time. We proposed a kinetic model that reproduces the dependence of bacterial viability on the UV light irradiation time by considering the temporal change in the amount of ROSs generated by UV light irradiation. A comparison of the calculated and experimental results revealed that the bactericidal effect consisted of the direct photolysis of bacteria and the photocatalysis via the generation of hydroxyl radicals, with the latter exhibiting a stronger bactericidal effect than the former.

Establishment of a cell-free translation system from rice callus extracts.

Eukaryotic in vitro translation systems require large numbers of protein and RNA components and thereby rely on the use of cell extracts. Here we established a new in vitro translation system based on rice callus extract (RCE). We confirmed that RCE maintains its initial activity even after five freeze-thaw cycles and that the optimum temperature for translation is around 20°C. We demonstrated that the RCE system allows the synthesis of hERG, a large membrane protein, in the presence of liposomes. We also showed that the introduction of a bicistronic mRNA based on 2A peptide to RCE allowed the production of two distinct proteins from a single mRNA. Our new method thus facilitates laboratory-scale production of cell extracts, making it a useful tool for the in vitro synthesis of proteins for biochemical studies.

Characterization of Bulk Nanobubbles Formed by Using a Porous Alumina Film with Ordered Nanopores.

Nanobubbles (NBs), with their unique physicochemical properties and promising applications, have become an important research topic. Generation of monodispersed bulk NBs with specified gas content remains a challenge. We developed a simple method for generating bulk NBs, using porous alumina films with ordered straight nanoscaled holes. Different techniques, such as nanoparticle tracking analysis (NTA), atomic force microscopy (AFM), and infrared absorption spectroscopy (IRAS), are used to confirm NB formation. The NTA data demonstrate that the minimum size of the NBs formed is less than 100 nm, which is comparable to the diameter of nanoholes in the porous alumina film. By generating NBs with different gases, including CO2, O2, N2, Ar, and He, we discovered that the minimum size of NBs negatively correlated with the solubility of encapsulated gases in water. Due to the monodispersed size of NBs generated from the highly ordered porous alumina, we determined that NB size is distributed discretely with a uniform increment factor of [Formula: see text]. To explain the observed characteristic size distribution of NBs, we propose a simple model in which two NBs of the same size are assumed to preferentially coalesce. This characteristic bubble size distribution is useful for elucidating the basic characteristics of nanobubbles, such as the long-term stability of NBs. This distribution can also be used to develop new applications of NBs, for example, nanoscaled reaction fields through bubble coalescence.

Self-Assembly of Hybrid Lipid Membranes Doped with Hydrophobic Organic Molecules at the Water/Air Interface.

Because of their unique properties, including an ultrathin thickness (3-4 nm), ultrahigh resistivity, fluidity and self-assembly ability, lipid bilayers can be readily functionalized and have been used in various applications such as bio-sensors and bio-devices. In this study, we introduced a planar organic molecule: copper (II) 2,9,16,23-tetra-tert-butyl-29H,31H-phthalocyanine (CuPc) to dope lipid membranes. The CuPc/lipid hybrid membrane forms at the water/air interface by self-assembly. In this membrane, the hydrophobic CuPc molecules are located between the hydrophobic tails of lipid molecules, forming a lipid/CuPc/lipid sandwich structure. Interestingly, an air-stable hybrid lipid bilayer can be readily formed by transferring the hybrid membrane onto a Si substrate. We report a straightforward method for incorporating nanomaterials into a lipid bilayer system, which represents a new methodology for the fabrication of biosensors and biodevices.