Utilizing a High-Performance Piezoelectric Nanocomposite as a Self-Activating Component in Piezotronic Artificial Mechanoreceptors.

Challenges such as poor dispersion and insufficient polarization of BaTiO3 (BTO) nanoparticles (NPs) within poly(vinylidene fluoride-co-trifluoroethylene) (P(VDF-TrFE)) composites have hindered their piezoelectricity, limiting their uses in pressure sensors, nanogenerators, and artificial sensory synapses. Here, we introduce a high-performance piezoelectric nanocomposite material consisting of P(VDF-TrFE)/modified-BTO (mBTO) NPs for use as a self-activating component in a piezotronic artificial mechanoreceptor. To generate high-performance piezoelectric nanocomposite materials, the surface of BTO is hydroxylated, followed by the covalent attachment of (3-aminopropyl)triethoxysilane to improve the dispersibility of mBTO NPs within the P(VDF-TrFE) matrix. We also aim to enhance the crystallization degree of P(VDF-TrFE), the efficiency characteristics of mBTO, and the poling efficiency, even when incorporating small amounts of mBTO NPs. The piezoelectric potential mechanically induced from the P(VDF-TrFE)/mBTO NPs nanocomposite was three times greater than that from P(VDF-TrFE) and twice as high as that from the P(VDF-TrFE)/BTO NPs nanocomposite. The piezoelectric potential generated by mechanical stimuli on the piezoelectric nanocomposite was utilized to activate the synaptic ionogel-gated field-effect transistor for the development of self-powered piezotronics artificial mechanoreceptors on a polyimide substrate. The device successfully emulated fast-adapting (FA) functions found in biological FA mechanoreceptors. This approach has great potential for applications to future intelligent tactile perception technology.

Intracellular Loop in the Brain Isoforms of Anoctamin 2 Channels Regulates Calcium-dependent Activation.

Anoctamin 2 (ANO2 or TMEM16B), a calcium-activated chloride channel (CaCC), performs diverse roles in neurons throughout the central nervous system. In hippocampal neurons, ANO2 narrows action potential width and reduces postsynaptic depolarization with high sensitivity to Ca2+ at relatively fast kinetics. In other brain regions, including the thalamus, ANO2 mediates activity-dependent spike frequency adaptations with low sensitivity to Ca2+ at relatively slow kinetics. How this same channel can respond to a wide range of Ca2+ levels remains unclear. We hypothesized that splice variants of ANO2 may contribute to its distinct Ca2+ sensitivity, and thus its diverse neuronal functions. We identified two ANO2 isoforms expressed in mouse brains and examined their electrophysiological properties: isoform 1 (encoded by splice variants with exons 1a, 2, 4, and 14) was expressed in the hippocampus, while isoform 2 (encoded by splice variants with exons 1a, 2, and 4) was broadly expressed throughout the brain, including in the cortex and thalamus, and had a slower calcium-dependent activation current than isoform 1. Computational modeling revealed that the secondary structure of the first intracellular loop of isoform 1 forms an entrance cavity to the calcium-binding site from the cytosol that is relatively larger than that in isoform 2. This difference provides structural evidence that isoform 2 is involved in accommodating spike frequency, while isoform 1 is involved in shaping the duration of an action potential and decreasing postsynaptic depolarization. Our study highlights the roles and molecular mechanisms of specific ANO2 splice variants in modulating neuronal functions.

Chemical gradients on graphene via direct mechanochemical cleavage of atoms from chemically functionalized graphene surfaces.

Manipulating the surface chemistry of graphene is critical to many applications that are achievable by chemical functionalization. Specifically, tailoring the spatial distribution of functional groups offers more opportunities to explore functionality using continuous changes in surface energy. To this end, careful consideration is required to demonstrate the chemical gradient on graphene surfaces, and it is necessary to develop a technique to pattern the spatial distribution of functional groups. Here, we demonstrate the tailoring of a chemical gradient through direct mechanochemical cleavage of atoms from chemically functionalized graphene surfaces via an atomic force microscope. Additionally, we define the surface characteristics of the fabricated sample by using lateral force microscopy revealing the materials' intrinsic properties at the nanoscale. Furthermore, we perform the cleaning process of the obtained lateral force images by using a machine learning method of truncated singular value decomposition. This work provides a useful technique for many applications utilizing continuous changes in the surface energy of graphene.

LPS induces microglial activation and GABAergic synaptic deficits in the hippocampus accompanied by prolonged cognitive impairment.

Neuroinflammation impacts the brain and cognitive behavior through microglial activation. In this study, we determined the temporal sequence from microglial activation to synaptic dysfunction and cognitive behavior induced by neuroinflammation in mice. We found that LPS injection activated microglia within a short period, followed by impairments in GABAergic synapses, and that these events led to long-term cognitive impairment. We demonstrated that, 3 days after LPS injection, microglia in the hippocampus were significantly activated due to the LPS-induced inflammation in association with alterations in cellular morphology, microglial density, and expression of phagocytic markers. GABAergic synaptic impairments were detected at 4-6 days after LPS treatment, a time when microglia activity had returned to normal. Consequently, memory impairment persisted for 6 days after injection of LPS. Our results suggest that neuroinflammation induces microglia activation, GABAergic synaptic deficits and prolonged memory impairment over a defined temporal sequence. Our observations provide insight into the temporal sequence of neuroinflammation-associated brain pathologies. Moreover, the specific loss of inhibitory synapses accompanying the impaired inhibitory synaptic transmission provides mechanistic insight that may explain the prolonged cognitive deficit observed in patients with neuroinflammation. Thus, this study provides essential clues regarding early intervention strategies against brain pathologies accompanying neuroinflammation.

Npas4 regulates IQSEC3 expression in hippocampal somatostatin interneurons to mediate anxiety-like behavior.

Activity-dependent GABAergic synapse plasticity is important for normal brain functions, but the underlying molecular mechanisms remain incompletely understood. Here, we show that Npas4 (neuronal PAS-domain protein 4) transcriptionally regulates the expression of IQSEC3, a GABAergic synapse-specific guanine nucleotide-exchange factor for ADP-ribosylation factor (ARF-GEF) that directly interacts with gephyrin. Neuronal activation by an enriched environment induces Npas4-mediated upregulation of IQSEC3 protein specifically in CA1 stratum oriens layer somatostatin (SST)-expressing GABAergic interneurons. SST+ interneuron-specific knockout (KO) of Npas4 compromises synaptic transmission in these GABAergic interneurons, increases neuronal activity in CA1 pyramidal neurons, and reduces anxiety behavior, all of which are normalized by the expression of wild-type IQSEC3, but not a dominant-negative ARF-GEF-inactive mutant, in SST+ interneurons of Npas4-KO mice. Our results suggest that IQSEC3 is a key GABAergic synapse component that is directed by Npas4 and ARF activity, specifically in SST+ interneurons, to orchestrate excitation-to-inhibition balance and control anxiety-like behavior.

Study on Human Activity Recognition Using Semi-Supervised Active Transfer Learning.

In recent years, various studies have begun to use deep learning models to conduct research in the field of human activity recognition (HAR). However, there has been a severe lag in the absolute development of such models since training deep learning models require a lot of labeled data. In fields such as HAR, it is difficult to collect data and there are high costs and efforts involved in manual labeling. The existing methods rely heavily on manual data collection and proper labeling of the data, which is done by human administrators. This often results in the data gathering process often being slow and prone to human-biased labeling. To address these problems, we proposed a new solution for the existing data gathering methods by reducing the labeling tasks conducted on new data based by using the data learned through the semi-supervised active transfer learning method. This method achieved 95.9% performance while also reducing labeling compared to the random sampling or active transfer learning methods.

Astrocytes Control Sensory Acuity via Tonic Inhibition in the Thalamus.

Sensory discrimination is essential for survival. However, how sensory information is finely controlled in the brain is not well defined. Here, we show that astrocytes control tactile acuity via tonic inhibition in the thalamus. Mechanistically, diamine oxidase (DAO) and the subsequent aldehyde dehydrogenase 1a1 (Aldh1a1) convert putrescine into GABA, which is released via Best1. The GABA from astrocytes inhibits synaptically evoked firing at the lemniscal synapses to fine-tune the dynamic range of the stimulation-response relationship, the precision of spike timing, and tactile discrimination. Our findings reveal a novel role of astrocytes in the control of sensory acuity through tonic GABA release.

Combined Method of Neuronal Cell-Inducible Vector and Valproic Acid for Enhanced Gene Expression under Hypoxic Conditions.

BACKGROUND: Gene therapy shows the ability to restore neuronal dysfunction via therapeutic gene expression. The efficiency of gene expression and delivery to hypoxic injury sites is important for successful gene therapy. Therefore, we established a gene/stem cell therapy system using neuron-specific enolase promoter and induced neural stem cells in combination with valproic acid to increase therapeutic gene expression in hypoxic spinal cord injury. METHODS: To examine the effect of combined method on enhancing gene expression, we compared neuronal cell-inducible luciferase levels under normoxia or hypoxia conditions in induced neural stem cells with valproic acid. Therapeutic gene, vascular endothelial growth factor, expression with combined method was investigated in hypoxic spinal cord injury model. We verified gene expression levels and the effect of different methods of valproic acid administration in vivo. RESULTS: The results showed that neuron-specific enolase promoter enhanced gene expression levels in induced neural stem cells compared to Simian Virus 40 promoter under hypoxic conditions. Valproic acid treatment showed higher gene expression of neuron-specific enolase promoter than without treatment. In addition, gene expression levels and cell viability were different depending on the various concentration of valproic acid. The gene expression levels were increased significantly when valproic acid was directly injected with induced neural stem cells in vivo. CONCLUSION: In this study, we demonstrated that the combination of neuron-specific enolase promoter and valproic acid induced gene overexpression in induced neural stem cells under hypoxic conditions and also in spinal cord injury depending on valproic acid administration in vivo. Combination of valproic acid and neuron-specific enolase promoter in induced neural stem cells could be an effective gene therapy system for hypoxic spinal cord injury.

CRISPR-mediated gene correction links the ATP7A M1311V mutations with amyotrophic lateral sclerosis pathogenesis in one individual.

Amyotrophic lateral sclerosis (ALS) is a severe disease causing motor neuron death, but a complete cure has not been developed and related genes have not been defined in more than 80% of cases. Here we compared whole genome sequencing results from a male ALS patient and his healthy parents to identify relevant variants, and chose one variant in the X-linked ATP7A gene, M1311V, as a strong disease-linked candidate after profound examination. Although this variant is not rare in the Ashkenazi Jewish population according to results in the genome aggregation database (gnomAD), CRISPR-mediated gene correction of this mutation in patient-derived and re-differentiated motor neurons drastically rescued neuronal activities and functions. These results suggest that the ATP7A M1311V mutation has a potential responsibility for ALS in this patient and might be a potential therapeutic target, revealed here by a personalized medicine strategy.

Enhanced surface plasmon microscopy based on multi-channel spatial light switching for label-free neuronal imaging.

In this paper, we have investigated multi-channel switching of light incidence in multiple directions to improve image clarity in surface plasmon microscopy (SPM) for robust and consistent imaging performance regardless of the pattern geometry and shape. Multi-channel light switching in SPM allows significant reduction of adverse scattering effects by surface plasmon (SP). For proof of concept, an eight-channel spatially switched SPM (ssSPM) system has been set up. The results with reference objects including square arrays and Siemens stars experimentally confirm much improved images with ssSPM by reducing the artifacts of SP scattering significantly. On a quantitative basis, contrast analysis preformed with square arrays shows image contrast enhanced by more than three times over conventional SPM. Three image reconstruction algorithms were evaluated for optimal image acquisition. It is suggested that averaging combined with minimum-filtering produces the highest resolution. ssSPM was applied to label-free imaging of primary neuron cultures and shown to present enhanced images with clarity far better than conventional SPM.

Superlocalized Three-Dimensional Live Imaging of Mitochondrial Dynamics in Neurons Using Plasmonic Nanohole Arrays.

We investigated the transport of neuronal mitochondria using superlocalized near-fields with plasmonic nanohole arrays (PNAs). Compared to traditional imaging techniques, PNAs create a massive array of superlocalized light beams and allow 3D mitochondrial dynamics to be sampled and extracted almost in real time. In this work, mitochondrial fluorescence excited by the PNAs was captured by an optical microscope using dual objective lenses, which produced superlocalized dynamics while minimizing light scattering by the plasmonic substrate. It was found that mitochondria move with an average velocity 0.33 ± 0.26 µm/s, a significant part of which, by almost 50%, was contributed by the movement along the depth axis ( z-axis). Mitochondrial positions were acquired with superlocalized precision (σ x = 5.7 nm and σ y = 11.8 nm) in the lateral plane and σ z = 78.7 nm in the z-axis, which presents an enhancement by 12.7-fold in resolution compared to confocal fluorescence microscopy. The approach is expected to serve as a way to provide 3D information on molecular dynamics in real time.

Comparison of point-source pollutant loadings to soil and groundwater for 72 chemical substances.

Fate and transport of 72 chemicals in soil and groundwater were assessed by using a multiphase compositional model (CompFlow Bio) because some of the chemicals are non-aqueous phase liquids or solids in the original form. One metric ton of chemicals were assumed to leak in a stylized facility. Scenarios of both surface spills and subsurface leaks were considered. Simulation results showed that the fate and transport of chemicals above the water table affected the fate and transport of chemicals below the water table, and vice versa. Surface spill scenarios caused much less concentrations than subsurface leak scenarios because leaching amounts into the subsurface environment were small (at most 6% of the 1 t spill for methylamine). Then, simulation results were applied to assess point-source pollutant loadings to soil and groundwater above and below the water table, respectively, by multiplying concentrations, impact areas, and durations. These three components correspond to the intensity of contamination, mobility, and persistency in the assessment of pollutant loading, respectively. Assessment results showed that the pollutant loadings in soil and groundwater were linearly related (r 2 = 0.64). The pollutant loadings were negatively related with zero-order and first-order decay rates in both soil (r = - 0.5 and - 0.6, respectively) and groundwater (- 1.0 and - 0.8, respectively). In addition, this study scientifically defended that the soil partitioning coefficient (K d) significantly affected the pollutant loadings in soil (r = 0.6) and the maximum masses in groundwater (r = - 0.9). However, K d was not a representative factor for chemical transportability unlike the expectation in chemical ranking systems of soil and groundwater pollutants. The pollutant loadings estimated using a physics-based hydrogeological model provided a more rational ranking for exposure assessment, compared to the summation of persistency and transportability scores in the chemical ranking systems. In the surface spill scenario, the pollutant loadings were zeros for all chemicals, except methylamine to soil whose pollutant loading was smaller than that in the subsurface leak scenario by 4 orders of magnitude. The maximum mass and the average mass multiplied by duration in soil greatly depended on leaching fluxes (r = 1.0 and 0.9, respectively), while the effect of leaching fluxes diminished below the water table. The contribution of this work is that a physics-based numerical model was used to quantitatively compare the subsurface pollutant loading in a chemical accident for 72 chemical substances, which can scientifically defend a simpler and more qualitative assessment of pollutant loadings. Besides, this study assessed pollutant loadings to soil (unsaturated zone) and groundwater (saturated zone) all together and discussed their interactions.

Growth of wrinkle-free graphene on texture-controlled platinum films and thermal-assisted transfer of large-scale patterned graphene.

Growth of large-scale patterned, wrinkle-free graphene and the gentle transfer technique without further damage are most important requirements for the practical use of graphene. Here we report the growth of wrinkle-free, strictly uniform monolayer graphene films by chemical vapor deposition on a platinum (Pt) substrate with texture-controlled giant grains and the thermal-assisted transfer of large-scale patterned graphene onto arbitrary substrates. The designed Pt surfaces with limited numbers of grain boundaries and improved surface perfectness as well as small thermal expansion coefficient difference to graphene provide a venue for uniform growth of monolayer graphene with wrinkle-free characteristic. The thermal-assisted transfer technique allows the complete transfer of large-scale patterned graphene films onto arbitrary substrates without any ripples, tears, or folds. The transferred graphene shows high crystalline quality with an average carrier mobility of ∼ 5500 cm(2) V(-1) s(-1) at room temperature. Furthermore, this transfer technique shows a high tolerance to variations in types and morphologies of underlying substrates.

Real-time concealed-object detection and recognition with passive millimeter wave imaging.

Millimeter wave (MMW) imaging is finding rapid adoption in security applications such as concealed object detection under clothing. A passive MMW imaging system can operate as a stand-off type sensor that scans people in both indoors and outdoors. However, the imaging system often suffers from the diffraction limit and the low signal level. Therefore, suitable intelligent image processing algorithms would be required for automatic detection and recognition of the concealed objects. This paper proposes real-time outdoor concealed-object detection and recognition with a radiometric imaging system. The concealed object region is extracted by the multi-level segmentation. A novel approach is proposed to measure similarity between two binary images. Principal component analysis (PCA) regularizes the shape in terms of translation and rotation. A geometric-based feature vector is composed of shape descriptors, which can achieve scale and orientation-invariant and distortion-tolerant property. Class is decided by minimum Euclidean distance between normalized feature vectors. Experiments confirm that the proposed methods provide fast and reliable recognition of the concealed object carried by a moving human subject.

Characteristics of stereo images from detectors in focal plane array.

The equivalent ray geometry of two horizontally aligned detectors at the focal plane of the main antenna in a millimeter wave imaging system is analyzed to reveal the reason why the images from the detectors are fused as an image with a depth sense. Scanning the main antenna in both horizontal and vertical directions makes each detector perform as a camera, and the two detectors can work like a stereo camera in the millimeter wave range. However, the stereo camera geometry is different from that of the stereo camera used in the visual spectral range because the detectors' viewing directions are diverging to each other and they are a certain distance apart. The depth sense is mainly induced by the distance between detectors. The images obtained from the detectors in the millimeter imaging system are perceived with a good depth sense. The disparities responsible for the depth sense are identified in the images.

Real-time outdoor concealed-object detection with passive millimeter wave imaging.

Millimeter wave imaging is finding rapid adoption in security applications such as the detection of objects concealed under clothing. A passive imaging system can be realized as a stand-off type sensor that can operate in open spaces, both indoors and outdoors. In this paper, we address real-time outdoor concealed-object detection and segmentation with a radiometric imaging system operating in the W-band. The imaging system is equipped with a dielectric lens and a receiver array operating at around 94 GHz. Images are analyzed by multilevel segmentation to identify a concealed object. Each level of segmentation comprises vector quantization, expectation-maximization, and Bayesian decision making to cluster pixels on the basis of a Gaussian mixture model. In addition, we describe a faster process that adopts only vector quantization for the first level segmentation. Experiments confirm that the proposed methods provide fast and reliable detection and segmentation for a moving human subject carrying a concealed gun.

Automatic image segmentation for concealed object detection using the expectation-maximization algorithm.

We address an image segmentation method to detect concealed objects captured by passive millimeter wave (MMW) imaging. Passive MMW imaging can create interpretable imagery on the objects concealed under clothing, which gives the great advantage to the security system. In this paper, we propose the multi-level expectation maximization (EM) method to separate the concealed objects from the other area in the image. We apply the EM method to obtain a Gaussian mixture model (GMM) of the acquired image. In the experiments, we evaluate the performance by the average probability of error. We will show that the consecutive EM processes separates the object area more accurately than the conventional EM method.