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As the evolutionary ancestor of Cas12 nuclease, the transposon (IS200/IS605)-encoded TnpB proteins act as compact RNA-guided DNA endonucleases. To explore their evolutionary diversity and potential as genome editors, we screened TnpBs from 64 annotated IS605 members and identified 25 active in Escherichia coli, of which three are active in human cells. Further characterization of these 25 TnpBs enables prediction of the transposon-associated motif (TAM) and the right-end element RNA (reRNA) directly from genomic sequences. We established a framework for annotating TnpB systems in prokaryotic genomes and applied it to identify 14 additional candidates. Among these, ISAam1 (369 amino acids (aa)) and ISYmu1 (382 aa) TnpBs demonstrated robust editing activity across dozens of genomic loci in human cells. Both RNA-guided genome editors demonstrated similar editing efficiency as SaCas9 (1,053 aa) while being substantially smaller. The enormous diversity of TnpBs holds potential for the discovery of additional valuable genome editors. Compact genome editors were discovered by mining a transposon library. [ABSTRACT FROM AUTHOR]

Objective: Abdominal aortic calcification (AAC) is an important marker of subclinical atherosclerosis and a predictor of cardiovascular disease. This study aims to explore the association between carotenoid intakes and AAC. Methods: We included 2889 participants from the National Health and Nutrition Examination Survey (NHANES). Dietary carotenoid intakes were obtained through 24-h dietary recall interviews. Severe AAC was defined as a Kauppila score > 5. The main analysis utilizes logistic and restricted cubic spline models. Result: Severe AAC was detected in 378 (13.08%) participants. In fully adjusted models, the odds ratios (OR) with 95% confidence intervals (CI) of α-carotene, β-carotene, β-cryptoxanthin, lycopene, lutein with zeaxanthin and total carotenoid intakes for individuals with severe AAC were 0.53 (0.23–0.77), 0.39 (0.19–0.80), 0.18 (0.05–0.62), 0.40 (0.20–0.78), 0.53 (0.32–0.88) and 0.38 (0.18–0.77) in the highest versus lowest quartile intake, respectively. Dose–response analyses revealed that all of the carotenoids were associated with decreased risk of severe AAC in a nonlinear trend. Total carotenoid intakes of at least 100ug/kg/day were associated with decreased odds for severe AAC. Conclusion: α-carotene, β-carotene, β-cryptoxanthin, lycopene, lutein with zeaxanthin and total carotenoids were inversely associated with the risk of severe AAC in adults. [ABSTRACT FROM AUTHOR]

Cell heterogeneity has impeded the accurate interpretation of the bulk transcriptome data from patients with diabetic nephropathy (DN). We performed an analysis by integrating bulk and single‐cell transcriptome datasets to uncover novel mechanisms leading to DN, especially in the podocytes. Microdissected glomeruli and tubules transcriptome datasets were selected from Gene Expression Omnibus (GEO). Then the consistency between datasets was evaluated. The analysis of the bulk dataset and single‐nucleus RNA dataset was integrated to reveal the cell type‐specific responses to DN. The candidate genes were validated in kidney tissues from DN patients and diabetic mice. We compared 4 glomerular and 4 tubular datasets and found considerable discrepancies among datasets regarding the deferentially expressed genes (DEGs), involved signaling pathways, and the hallmark enrichment profiles. Deconvolution of the bulk data revealed that the variations in cell‐type proportion contributed greatly to this discrepancy. The integrative analysis uncovered that the dysregulation of spermatogenesis‐related genes, including TEKT2 and PIAS2, was involved in the development of DN. Importantly, the mRNA level of TEKT2 was negatively correlated with the mRNA levels of NPHS1 (r = −.66, p <.0001) and NPHS2 (r = −.85, p <.0001) in human diabetic glomeruli. Immunostaining confirmed that the expression of TEKT2 and PIAS2 were up‐regulated in podocytes of DN patients and diabetic mice. Knocking down TEKT2 resisted high glucose‐induced cytoskeletal remodeling and down‐regulation of NPHS1 protein in the cultured podocyte. In conclusion, the integrative strategy can help us efficiently use the publicly available transcriptomics resources. Using this approach and combining it with classical research methods, we identified TEKT2 and PIAS2, two spermatogenesis‐related genes involved in the pathogenesis of DN. Furthermore, TEKT2 is involved in this pathogenesis by regulating the podocyte cytoskeleton. [ABSTRACT FROM AUTHOR]

Multimodal emotion recognition in conversational videos (ERC) develops rapidly in recent years. To fully extract the relative context from video clips, most studies build their models on the entire dialogues which make them lack of real-time ERC ability. Different from related researches, a novel multimodal emotion recognition model for conversational videos based on reinforcement learning and domain knowledge (ERLDK) is proposed in this paper. In ERLDK, the reinforcement learning algorithm is introduced to conduct real-time ERC with the occurrence of conversations. The collection of history utterances is composed as an emotion-pair which represents the multimodal context of the following utterance to be recognized. Dueling deep-Q-network (DDQN) based on gated recurrent unit (GRU) layers is designed to learn the correct action from the alternative emotion categories. Domain knowledge is extracted from public dataset based on the former information of emotion-pairs. The extracted domain knowledge is used to revise the results from the RL module and is transformed into other dataset to examine the rationality. The experimental results on datasets show that ERLDK achieves the state-of-the-art results on weighted average and most of the specific emotion categories. [ABSTRACT FROM AUTHOR]

Multimodal sentiment analysis is one of the most attractive interdisciplinary research topics in artificial intelligence (AI). Different from other classification issues, multimodal sentiment analysis of human is a much finer classification problem. However, most current work accept all multimodalities as the input together and then output final results at one time after fusion and decision processes. Rare models try to divide their models into more than one fusion modules with different fusion strategies for better adaption of different tasks. Additionally, most recent multimodal sentiment analysis methods pay great focuses on binary classification, but the accuracy of multi-classification still remains difficult to improve. Inspired by the emotional processing procedure in cognitive science, both binary and multi-classification abilities are improved in our method by dividing the complicated problem into smaller issues which are easier to be handled. In this paper, we propose a Hierarchal Attention-BiLSTM (Bidirectional Long-Short Term Memory) model based on Cognitive Brain limbic system (HALCB). HALCB splits the multimodal sentiment analysis into two modules responsible for two tasks, the binary classification and the multi-classification. The former module divides the input items into two categories by recognizing their polarity and then sends them to the latter module separately. In this module, Hash algorithm is utilized to improve the retrieve accuracy and speed. Correspondingly, the latter module contains a positive sub-net dedicated for positive inputs and a negative sub-nets dedicated for negative inputs. Each of these binary module and two sub-nets in multi-classification module possesses different fusion strategy and decision layer for matching its respective function. We also add a random forest at the final link to collect outputs from all modules and fuse them at the decision-level at last. Experiments are conducted on three datasets and compare the results with baselines on both binary classification and multi-classification tasks. Our experimental results surpass the state-of-the-art multimodal sentiment analysis methods on both binary and multi-classification by a big margin. [ABSTRACT FROM AUTHOR]

A new biosensor method was developed to determine residual carbofuran in tomatoes in a rapid and convenient fashion based on immobilizing acetylcholinesterase (AChE) on an electrode modified by concanavalin A (Con A)/polydopamine (PDA)-reduced graphene oxide (RGO)-gold nanoparticle (GNP) nanocomposites. The specific binding between Con A and AChE was investigated by the Ellman method and cyclic voltammetry (CV). The synthesis of nanocomposites was monitored by ultraviolet-visible absorption spectroscopy, scanning electron microscopy (SEM), and electrochemical impedance spectroscopy (EIS). The results showed that, due to the specific binding and good electrical conductivity, the biosensor had 2.2 times higher bioactivity, leading to high sensitivity with a low Michaelis constant of 0.10 mM. Parameters that affect the response of the biosensor, such as the pH, enzyme loading, ionic concentration, and inhibition time, were optimized. When used for the detection of carbofuran, this biosensor showed a wide range of applicability from 5 µg/kg to 40 µg/kg with a detection limit of 0.012 µg/kg. In addition, the biosensor demonstrated good recovery values of 101% and 90% for 10 µg/kg and 100 µg/kg of the analyte, good stability, high repeatability, and a rapid detection time of 20 min for carbofuran in tomatoes, which provides significant advantages for future analysis. [ABSTRACT FROM AUTHOR]

In this work, we reported a monodispersed MDM (metal–dielectric-metal) type upconversion composite material with ultrahigh emission enhancement for the first time. Different from the planar configuration of traditional MDM systems, the proposed materials here consisting of silver nanoparticles as the metallic core, upconversion nanoparticles(UCNPs) as the intermediate dielectric layer, and silver layer as the metallic shell. The structural characteristics were investigated to explore the spectral band match between the plasmonics and UCNPs. The sandwich structure can create high density hot carriers at the nearfield region around the UCNPs, leading to the remarkable excitation enhancement. According to the proper structure design, the upconversion intensity can be enhanced by over five orders of magnitude. The outer metallic layer thickness, the diameter of attached UCNPs and the ambient refractive index were found responsible for the intensity enhancement. Such upconversion materials combined the merit of monodispersity and the high emission efficiency, which can improve their performance in bioimaging and photovoltaic device. • The plasmonic absorptions band can be controlled to simultaneously match multiple excitation wavelength of UCNPs. • This Fluorescence enhancing strategy can be suitable for almost all common upconversion nanocrystals. • The upconversion intensity can be enhanced by over five orders of magnitude. • A monodisperse MDM nanocavity composite with high efficiency was proposed. [ABSTRACT FROM AUTHOR]

The thermal band of a satellite platform enables the measurement of land surface temperature (LST), which captures the spatial-temporal distribution of energy exchange between the Earth and the atmosphere. LST plays a critical role in simulation models, enhancing our understanding of physical and biochemical processes in nature. However, the limitations in swath width and orbit altitude prevent a single sensor from providing LST data with both high spatial and high temporal resolution. To tackle this challenge, the unmixing-based spatiotemporal fusion model (STFM) offers a promising solution by integrating data from multiple sensors. In these models, the surface reflectance is decomposed from coarse pixels to fine pixels using the linear unmixing function combined with fractional coverage. However, when downsizing LST through STFM, the linear mixing hypothesis fails to adequately represent the nonlinear energy mixing process of LST. Additionally, the original weighting function is sensitive to noise, leading to unreliable predictions of the final LST due to small errors in the unmixing function. To overcome these issues, we selected the U-STFM as the baseline model and introduced an updated version called the nonlinear U-STFM. This new model incorporates two deep learning components: the Dynamic Net (DyNet) and the Chang Ratio Net (RatioNet). The utilization of these components enables easy training with a small dataset while maintaining a high generalization capability over time. The MODIS Terra daytime LST products were employed to downscale from 1000 m to 30 m, in comparison with the Landsat7 LST products. Our results demonstrate that the new model surpasses STARFM, ESTARFM, and the original U-STFM in terms of prediction accuracy and anti-noise capability. To further enhance other STFMs, these two deep-learning components can replace the linear unmixing and weighting functions with minor modifications. As a deep learning-based model, it can be pretrained and deployed for online prediction. [ABSTRACT FROM AUTHOR]

Biological signals, including electroencephalography (EEG) and electrooculography (EOG), are often used to develop switches, which represent a class of typical asynchronous human–computer interfaces (HCIs) in which control and idle states need to be distinguished based on a criterion. Determining a satisfactory criterion for rapid and accurate discrimination between control and idle states remains a challenging issue, as EEG signals are highly noisy and nonstationary, and EOG signals are highly affected by unintended/spontaneous eye movements. Therefore, most existing EEG- or EOG-based switches are characterized by disadvantages of long response times (RTs) or high false positive rates (FPRs). The primary contribution of this work is the development of a novel EOG-based switch design, in which a visual trigger mechanism is introduced to guide the users’ blinks and to assist in detecting blinks. Specifically, the graphical user interface (GUI) includes a switch button that flashes once per 1.2 s. The user is instructed to blink synchronously with the flashes of the switch button to issue an on/off command while a single-channel EOG signal is collected. A waveform detection algorithm is applied to the ongoing EOG signal, which discriminates the intended and unintended blinks mainly based on the synchrony between the blink and the switch buttons flash. Once an intended blink, i.e., a blink corresponding to a button’s flash, is detected, the system issues an on/off command. As one application, the proposed EOG-based switch is used to produce start/stop commands for a wheelchair. Several online experiments were conducted with ten healthy subjects. An average accuracy of 99.5%, an RT of 1.3 s for issuing a switch command in the control state, and an average FPR of 0.10/min in the idle state were achieved. The experimental results therefore demonstrate the effectiveness of the single-channel EOG-based switch. [ABSTRACT FROM AUTHOR]

Multivariate pattern analysis (MVPA) approach applied to neuroimaging data, such as functional magnetic resonance imaging (fMRI) data, has received a great deal of attention because of its sensitivity to distinguishing patterns of neural activities associated with different stimuli or cognitive states. Generally, when using MVPA approach to decode the mental states or stimuli, a set of discriminative variables (e.g., voxels) is first selected. However, in most of existing MVPA methods, the selected variables do not contain all informative variables, since these selected variables are sufficient for decoding. In this paper, we propose a multivariate pattern analysis method based on sparse representation for decoding the brain states and localizing category-specific brain activation areas corresponding to two experimental conditions/tasks at the same time. Unlike traditional MVPA approaches, this method is designed to find informative variables as many as possible. We applied the proposed method to two judgement experiments: a gender discrimination and an emotion discrimination task, data analysis results demonstrate its effectiveness and potential applications. [ABSTRACT FROM AUTHOR]

To recognize individuals, the brain often integrates audiovisual information from familiar or unfamiliar faces, voices, and auditory names. To date, the effects of the semantic familiarity of stimuli on audiovisual integration remain unknown. In this functional magnetic resonance imaging (fMRI) study, we used familiar/unfamiliar facial images, auditory names, and audiovisual face-name pairs as stimuli to determine the influence of semantic familiarity on audiovisual integration. First, we performed a general linear model analysis using fMRI data and found that audiovisual integration occurred for familiar congruent and unfamiliar face-name pairs but not for familiar incongruent pairs. Second, we decoded the familiarity categories of the stimuli (familiar vs. unfamiliar) from the fMRI data and calculated the reproducibility indices of the brain patterns that corresponded to familiar and unfamiliar stimuli. The decoding accuracy rate was significantly higher for familiar congruent versus unfamiliar face-name pairs (83.2%) than for familiar versus unfamiliar faces (63.9%) and for familiar versus unfamiliar names (60.4%). This increase in decoding accuracy was not observed for familiar incongruent versus unfamiliar pairs. Furthermore, compared with the brain patterns associated with facial images or auditory names, the reproducibility index was significantly improved for the brain patterns of familiar congruent face-name pairs but not those of familiar incongruent or unfamiliar pairs. Our results indicate the modulatory effect that semantic familiarity has on audiovisual integration. Specifically, neural representations were enhanced for familiar congruent face-name pairs compared with visual-only faces and auditory-only names, whereas this enhancement effect was not observed for familiar incongruent or unfamiliar pairs. Hum Brain Mapp 37:4333-4348, 2016. © 2016 Wiley Periodicals, Inc. [ABSTRACT FROM AUTHOR]

Low molecular weight, uncharged, halogenated disinfection byproducts (DBPs) are poorly removed by the reverse osmosis and advanced oxidation process treatment units often applied for further treatment of municipal wastewater for potable reuse. Granular activated carbon (GAC) treatment effectively sorbed 22 halogenated DBPs. Conversion of the GAC to a cathode within an electrolysis cell resulted in significant degradation of the 22 halogenated DBPs by reductive electrolysis at −1 V vs. Standard Hydrogen Electrode (SHE). The lowest removal efficiency over 6 h electrolysis was for trichloromethane (chloroform; 47%) but removal efficiencies were >90% for 13 of the 22 DBPs. In all cases, DBP degradation was higher than in electrolysis-free controls, and degradation was verified by the production of halides as reduction products. Activated carbons and charcoal were more effective than graphite for electrolysis, with graphite featuring poor sorption for the DBPs. A subset of halogenated DBPs (e.g., haloacetonitriles, chloropicrin) were degraded upon sorption to the GAC, even without electrolysis. Using chloropicrin as a model, experiments indicated that this loss was attributable to the partial reduction of sorbed chloropicrin from reducing equivalents in the GAC. Reducing equivalents depleted by these reactions could be restored when the GAC was treated by reductive electrolysis. GAC treatment of an advanced treatment train effluent for potable reuse effectively reduced the concentrations of chloroform, bromodichloromethane and dichloroacetonitrile measured in the column influent to below the method detection limits. Treatment of the GAC by reductive electrolysis at −1 V vs. SHE over 12 h resulted in significant degradation of the chloroform (63%), bromodichloromethane (96%) and dichloroacetonitrile (99%) accumulated on the GAC. The results suggest that DBPs in advanced treatment train effluents could be captured and degraded continuously by reductive electrolysis using a GAC-based cathode. [ABSTRACT FROM AUTHOR]

Objective. This systematic review was conducted to evaluate the clinical effectiveness and safety of herbal medicine (HM) as an alternative management for hot flushes induced by endocrine therapy in breast cancer patients. Methods. Key English and Chinese language databases were searched from inception to July 2015. Randomized Controlled Trials (RCTs) evaluating the effects of HM on hot flushes induced by endocrine therapy in women with breast cancer were retrieved. We conducted data collection and analysis in accordance with the Cochrane Handbook for Systematic Reviews of Interventions. Statistical analysis was performed with the software (Review Manager 5.3). Results. 19 articles were selected from the articles retrieved, and 5 articles met the inclusion criteria for analysis. Some included individual studies showed that HM can relieve hot flushes as well as other menopausal symptoms induced by endocrine therapy among women with breast cancer and improve the quality of life. There are minor side effects related to HM which are well tolerated. Conclusion. Given the small number of included studies and relatively poor methodological quality, there is insufficient evidence to draw positive conclusions regarding the objective benefit of HM. Additional high quality studies are needed with more rigorous methodological approach to answer this question. [ABSTRACT FROM AUTHOR]

A novel SRAM cell tolerant to single-event upsets (SEUs) is presented in this paper. By adding four more transistors inside, the proposed circuit can obtain higher critical charge at each internal node compared to the conventional 6-transistor (6T) cell. Arrays of 2k-bit capacitance of these two designs were implemented in a 65 nm CMOS bulk technology for comparison purpose. Radiation experiments showed that, at the nominal 1.0 V supply voltage, the proposed cell achieves 47.1 % and 49.3 % reduction in alpha and proton soft error rates (SER) with an area overhead of 37 %. [ABSTRACT FROM AUTHOR]

A built-in single event upsets (SEUs) detector is presented in this paper. This detector utilizes charge sharing to detect an SEU in a sequential cell, and the detection process is analyzed through Accuro simulations in a 65 nm technology. The normal operation of this detector would not induce obvious performance degradation of the target circuit. Through using this detector, error correction can be achieved based on dual modular redundancy (DMR) while the related power is about 20.4 % lower than that induced by triple modular redundancy (TMR). [ABSTRACT FROM AUTHOR]

A radiation hardened by design (RHBD) latch and its temporally hardened version to tolerate double node upsets are proposed in this paper. C-Elements are used to construct structures for fault correction. The temporally hardened version can further tolerate some single-event transients (SETs) at input port and clock line. Compared with Quintuple Modular Redundancy (QMR), the proposed non-temporally and temporally hardened latches are more area and power efficient with improved propagation delays. Compared with several previously reported temporally hardened latches, the proposed temporally hardened latch may introduce lower performance loss induced as setup time increase. Several multi-node upset tolerant latches are also compared with these two designs in terms of area, power, and delay. A cell level soft error analysis (TFIT) shows that the upset threshold LETs of the proposed latches in 180 nm process are higher than 16 MeV-cm/mg. [ABSTRACT FROM AUTHOR]

In this paper, a new layout for SRAM 6T bitcell is presented. The new layout is a simple modification over the traditional 6T layout, but it has demonstrated better soft error tolerance over the traditional layout in radiation experiments. The area of the new layout is 31 % larger than the traditional layout. In TCAD simulation, it demonstrates over 2× smaller error cross section than the traditional layout. In alpha particle and proton experiments, its soft error rate can be reduced up to 73 % compared to the traditional layout. [ABSTRACT FROM AUTHOR]

Soft Error Rates (SER) of hardened and unhardened SRAM cells need to be experimentally characterized to determine their appropriate applications in radiation environments. This characterization is especially important when low supply voltage is preferred. In this paper, we developed an SRAM test chip with four cell arrays including two types of unhardened cells (standard 6T and subthreshold 10T) and two types of hardened cells (Quatro and DICE). This test chip was fabricated in a 65 nm bulk technology and irradiated by heavy ions at different supply voltages. Experimental results show that the SERs of 6T and 10T cells present significant sensitivities to supply voltages when the particle linear energy transfers (LETs) are relatively low. For Quatro and DICE cells, one does not consistently show superior hardening performance over the other. It is also noted that Quatro cells show significant advantage in single event resilience over 10T cells although they consume similar areas. TCAD simulations were carried out to validate the experimental data. In addition, the error amount distributions follow a Poisson distribution very well for each type of cell array. [ABSTRACT FROM AUTHOR]

The recently proposed modified-compressive sensing (modified-CS), which utilizes the partially known support as prior knowledge, significantly improves the performance of recovering sparse signals. However, modified-CS depends heavily on the reliability of the known support. An important problem, which must be studied further, is the recoverability of modified-CS when the known support contains a number of errors. In this letter, we analyze the recoverability of modified-CS in a stochastic framework. A sufficient and necessary condition is established for exact recovery of a sparse signal. Utilizing this condition, the recovery probability that reflects the recoverability of modified-CS can be computed explicitly for a sparse signal with nonzero entries. Simulation experiments have been carried out to validate our theoretical results. [ABSTRACT FROM AUTHOR]

In this paper, a hybrid brain–computer interface (BCI) system combining P300 and steady-state visual evoked potential (SSVEP) is proposed to improve the performance of asynchronous control. The four groups of flickering buttons were set in the graphical user interface. Each group contained one large button in the center and eight small buttons around it, all of which flashed at a fixed frequency (e.g., 7.5 Hz) to evoke SSVEP. At the same time, the four large buttons of the four groups were intensified through shape and color changes in a random order to produce P300 potential. During the control state, the user focused on a desired group of buttons (target buttons) to evoke P300 potential and SSVEP, simultaneously. Discrimination between the control and idle states was based on the detection of both P300 and SSVEP on the same group of buttons. As an application, this method was used to produce a “go/stop” command in real-time wheelchair control. Several experiments were conducted, and data analysis results showed that combining P300 potential and SSVEP significantly improved the performance of the BCI system in terms of detection accuracy and response time. [ABSTRACT FROM PUBLISHER]

Abstract: The effects of ultrasonication pre-treatment of graphene oxide (GO) on the mechanical properties of GO/poly(vinyl alcohol) (PVA) composites were studied. Results show that the mechanical properties are sensitive to ultrasonication time (or energy input) and there is an optimum ultrasonication time (OUT) that leads to the largest improvement in mechanical property. If the ultrasonication time is less than OUT, the GO sheets are not fully exfoliated, and only a partial reinforcement effect is achieved. Ultrasonication times longer than OUT cause a reduction of GO sheet size and impair the efficiency of mechanical improvement. The optimized ultrasonication energy input of 15Wh/L may serve as a general guideline for preparation of GO composites. [Copyright &y& Elsevier]

Abstract: The growing demand for compact point-of-care medical devices and portable instruments for on-site environmental sampling has stimulated intense research on flexible sensors that can be miniaturized and function under considerable physical deformation. We report a new type of flexible electrochemical biosensors based on free-standing graphene paper carrying binary nanocomposites of PtAu alloy and MnO2. The coral-like PtAu–MnO2 nanocomposites are grown on the substrate through one-step template-free electrodeposition, leading to an intimate contact between the PtAu alloy and MnO2 matrix. The flexible electrode exhibits a unique set of structural and electrochemical properties such as better uniformity, larger active surface areas, and faster electron transfer in comparison with the control electrode prepared by tandem growth of MnO2 network and PtAu alloy in two steps. In nonenzymatic amperometric glucose detection, the PtAu–MnO2 binary nanostructure-decorated graphene paper has shown greatly enhanced sensing performance such as wide liner range (0.1mM to 30.0mM), high sensitivity (58.54μAcm−2 mM−1), low detection limit (0.02mM, S /N=3), satisfactory selectivity, excellent reproducibility and stability, and tolerability to mechanical stress. The strategy of co-growth of metal and metal oxides on freestanding carbon substrates opens new possibility to develop high-performance flexible electrochemical sensors. [Copyright &y& Elsevier]

To control a cursor on a monitor screen, a user generally needs to perform two tasks sequentially. The first task is to move the cursor to a target on the monitor screen (termed a 2-D cursor movement), and the second task is either to select a target of interest by clicking on it or to reject a target that is not of interest by not clicking on it. In a previous study, we implemented the former function in an EEG-based brain–computer interface system using motor imagery and the P300 potential to control the horizontal and vertical cursor movements, respectively. In this study, the target selection or rejection functionality is implemented using a hybrid feature from motor imagery and the P300 potential. Specifically, to select the target of interest, the user must focus his or her attention on a flashing button to evoke the P300 potential, while simultaneously maintaining an idle state of motor imagery. Otherwise, the user performs left-/right-hand motor imagery without paying attention to any buttons to reject the target. Our data analysis and online experimental results validate the effectiveness of our approach. The proposed hybrid feature is shown to be more effective than the use of either the motor imagery feature or the P300 feature alone. Eleven subjects attended our online experiment, in which a trial involved sequential 2-D cursor movement and target selection. The average duration of each trial and average accuracy of target selection were 18.19 s and 93.99\%, respectively, and each target selection or rejection event was performed within 2 s. [ABSTRACT FROM PUBLISHER]

Abstract: A surface-draw method to fabricate recyclable carbon nanotube/polyvinyl butyral (CNT/PVB) composite fibers is reported. This method is effective for both single-walled carbon nanotube (SWCNT) and multi-walled carbon nanotube. The CNT mass content of CNT/PVB composite fibers can vary from 0 to 80wt.%, which is higher than most CNT/polymer composites reported to date. The diameter of the composite fibers can be controlled in the range of 10–100μm, with essentially unlimited draw length. The composite fibers with 7.4wt.% SWCNTs showed optimal tensile properties. Compared with pure PVB fibers, the tensile strength, failure strain, and elastic modulus of the composite fiber have improved about 127%, 27%, and 73%, respectively. In addition, SWCNT/PVB composites with 66.7wt.% SWCNTs have the highest conductivity of 42.9Sm−1. More importantly, the major benefit is the “greenness” of the method, which involves environment friendly ethanol–water solvent with no functionalization of the nanotube required, and only simple apparatus are needed. The CNT/PVB composite fibers obtained can be dissolved in ethanol solution and reformed with the surface draw method without any additional treatment; and the material properties after recycle is comparable to those fabricated in the first round. [Copyright &y& Elsevier]

Abstract: In this paper, we first present a self-training semi-supervised support vector machine (SVM) algorithm and its corresponding model selection method, which are designed to train a classifier with small training data. Next, we prove the convergence of this algorithm. Two examples are presented to demonstrate the validity of our algorithm with model selection. Finally, we apply our algorithm to a data set collected from a P300-based brain computer interface (BCI) speller. This algorithm is shown to be able to significantly reduce training effort of the P300-based BCI speller. [Copyright &y& Elsevier]

Abstract: This paper discusses blind source extraction in various ill-conditioned cases based on a simple extraction network model. Extractability is first analyzed for the following ill-conditioned cases: the mixing matrix is square but singular, the number of sensors is smaller than that of sources, the number of sensors is larger than that of sources but the column rank of mixing matrix is deficient, and the number of sources is unknown and the column rank of mixing matrix is deficient. A necessary and sufficient condition for extractability is obtained. A cost function and an unsupervised learning algorithm for the extraction network model are developed. Simulation results are also presented to show the validity of the theoretical results and the performance and characteristics of the learning algorithm. [Copyright &y& Elsevier]

This paper proposes a novel grouping decision approach for blind source estimation of FIR (finite impulse response) channels with binary sources. First, solvability is discussed for single-input systems and multi-input systems. Necessary and sufficient conditions for recoverability are derived. For single-input systems, a new deterministic algorithm based on grouping and decision is proposed to recover the source up to a delay. The algorithm is easy to implement and has several advantages. For instance, when the solvability conditions are satisfied, it can be applied to cases in which: (i) the channel has zeros on the unit circle or outside of the unit circle; (ii) there are fewer sensors than sources; (iii) the source is temporarily dependent. To improve noise tolerance and reduce computational cost, the algorithm is further elaborated for highly noisy channels and high-order FIR channels, respectively. For the channels with high unimodal noise, fewer peaks appear in the probability density function (pdf) of the outputs compared to the pdf of the outputs of channels with a higher SNR. After the peaks representing cluster centers are estimated using a maximum likelihood (ML) approach, the deterministic algorithm can be used. Similar to highly noisy channels, the algorithm is also effective for high-order, exponentially decaying channels after fewer cluster centers are estimated. Furthermore, blind source estimation for multi-input systems also can be carried out as with the case of single input systems. Two deflation algorithms are presented for temporarily dependent sources and i.i.d. sources. Based on the source estimation and deflation algorithms, the sources can be obtained one by one. Finally, the validity and performance of the algorithms are illustrated by several simulation examples. [Copyright &y& Elsevier]

This paper discusses the bifurcation on the oscillation of the following second order ordinary differential equation:x″(t)+tλp(t)f(x)=0.Several conditions for the functions p(t), f(x) are obtained, under which the equation is nonoscillatory as λ<−1, and oscillatory as λ>−1, that is, λ=−1 is a bifurcation value on oscillation of the equation. [Copyright &y& Elsevier]

Presents information on a study which introduced a technique for sequential blind extraction of singularly mixed source signals. Description of a neural-network model and an adaptive algorithm for single-source blind extraction; Stability of the algorithm ; Simulation results; Conclusions.

How to effectively regulate the spread of Internet public opinion from multisubject is the focus that governments around the world need to face. From the cross perspective of multilayer network and multisubject association, this paper studies the diffusion mechanism of Internet public opinion, constructs the multilayer network of Internet public opinion and its diffusion model, and then systematically analyzes the evolution characteristics of Internet public opinion diffusion. The main conclusions of the study are as follows: it is easier to trigger the spread of Internet public opinion by establishing associations among netizens in a preferred way. When the probability of random connection in different layers increases synchronously, the diffusion intensity of Internet public opinion shows a gradual downward trend. The intensity of government intervention has the greatest impact on the diffusion intensity of Internet public opinion. When the factors of netizens, Internet platform, and government interact, it can effectively reduce the intensity and scope of Internet public opinion diffusion. Once the media participate, it will improve the complexity of Internet public opinion diffusion. The government's intervention in Internet public opinion is a "double-edged sword," which needs to set the intervention intensity according to different subjects and their factor characteristics. This study can provide a theoretical reference for formulating strategies to adjust Internet public opinion diffusion from the cross perspective of multilayer network and multisubject association. [ABSTRACT FROM AUTHOR]

In this paper, the general class of singular systems with delay and second order linear constant coefficients singular systems with delay, is considered. First, for singular systems with delay, new definitions of stability are presented, and general sufficient stability conditions and instability conditions are derived. Secondly, these results are applied to the analysis of stability and instability of second-order linear constant coefficients singular systems with delay, the location of a possible bifurcation is discovered. [ABSTRACT FROM AUTHOR]

Cyclin-dependent kinase 9 (CDK9) is an increasingly important potential cancer treatment target. Nowadays, developing selective CDK9 inhibitors has been extremely challenging as its ATP-binding sites are similar with other CDKs. Here, we report that the CDK9 inhibitor BAY-1143572 is converted into a series of proteolysis targeting chimeras (PROTACs) which leads to several compounds inducing the degradation of CDK9 in acute myeloid leukemia cells at a low nanomolar concentration. In addition, the most potent PROTAC molecule B03 could inhibit cell growth more effectively than warhead alone, with little inhibition of other kinases. This enhanced antiproliferative activity is mediated by a slight increase in kinase inhibitory activity and an increase in the level of apoptosis induction. Moreover, B03 could induce the degradation of CDK9 in vivo. Our work provides evidence that B03 represents a lead for further development and that CDK9 degradation is a potential valuable therapeutic strategy in acute myeloid leukemia. Image 1 • A series of CDK9 PROTACs have been obtained through the conversion of a selective inhibitor BAY-1143572. • The most promising compound B03 has high kinase selectivity profiles. • Compound B03 remarkably inhibit the growth of acute myeloid leukemia cells. • B03 could degrade CDK9 effectively in vitro and in vivo. [ABSTRACT FROM AUTHOR]

A triple modular redundancy (TMR) based design technique for double cell upsets (DCUs) mitigation is investigated in this paper. This technique adds three extra self-voter circuits into a traditional TMR structure to enable the enhanced error correction capability. Fault-injection simulations show that the soft error rate (SER) of the proposed technique is lower than 3% of that of TMR. The implementation of this proposed technique is compatible with the automatic digital design flow, and its applicability and performance are evaluated on an FIFO circuit. [ABSTRACT FROM AUTHOR]

Phenotypic transformation of vascular smooth muscle cells (VSMCs) plays a crucial role in abdominal aortic aneurysm (AAA) formation. CARMN, a highly conserved, VSMC-enriched long noncoding RNA (lncRNA), is integral in orchestrating various vascular pathologies by modulating the phenotypic dynamics of VSMCs. The influence of CARMN on AAA formation, particularly its mechanisms, remains enigmatic. Our research, employing single-cell and bulk RNA sequencing, has uncovered a significant suppression of CARMN in AAA specimens, which correlates strongly with the contractile function of VSMCs. This reduced expression of CARMN was consistent in both 7- and 14-day porcine pancreatic elastase (PPE)-induced mouse models of AAA and in human clinical cases. Functional analyses disclosed that the diminution of CARMN exacerbated PPE-precipitated AAA formation, whereas its augmentation conferred protection against such formation. Mechanistically, we found CARMN's capacity to bind with SRF, thereby amplifying its role in driving the transcription of VSMC marker genes. In addition, our findings indicate an enhancement in CAMRN transcription, facilitated by the binding of NRF2 to its promoter region. Our study indicated that CARMN plays a protective role in preventing AAA formation and restrains the phenotypic transformation of VSMC through its interaction with SRF. Additionally, we observed that the expression of CARMN is augmented by NRF2 binding to its promoter region. These findings suggest the potential of CARMN as a viable therapeutic target in the treatment of AAA. [ABSTRACT FROM AUTHOR]

Many studies have highlighted the importance of moderate exercise. While it can attenuate diabetic kidney disease, its mechanism has remained unclear. The level of myokine irisin in plasma increases during exercise. We found that irisin was decreased in diabetic patients and was closely related to renal function, proteinuria, and podocyte autophagy injury. Muscle‐specific overexpression of PGC‐1α (mPGC‐1α) in a mouse model is known to increase plasma irisin levels. The mPGC‐1α mice were crossed with db/m mice to obtain db/db mPGC‐1α+ mice in the present study. Compared to db/db mice without mPGC‐1α, plasma irisin was increased, and albuminuria and glomerular pathological damage were both alleviated in db/db mPGC‐1α+ mice. Impaired autophagy in podocytes was restored as well. Irisin inhibited the activation of the PI3K/AKT/mTOR signaling pathway in cultured human podocytes and improved damaged autophagy induced by high glucose levels. Then, db/db mice were treated with recombinant irisin, which had similar beneficial effects on the kidney as those in db/db mPGC‐1α+ mice, with alleviated glomerular injury and albuminuria. Moreover, the autophagy in podocytes was also significantly restored. These results suggest that irisin secreted by skeletal muscles protects the kidney from diabetes mellitus damage. It also restores autophagy in podocytes by inhibiting the abnormal activation of the PI3K/AKT/mTOR signaling pathway. Thus, irisin may become a new drug for the prevention and treatment of diabetic nephropathy. [ABSTRACT FROM AUTHOR]

Abstract Accurately and effectively mapping and evaluating cultivated land fallow has already become an important issue that has received much attention in China. However, systematically analysing regional cultivated land fallow remains inadequate because current studies have mainly focused on quantifying cultivated land fallow using statistical data based on administrative units or a single aspect of cultivated land fallow using high or medium spatial resolution images at the local or regional scales. Against the existing shortcomings, this study first developed an integrated index of cultivated land fallow (ILF) for mapping and evaluating cultivated land fallow in Southwest China using multisource spatial data. The performance of the ILF was validated by comparing its results with Google Earth images and ecological carrying capacity of cultivated land (TEC). And the spatial distribution of cultivated land fallow in Southwest China was evaluated at the regional, provincial and metropolitan scales. The results revealed that the ILF provided a reliable evaluation of cultivated land fallow in Southwest China. Compared to the Google earth images, the pixel with the high ILF value was the cultivated land that was found to prioritize fallow. There was also a significant correlation between ILF and TEC at the prefectural level in Sichuan, with an R 2 value >0.65. In Southwest China, the cultivated land related to highly appropriate fallow (HAF) accounted for 5.73% of the total cultivated land in 2010. The cultivated land related to inappropriate fallow (IF) accounted for 53.26% and 37.36% in Sichuan and Chongqing but only comprised 22.90% and 19.72% in Yunnan and Guizhou, respectively. Special attention needs to be paid to Guiyang and Kunming, where the HAF made up 25.38% and 17.48% of their total cultivated land, respectively. Human activities have been found to already become the most important impact factors for cultivated land fallow in Southwest China. This study is especially valuable for providing a scientific basis for policy-making on viable cultivated land fallow policy in Southwest China. Graphical abstract Unlabelled Image Highlights • A simple and direct way was proposed to map cultivated land fallow in Southwest China. • The spatial distribution of cultivated land fallow in Southwest China was evaluated from multiscale perspectives. • Human activities are among the major impact factors of cultivated land fallow in Southwest China. [ABSTRACT FROM AUTHOR]

Forest fires are one of the most severe natural disasters facing global ecosystems, as they have a significant impact on ecological security and social development. As remote sensing technology has developed, burned areas can now be quickly extracted to support fire monitoring and post-disaster recovery. This study focused on monitoring forest fires that occurred in Chongqing, China, in August 2022. The burned area was identified using various satellite images, including Sentinel-2, Landsat8, Environmental Mitigation II A (HJ2A), and Gaofen-6 (GF-6). The burned area was extracted using visual interpretation, differenced Normalized Difference Vegetation Index (dNDVI), and differenced Normalized Burnup Ratio (dNBR). The results showed that: (1) The results of the three monitoring methods were very consistent, with a coefficient of determination R2 > 0.96. (2) A threshold method based on the dNBR-extracted burned area was used to analyze fire severity, with moderate-severity fires making up the majority (58.05%) of the fires. (3) Different topographic factors had some influence on the severity of the forest fires. High elevation, steep slopes and the northwestern aspect had the largest percentage of burned area. [ABSTRACT FROM AUTHOR]

Background: This study aimed to develop and validate a deep learning (DL) model to identify atelectasis and attic retraction pocket in cases of otitis media with effusion (OME) using multi-center otoscopic images. Method: A total of 6393 OME otoscopic images from three centers were used to develop and validate a DL model for detecting atelectasis and attic retraction pocket. A threefold random cross-validation procedure was adopted to divide the dataset into training validation sets on a patient level. A team of otologists was assigned to diagnose and characterize atelectasis and attic retraction pocket in otoscopic images. Receiver operating characteristic (ROC) curves, including area under the ROC curve (AUC), accuracy, sensitivity, and specificity were used to assess the performance of the DL model. Class Activation Mapping (CAM) illustrated the discriminative regions in the otoscopic images. Results: Among all OME otoscopic images, 3564 (55.74%) were identified with attic retraction pocket, and 2460 (38.48%) with atelectasis. The diagnostic DL model of attic retraction pocket and atelectasis achieved a threefold cross-validation accuracy of 89% and 79%, AUC of 0.89 and 0.87, a sensitivity of 0.93 and 0.71, and a specificity of 0.62 and 0.84, respectively. Larger and deeper cases of atelectasis and attic retraction pocket showed greater weight, based on the red color depicted in the heat map of CAM. Conclusion: The DL algorithm could be employed to identify atelectasis and attic retraction pocket in otoscopic images of OME, and as a tool to assist in the accurate diagnosis of OME. [ABSTRACT FROM AUTHOR]

In recent years, the retrieval and validation of remotely-sensed leaf area index (LAI) products over complex land surfaces have received much attention due to the high-precision land surface model simulations and applications in global climate change. However, most of these related researches mainly focus on coarse resolution products. This is because few products have been specifically designed for solving the problems derived from complex land surfaces in mountain areas until now. MuSyQ LAI is a new product derived from Gaofen-1 (GF-1) satellite data. This product is characterized with a temporal resolution of 10 days and a spatial resolution of 16 m. As is well known, high-resolution products have less uncertainties because of the homogeneities of sub-pixel. Therefore, to evaluate the precision and uncertainty of MuSyQ LAI, an up-scaling strategy was employed here to validate MuSyQ LAI for three mountain regions in Southwest China. The validation strategy can be divided into three parts. First, a regression model was built by in situ LAI measured by LAI-2200 and the normalized difference vegetation index (NDVI) from unmanned aerial vehicle (UAV) images to obtain a 0.5 m resolution LAI map. Second, an up-scaled LAI map with a spatial resolution consistent with MuSyQ LAI was calculated by the pixel-averaging method from the UAV-based LAI map. Third, the MuSyQ LAI was validated by the up-scaled UAV-based LAI in pixel scale. Simultaneously, the sources of uncertainty were analyzed and compared from the view of data source, retrieval model, and scale effects. The results suggested that MuSyQ LAI in the study areas are significantly underestimated by 53.69% due to the complex terrain and heterogeneous land cover. There are three main reasons for the underestimation. The differences between GF-1 reflectance and UAV-based reflectance employed to estimate LAI are the largest factors for the validation results, even accounting for 61.47% of the total bias. Subsequently, the scale effects led to about 28.44% bias. Last but not least, the models employed to retrieve LAI contributed merely 10.09% uncertainties to the total bias. In conclusion, the accuracy of MuSyQ LAI still has a large space to be improved from the view of reflectance over complex terrain. This study is quite important for applications of MuSyQ LAI products and also provides a reference for the improvement and application of other high-resolution remotely sensed LAI products. [ABSTRACT FROM AUTHOR]

Lanthanide-doped up-conversion nanoparticles (UCNPs) can be widely used as near-infrared absorbing photoactive materials in bioimaging and photovoltaic devices. However, the low absorption cross section and low luminescence quantum rate of UCNPs significantly limit its use. Therefore, a hexagonal gold pillar nano-array structure consisting of UCNPs, gold pillar arrays, gold film and silica layer is proposed. By optimizing the structural parameters, the surface plasmon resonance wavelengths are simultaneously matched with the 808 nm excitation wavelength and 450 nm emission wavelength of the UCNPs. The gap-mode nanocavity confines the incident excitation radiation to nanophotonic hotspots with greatly high field strengths, thus theoretically proposed an efficient strategy to enhance the up-conversion luminescence. The plasmonic structure investigated in this study combines the advantages of ease of processing, high absorption, low loss and good controllability of its localized surface plasmon resonance. It provides a new solution for up-conversion enhancement design of gap-mode nanocavities. [ABSTRACT FROM AUTHOR]

Experimental studies on DNA transposable elements (TEs) have been limited in scale, leading to a lack of understanding of the factors influencing transposition activity, evolutionary dynamics, and application potential as genome engineering tools. We predicted 130 active DNA TEs from 102 metazoan genomes and evaluated their activity in human cells. We identified 40 active (integration-competent) TEs, surpassing the cumulative number (20) of TEs found previously. With this unified comparative data, we found that the Tc1/ mariner superfamily exhibits elevated activity, potentially explaining their pervasive horizontal transfers. Further functional characterization of TEs revealed additional divergence in features such as insertion bias. Remarkably, in CAR-T therapy for hematological and solid tumors, Mariner2_AG (MAG), the most active DNA TE identified, largely outperformed two widely used vectors, the lentiviral vector and the TE-based vector SB100X. Overall, this study highlights the varied transposition features and evolutionary dynamics of DNA TEs and increases the TE toolbox diversity. [Display omitted] • Forty active DNA TEs from mining 102 metazoan genomes increase the TE toolbox diversity • Tc1 elements with high copy numbers and IR-DR structures tend to show high activity • Active TEs show diverged functional features such as insertion profile and cargo capacity • MAG outperforms lentiviral vectors in CAR-T cell therapy A heterologous survey of 130 DNA transposable elements (TEs) in human cells not only unveils evolutionary and functional features linked to transposition activity but also expands the TE-based genome engineering toolbox by incorporating functionally diverse TEs, particularly the highly potent MAG. [ABSTRACT FROM AUTHOR]

In recent years, various applications of brain computer interfaces (BCIs) have been studied. In this paper, we present a hybrid BCI combining P300 and motor imagery to operate an explorer. Our system is mainly composed of a BCI mouse, a BCI speller and an explorer. Through this system, the user can access his computer and manipulate (open, close, copy, paste, and delete) files such as documents, pictures, music, movies and so on. The system has been tested with five subjects, and the experimental results show that the explorer can be successfully operated according to subjects’ intentions. [ABSTRACT FROM AUTHOR]

In recent years, neuroimaging studies have remarkably demonstrated the presence of cognitive motor dissociation in patients with disorders of consciousness (DoC). These findings accelerated the development of brain–computer interfaces (BCIs) as clinical tools for behaviorally unresponsive patients. This article reviews the recent progress of BCIs in patients with DoC and discusses the open challenges. In view of the practical application of BCIs in patients with DoC, four aspects of the relevant literature are introduced: consciousness detection, auxiliary diagnosis, prognosis, and rehabilitation. For each aspect, the paradigm design, brain signal processing methods, and experimental results of representative BCI systems are analyzed. Furthermore, this article provides guidance for BCI design for patients with DoC and discusses practical challenges for future research. [ABSTRACT FROM AUTHOR]

It is essential to explore Fe-MOFs catalysts containing both multiple active sites and rapid charge separation for improving photo-Fenton performance. Herein, a defect and doping engineering mediated M-D-MIL(Fe)/Cu-C 3 N 4 heterojunction with dual active centers was prepared and its removal performance was investigated against tetracycline hydrochloride. Characterization confirms that: (1) The ligand vacancies in M-D-MIL(Fe) can expose plenty of coordinatively unsaturated metal sites (Fe CUS), which enhance the Lewis acidity and optimize the adsorption of H 2 O 2. Meanwhile, the built-in dual redox centers (Fe3+/Fe2+ and Cu+/Cu2+) can synergistically promote the activation of H 2 O 2. (2) The ligand vacancies in M-D-MIL(Fe) and copper ion in C 3 N 4 as electron trapping sites can optimize the carrier separation of single-component materials. Furthermore, the composites exhibit a suitable energy band structure, an oriented built-in electric field, and tight interfacial contacts, all of which collectively create an optimal pathway and driving force for the efficient transport of photoinduced charges. This, in turn, accelerates the Fe3+/Fe2+ redox cycle. Finally, M-D-MIL(Fe)/Cu-C 3 N 4 demonstrates excellent photo-Fenton performance at low H 2 O 2 concentrations (5 mM), with a kinetic rate (k) of 0.035 min⁻¹, which is 14.58, 18.42, 1.94, and 15.21 times higher than those of MIL-100(Fe), C 3 N 4 , M-D-MIL(Fe), and Cu-C 3 N 4 , respectively. The study presents an innovative idea with potential applications in environmental restoration. • A M-D-MIL(Fe)/Cu-C 3 N 4 heterojunction with dual active centers was fabricated by defect and doping engineering. • Ligand vacancy intensified Lewis acidity. • The ligand vacancy, copper ion and built-in electric field improved the charge separation to promote Fe3+ reduction. • The built-in dual redox centers (Fe3+/Fe2+ and Cu+/Cu2+) played an important role in TC-HCl degradation. • •M-D-MIL(Fe)/Cu-C 3 N 4 as photo-Fenton catalyst exhibited superior photo-Fenton activity. [ABSTRACT FROM AUTHOR]

Abstract: While common spatial pattern may be the most widely used feature for discriminating motor imagery based EEG signals, Rayleigh coefficient maximization enable us to have one more effective. However, such a feature is often deteriorated by redundant electrode channels which may result in low classification accuracy, extra subsequent computational load and difficulty in understanding which part of the brain relates to classification-relevant activity. In this paper, we present a channel selection method to deal with these problems, in which an improved genetic algorithm based on the Rayleigh coefficient feature is conducted to determine the optimal subset of channels. Experiment results on two motor imagery EEG datasets verify that our method is effective in channel selection for classifying motor imagery EEG signals. [Copyright &y& Elsevier]

Background: Endothelial dysfunction is an early sign of diabetic cardiovascular disease and may contribute to progressive diabetic nephropathy (DN). There is increasing evidence that dysfunction of the endothelial tight junction is a crucial step in the development of endothelial hyperpermeability, but it is unknown whether this occurs in glomerular endothelial cells (GEnCs) during the progression of DN. We examined tight junction dysfunction of GEnCs during early-stage DN and the potential underlying mechanisms. We also examined the effect of simvastatin (3-Hydroxy-3-methylglutaryl CoA reductase inhibitor) on dysfunction of the tight junctions of cultured GEnCs and in db/db mice with early-stage DN. Methods: We assessed the expression of occludin and ZO-1, two major components of the tight junction complex, in cultured rat GEnCs treated with high glucose and in 12 week-old db/db mice with early-stage DN. We also investigated activation of RhoA/ROCK1 signaling, GEnC permeability, and renal function of the mice. Results: High glucose suppresses occludin expression and disrupts occludin/ZO-1 translocation in GEnCs. These changes were associated with increased permeability to albumin and activation of RhoA/ROCK1 signaling. Occludin and ZO-1 dysregulation also occurred in the glomeruli of mice with early-stage DN, and these abnormalities were accompanied by albuminuria and activation of RhoA/ROCK1 in isolated glomeruli. Simvastatin prevented high glucose or hyperglycemia-induced dysregulation of occludin and ZO-1 by inhibition of RhoA/ROCK1 signaling in cultured GEnCs and in db/db mice with early-stage DN. Conclusion: Our results indicate that activation of RhoA/ROCK1 by high glucose disrupts the expression and translocation of occludin/ZO-1 and that simvastatin alleviates occludin/ZO-1 dysregulation and albuminuria by suppressing RhoA/ROCK1 signaling during early-stage DN. These results suggest a potential therapeutic strategy for preventing the onset of albuminuria in early-stage DN. [ABSTRACT FROM AUTHOR]