Key message
G protein couples MAPK cascade through maize heterotrimeric Gβ subunit MGB1.
Heterotrimeric G protein Gβ interacts with Gγ subunit to generate Gβγ dimer in modulation of various ...biological processes. The modulatory events at transcriptome scale of plant Gβ subunit remain largely unknown. To reveal the regulatory basis of Gβ subunit at transcriptome level, we first identified a canonical maize Gβ subunit MGB1 that physically interacted with Type C Gγ protein MGG4. For transcriptome analysis, two independent CRISPR/Cas9-edited
MGB1
lines were generated, which all exhibited growth arrest, suggestive of MGB1 essential for maize seedling establishment. Transcriptomic outcomes showed that
MGB1
knockout resulted in elevated transcriptional abundance of plant immune response marker
PR
and immune receptor
RPM1
. Integrated GO, KEGG, and GSEA analyses pinpointed the enrichment of differentially expressed genes in defense response pathway. Functional association network construction revealed MAPK cascade components and PR protein as hub regulators of
MGB1
-mediated immune signaling. MGB1 and scaffold protein ZmRACK1 together with MAPK cascade components coordinately modulated maize immune responses. We built a modulatory hierarchy of Gβ subunit at transcriptome and interacting scales, which is informative for our understanding of the regulatory basis of G protein signaling.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
•An adaptive weighted least squares support vector regression (AWLSSVR) is proposed to model the rate-dependent hysteresis of piezoelectric actuators.•The AWLSSVR hyperparameters are optimized by ...using particle swarm optimization.•An adaptive weighting strategy is proposed to eliminate the effects of noises in the training dataset and reduce the sample size at the same time.•The results show that the AWLSSVR is more accurate than other versions of least squares support vector regression.
To overcome the low positioning accuracy of piezoelectric actuators (PZAs) caused by the hysteresis nonlinearity, this paper proposes an adaptive weighted least squares support vector regression (AWLSSVR) to model the rate-dependent hysteresis of PZA. Firstly, the AWLSSVR hyperparameters are optimized by using particle swarm optimization. Then an adaptive weighting strategy is proposed to eliminate the effects of noises in the training dataset and reduce the sample size at the same time. Finally, the proposed approach is applied to predict the hysteresis of PZA. The results show that the proposed method is more accurate than other versions of least squares support vector regression for training samples with noises, and meanwhile reduces the sample size and speeds up calculation.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK, ZRSKP
With the development of the Industrial Internet of Things (IIoT), the complex traffic generated by large-scale IIoT devices presents challenges for traffic analysis. Most of existing deep ...learning-based traffic analysis methods use a single flow for classification, resulting in being misled by the irrelevant flow. Thus, it is necessary to use flow sequences for traffic analysis. However, existing models fail to effectively distinguish unimportant flows in flow sequence, which affects the classification performance. To address the above challenges, we propose a novel traffic classifier called Flow Transformer to perform traffic analysis with flow sequences, which leverages multi-head attention mechanism to strengthen the information interaction between related flows. Besides, the RF-based feature selection method is designed to select the optimal feature combination, avoiding insignificant features from reducing the performance of the classifier. Experimental results on three real-world traffic datasets demonstrate that our method outperforms state-of-the-art methods with a large margin.
Digit symbol substitution test (DSST), which is a valid and sensitive tool to assess human cognitive dysfunction, has been widely used in clinical neuropsychology. Although several versions of DSST ...are currently available, most of the existing DSST versions rely on examinees' intact motor function. This limits their utility in severely motor-impaired individuals. A brain-computer interface (BCI) version of DSST was implemented in this study. Steady-state visual evoked potential (SSVEP) was adopted to build the BCI. Nine symbols in the proposed SSVEP BCI-based DSST were designed with clearly different shapes for decreasing measurement errors due to misidentified symbols. To reduce practice effect, furthermore, the digit-symbol pairs of each trial were different. A two-target SSVEP BCI was designed to judge whether the digit-symbol probe in the center of the user interface matched one of the nine digit-symbol pairs above the user interface. All 12 examinees were able to perform the tasks using the proposed SSVEP BCI-based DSST with 96.17 ± 4.18% averaged accuracy, which was comparable with that of computerized DSST. Furthermore, for examinees participating in both offline and online experiment, the accuracies of the online and offline experiments were comparable, supporting that the proposed BCI-DSST was reliable for repeatedly evaluating examinees’ cognitive function over time. These results verified that the proposed SSVEP BCI-based DSST was feasible and effective for healthy subjects.
•A novel SSVEP BCI-based DSST was implemented and was test on 12 healthy people.•Performance of SSVEP BCI-based DSST was comparable with that of computerized DSST.•SSVEP BCI-based DSST was reliable for repeatedly evaluating cognitive function.•SSVEP BCI-based DSST can potentially be used for severely motor-impaired individuals.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
The steady-state visual evoked potential (SSVEP)-based brain-computer interface has received extensive attention in research due to its simple system, less training data, and high information ...transfer rate. There are currently two prominent methods dominating the classification of SSVEP signals. One is the knowledge-based task-related component analysis (TRCA) method, whose core idea is to find the spatial filters by maximizing the inter-trial covariance. The other is the deep learning-based approach, which directly learns a classification model from data. However, how to integrate the two methods to achieve better performance has not been studied before.
In this study, we develop a novel algorithm named TRCA-Net (TRCA-Net) to enhance SSVEP signal classification, which enjoys the advantages of both the knowledge-based method and the deep model. Specifically, the proposed TRCA-Net first performs TRCA to obtain spatial filters, which extract task-related components of data. Then the TRCA-filtered features from different filters are rearranged as new multi-channel signals for a deep convolutional neural network (CNN) for classification. Introducing the TRCA filters to a deep learning-based approach improves the signal-to-noise ratio of input data, hence benefiting the deep learning model.
We evaluate the performance of TRCA-Net using two publicly available large-scale benchmark datasets, and the results demonstrate the effectiveness of TRCA-Net. Additionally, offline and online experiments separately testing ten and five subjects further validate the robustness of TRCA-Net. Further, we conduct ablation studies on different CNN backbones and demonstrate that our approach can be transplanted into other CNN models to boost their performance.
The proposed approach is believed to have a promising potential for SSVEP classification and promote its practical applications in communication and control. The code is available athttps://github.com/Sungden/TRCA-Net.
Key points
Spiritual care is an important component of palliative care.
Timely and comprehensive spiritual care can lead to improved patient care outcomes including pain relief and reduced opioid use ...in palliative care patients.
Local religious and cultural factors need to be considered when providing spiritual care and developing services.
The introduction and integration of current spiritual care education and quality frameworks into current curricula and practice is essential for the development of the field.
A generalist‐specialist approach to spiritual care may improve both efficacy and scalability of services.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
This study designed a brain-computer interface (BCI) with high frequency steady-state visual evoked potentials (SSVEPs) paradigm based on dual frequency modulation. The information transfer rates ...(ITR) of traditional low-frequency SSVEP-BCIs are high, but are very irritating to the human eye for long-term use. High-frequency stimulation can greatly improve the comfort of the system, but the communication rate of high-frequency systems is poor for the EEG response of high-frequency stimulation is weak. This study introduces a dual-frequency modulation method to improve the recognition accuracy of high-frequency BCI. Each target in the paradigm is composed of sinusoidal brightness modulated flicker light of the same initial phase with different stimulation frequencies in a space composition of the checkerboard. Using the above method, a relatively high-frequency SSVEP-BCI paradigm with a relatively complex code is proposed. Due to the complexity of the coding, only the training-based identification algorithm is used. With a data length of 0.5s, the average recognition accuracy is 91.02±7.77%, and ITR is 267.85±39.36bits/min. The performance is higher than the existing high frequency SSVEP-based BCI paradigms.
Inflammatory liver diseases present a significant public health problem. Green tea polyphenols (GTPs) have a myriad of health benefits in animals and humans, including alleviating of hepatic ...inflammation; however, the underlying mechanisms are complicated and remain unclear. The current study investigated the preventive effects and mechanism of GTPs on lipopolysaccharide (LPS)-induced inflammatory liver injury in mice. The ICR mice received intragastric GTPs once per day for 7 consecutive days prior to LPS stimulation (15 mg kg
−1
, intraperitoneally) and liver damage and oxidative stress, pro-inflammatory cytokines, and the hepatic nuclear factor-κB (NF-κB) and Nod-like receptor family, pyrin domain containing 3 (NLRP3) inflammasomes were observed. Our results showed that GTP supplementation significantly reduced LPS-induced plasma alanine aminotransferase (ALT) and aspartate aminotransferase (AST) levels and hepatic malondialdehyde (MDA) levels; and LPS-induced reduction of glutathione (GSH) levels and total superoxide dismutase (T-SOD) activities was drastically improved by GTP pretreatment. GTP supplementation significantly reduced plasma contents and hepatic mRNA levels of interleukin (IL)-1β, IL-18, IL-6, and tumor necrosis factor (TNF)-α, compared with LPS-treated mice which did not receive GTP treatment. In addition, the production of cytokines, such as IL-1β, IL-18, IL-6, and TNF-α in mice livers, and acute-phase response (plasma levels of nitric oxide and C-reactive protein) were also decreased following GTP pre-treatment. Furthermore, GTPs reduced LPS-induced hepatic NF-κB signaling and NLRP3 inflammasome activation. GTPs exert protective effects against inflammatory liver injury by regulating NF-κB signaling and the NLRP3 inflammasome activation. Our findings suggest that dietary GTP supplementation may be an adjunctive prevention and treatment for acute liver injury-associated inflammation.
Inflammatory liver diseases present a significant public health problem.
Abstract
Objective.
Steady-state visual evoked potential (SSVEP)-based brain–computer interfaces (BCIs) have attracted increasing attention due to their high information transfer rate. To improve the ...performance of SSVEP detection, we propose a bidirectional Siamese correlation analysis (bi-SiamCA) model.
Approach
. In this model, an long short-term memory-based Siamese architecture is designed to measure the similarity between the SSVEP signal and the template in each frequency and obtain the probability that the SSVEP signal belongs to each frequency. Additionally, a maximize agreement module with a designed contrastive loss is adopted in the Siamese architecture to increase the similarity between the SSVEP signal and the reference signal in the same frequency. Moreover, a two-way signal processing mechanism is built to effectively integrate complementary information from two temporal directions of the input signals. Our model uses raw SSVEPs as inputs and can be trained end-to-end.
Main results.
Experimental results on a 40-class dataset and a 12-class dataset indicate that bi-SiamCA can significantly improve the classification accuracy compared with the prominent traditional and deep learning methods, especially under short data lengths. Feature visualizations show that the similarity between the SSVEP signal and the reference signal in the same frequency gradually improved in our model.
Conclusion.
The proposed bi-SiamCA model enhances the performance of SSVEP detection and outperforms the compared methods.
Significance.
Due to its high decoding accuracy under short signals, our approach has great potential to implement a high-speed SSVEP-based BCI.
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•A novel assembled approach triggered by UV light was used for copper protection.•The thiol-yne click reaction on copper surface could be catalyzed by 365 nm UV.•The thioether (TTA) ...assembled film was prepared by the click reaction.•Electrochemical data displayed the TTA film had the strongly protective property.
Self-assembling process has been wildly used in the metal protection, and the better approaches to improve the assembled film are always explored. In this paper, a novel click-assembled approach triggered by UV light on copper surface is present. The results show the thiol-yne click reaction between dithiothreitol (DTT) and tert-butyl acetylene (TBA) is triggered on copper surface under the exposure of 365 nm UV light. The newly generated C–S bonds connect the inhibitor molecules on copper surface to form the thioether (TTA) film, the protective efficiency is 96.0%. This assembled approach triggered by light provides a new idea for the metal protection.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
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