Barley GRIK1-SnRK1 kinases subvert a viral virulence protein to upregulate antiviral RNAi and inhibit infection.

Viruses often usurp host machineries for their amplification, but it remains unclear if hosts may subvert virus proteins to regulate viral proliferation. Here, we show that the 17K protein, an important virulence factor conserved in barley yellow dwarf viruses (BYDVs) and related poleroviruses, is phosphorylated by host GRIK1-SnRK1 kinases, with the phosphorylated 17K (P17K) capable of enhancing the abundance of virus-derived small interfering RNAs (vsiRNAs) and thus antiviral RNAi. Furthermore, P17K interacts with barley small RNA-degrading nuclease 1 (HvSDN1) and impedes HvSDN1-catalyzed vsiRNA degradation. Additionally, P17K weakens the HvSDN1-HvAGO1 interaction, thus hindering HvSDN1 from accessing and degrading HvAGO1-carried vsiRNAs. Importantly, transgenic expression of 17K phosphomimetics (17K5D ), or genome editing of SDN1, generates stable resistance to BYDV through elevating vsiRNA abundance. These data validate a novel mechanism that enhances antiviral RNAi through host subversion of a viral virulence protein to inhibit SDN1-catalyzed vsiRNA degradation and suggest new ways for engineering BYDV-resistant crops.

Regulation of cryptochrome-mediated blue light signaling by the ABI4-PIF4 module.

ABSCISIC ACID-INSENSITIVE 4 (ABI4) is a pivotal transcription factor which coordinates multiple aspects of plant growth and development as well as plant responses to environmental stresses. ABI4 has been shown to be involved in regulating seedling photomorphogenesis; however, the underlying mechanism remains elusive. Here, we show that the role of ABI4 in regulating photomorphogenesis is generally regulated by sucrose, but ABI4 promotes hypocotyl elongation of Arabidopsis seedlings under blue (B) light under all tested sucrose concentrations. We further show that ABI4 physically interacts with PHYTOCHROME INTERACTING FACTOR 4 (PIF4), a well-characterized growth-promoting transcription factor, and post-translationally promotes PIF4 protein accumulation under B light. Further analyses indicate that ABI4 directly interacts with the B light photoreceptors cryptochromes (CRYs) and inhibits the interactions between CRYs and PIF4, thus relieving CRY-mediated repression of PIF4 protein accumulation. In addition, while ABI4 could directly activate its own expression, CRYs enhance, whereas PIF4 inhibits, ABI4-mediated activation of the ABI4 promoter. Together, our study demonstrates that the ABI4-PIF4 module plays an important role in mediating CRY-induced B light signaling in Arabidopsis.

CC Chemokine 2 Promotes Ovarian Cancer Progression through the MEK/ERK/MAP3K19 Signaling Pathway.

Ovarian cancer is a gynecological tumor with an incidence rate lower than those of other gynecological tumor types and the second-highest death rate. CC chemokine 2 (CCL2) is a multifunctional factor associated with the progression of numerous cancers. However, the effect of CCL2 on ovarian cancer progression is unclear. Here, we found that exogenous CCL2 and the overexpression of CCL2 promoted the proliferation and metastasis of ovarian cancer cells. On the other hand, CCL2 knockdown via CRISPR/Cas9 inhibited ovarian cancer cell proliferation, migration, and invasion. The present study demonstrated that mitogen-activated protein three kinase 19 (MAP3K19) was the key CCL2 target for regulating ovarian cancer progression through transcriptome sequencing. Additionally, MAP3K19 knockout inhibited ovarian cancer cell proliferation, migration, and invasion. Furthermore, CCL2 increased MAP3K19 expression by activating the mitogen-activated protein kinase kinase (MEK)/extracellular signal-regulated kinase (ERK) pathway. The present study showed the correlation between CCL2 and ovarian cancer, suggesting that CCL2 may be a novel target for ovarian cancer therapy.

Role of CC-chemokine ligand 2 in gynecological cancer.

Gynecological cancer is one of the most severe diseases that threaten the lives and health of women worldwide. Its incidence rate increases with each passing year and becomes more prevalent among young people. The prognosis of gynecological cancer remains poor despite significant advances in surgical removal and systemic chemotherapy. Several chemokines play a role in the progression of gynecologic cancers. CCL2 (CC-chemokine ligand 2), also termed MCP-1 (monocyte chemotactic protein 1), plays a significant physiological role in monocyte cell migration and the inflammatory response. Recent studies have demonstrated that CCL2 plays a pro-tumorigenic function in the tumor microenvironment. According to previous studies, CCL2 plays a significant role in the occurrence and development of gynecological cancers. Furthermore, recent studies noted that CCL2 could be a potential diagnostic biomarker and prognostic predictor. The purpose of this paper is to review the role of CCL2 in the occurrence and development of gynecological cancers and to discuss the potential therapeutic strategy of CCL2 for gynecological cancers, with a primary focus on breast cancer, ovarian cancer, cervical cancer, and endometrial cancer.

First Report of Root Rot of Tobacco Caused by Fusarium brachygibbosum in China.

Tobacco (Nicotiana tabacum L.) is an important cash crop in China, with an estimated production of 2.2 million tons every year (Berbec and Matyka, 2020). In June 2020, a root rot disease was observed on tobacco (cv. Zhongyan 100) in four surveyed counties (Mianchi, Lushi, Duguan and Lingbao) in Sanmenxia. Diseased plants exhibited leaf chlorosis and purplish to brown vascular discoloration of stem, taproot and lateral roots. The disease incidence ranged from 15% to 40% in 11 surveyed fields, 36.7 ha in total. Twenty five diseased tissues were surface sterilized in 75% ethanol and placed on potato dextrose agar (PDA) medium. Fifteen single-spore isolates were obtained from 25 diseased tissue samples. All cultures growing on PDA had white colonies with abundant aerial mycelia initially, turning into yellow to orange in the center and produced red pigmentation after seven days of growth. The 7-day-old cultures grown on carnation leaf agar (CLA) produced macroconidia that were curved with 3-5 septa, had wide central cells, slightly pointy apex, and measured 17.0-45.9 µm long×3.0-4.6 µm wide (n=50). The microconidia formed on CLA were slightly curved, ovoid with zero to two septa, measuring 5.4-15.5 µm long×2.0-3.2 µm wide (n=50). Spherical chlamydospores (7.58-13.52 µm; n=50) were terminal or intercalary, single or in chains. Such characteristics were typical of Fuarium brachygibbosum (Tirado-Ramírez et al. 2018). DNA from one representative single-spore isolate (MC1) was extracted, and the translation elongation factor 1-alpha (EF1-α), RNA polymerase I largest subunit (RPB1) and second largest subunit (RPB2) genes were amplified with primers EF1/EF2, F5/G2R and RPB2F/R respectively (O'Donnell et al. 1998, 2010), and sequenced. Sequences were submitted to GenBank under accession numbers MT947796 (EF1-α), MW679536 (RPB1) and MW430664 (RPB2). The consensus sequences showed 99.70%, 99.94% and 100% identity to the sequences of F. brachygibbosum strain NRRL 34033 (accession no. GQ505418.1, HM347172.1 and GQ505482.1, Wang et al 2021). Morphological and molecular results confirmed this species as F. brachygibbosum (Al-Mahmooli, et al., 2013, Rentería -Martínez, et al., 2018). Pathogenicity tests were performed on tobacco seedlings grown on autoclaved tobacco specific substrate (Tobacco specific matrix, Ainong Biotechnology Co. Ltd, China). Healthy six-leaf stage tobacco seedlings (n=30; Zhongyan 100) were inoculated by placing 7-days old wheat seed (15 seeds per plant) infested with MC1 around the root. Thirty seedlings inoculated with sterile wheat seeds served as controls. All the plants were maintained in a growth chamber at 25±0.5℃ and 70% relative humidity. The assay was conducted three times. Typical symptoms of foliage chlorosis and root browning were observed 7-14 days after inoculation. The pathogen was reisolated from the necrotic tissue from all inoculated seedlings and was identified by sequencing partial EF1-α and RPB2 genes. Control plants remained asymptomatic and no pathogen was recovered from the control plants. Fusarium brachygibbosum is known as a pathogen of grains and cash crops in China (Shan, et al., 2017, Xia, et al., 2018). To our knowledge, this is the first report of F. brachygibbosum causing root rot on tobacco. We believe that our results will help to better understand rhizome fungal diseases affecting tobacco production in China. Acknowledgements: Funding was provided by the Science and Technology Project of Henan Provincial Tobacco Company (2020410000270012), Independent Innovation Project of Hennan Academy of Agricultural Sciences (2020ZC18) and Research and Development project of Henan Academy of Agricultural Sciences (2020CY010). References: Al-Mahmooli, I. H., et al. 2013. Plant Dis. 97:687; https://doi.org/10.1094/PDIS-09-12-0828-PDN Berbec A. K. and Matyka M. 2020. Agric. 10(11), 551; https://doi.org/10.3390/agriculture10110551 O'Donnell, K., et al. 1998. P. Natl. Acad. Sci. USA. 95(5):2044-2049; https://doi.org/10.1073/pnas.95.5.2044 O'Donnell, K., et al. 2010. J. Clin. Microbiol. 48(10)3708-3718; https://doi.org/10.1128/JCM.00989-10 Rentería -Martínez M.E., et al. 2018. Mex. J. of Phytopathol. 36(2):1-23; https://doi.org/10.18781/R.MEX.FIT.1710-1 Shan, L. Y., et al. 2017. Plant Dis. 101:837; https://doi.org/10.1094/PDIS-10-16-1465-PDN Tirado-Ramírez, M. A., et al. 2018. Plant Dis. 103; https://doi.org/10.1094/PDIS-04-18-0710-PDN Wang, S., et al. 2021. Plant Dis. 2021 Jan 6. doi: 10.1094/PDIS-05-20-0941-PDN. Epub ahead of print. PMID: 33406862. Xia, B., et al. 2018. Plant Dis. 102(11):2372; https://doi.org/10.1094/PDIS-12-17-1939-PDN The author(s) declare no conflict of interest.

Phospholipase D-derived phosphatidic acid promotes root hair development under phosphorus deficiency by suppressing vacuolar degradation of PIN-FORMED2.

Root hair development is crucial for phosphate absorption, but how phosphorus deficiency affects root hair initiation and elongation remains unclear. We demonstrated the roles of auxin efflux carrier PIN-FORMED2 (PIN2) and phospholipase D (PLD)-derived phosphatidic acid (PA), a key signaling molecule, in promoting root hair development in Arabidopsis thaliana under a low phosphate (LP) condition. Root hair elongation under LP conditions was greatly suppressed in pin2 mutant or under treatment with a PLDζ2-specific inhibitor, revealing that PIN2 and polar auxin transport and PLDζ2-PA are crucial in LP responses. PIN2 was accumulated and degraded in the vacuole under a normal phosphate (NP) condition, whereas its vacuolar accumulation was suppressed under the LP or NP plus PA conditions. Vacuolar accumulation of PIN2 was increased in pldζ2 mutants under LP conditions. Increased or decreased PIN2 vacuolar accumulation is not observed in sorting nexin1 (snx1) mutant, indicating that vacuolar accumulation of PIN2 is mediated by SNX1 and the relevant trafficking process. PA binds to SNX1 and promotes its accumulation at the plasma membrane, especially under LP conditions, and hence promotes root hair development by suppressing the vacuolar degradation of PIN2. We uncovered a link between PLD-derived PA and SNX1-dependent vacuolar degradation of PIN2 in regulating root hair development under phosphorus deficiency.

[Characteristics of vocalization in children with autism spectrum disorder during the still-face paradigm].

OBJECTIVE: To study the characteristics of vocalization during the still-face paradigm (SFP) before the age of 2 years and their correlation with the severity of autism spectrum disorder (ASD) symptoms at diagnosis in children with ASD. METHODS: A total of 43 children aged 7-23 months, who were suspected of ASD, were enrolled as the suspected ASD group, and 37 typical development (TD) children, aged 7-23 months, were enrolled as the TD group. The frequency and durations of vocalization in the SFP were measured. The children in the suspected ASD group were followed up to the age of 2 years, and 34 children were diagnosed with ASD. Autism Diagnostic Observation Schedule (ADOS) was used to assess the severity of symptoms. The correlation of the characteristics of vocalization before the age of 2 years with the severity of ASD symptoms was analyzed. RESULTS: Compared with the TD group, the ASD group had significant reductions in the frequency and durations of meaningful vocalization and vocalization towards people and a significant increase in the duration of vocalization toward objects (P<0.05). The Spearman correlation analysis showed that in the ASD group, the frequency and durations of total vocalization, non-speech vocalization, babbling, vocalization towards people, and vocalization towards objects were negatively correlated with the score of communication in ADOS (P<0.05). The frequency and durations of total vocalization, babbling, and vocalization towards people and the duration of vocalization towards objects were negatively correlated with the score of reciprocal social interaction in ADOS (P<0.05). The frequency of total vocalization, the duration of babbling, and the frequency and duration of vocalization towards people were negatively correlated with the score of play in ADOS (P<0.05). The frequency of total vocalization and non-speech vocalization and the frequency and durations of vocalization towards people were negatively correlated with the score of stereotyped behaviors and restricted interests in ADOS (P<0.05). The multiple linear regression analysis showed that the frequency of total vocalization was a negative predictive factor for the score of communication in ADOS (P<0.001), and the duration of vocalization towards people was a negative predictive factor for the score of reciprocal social interaction in ADOS (P<0.05). CONCLUSIONS: SFP can better highlight the abnormal vocalization of ASD children before the age of 2 years, and such abnormalities can predict the severity of ASD symptoms early.

Upgrade of wood sugar d-xylose to a value-added nutraceutical by in vitro metabolic engineering.

The upgrade of D-xylose, the most abundant pentose, to value-added biochemicals is economically important to next-generation biorefineries. myo-Inositol, as vitamin B8, has a six-carbon carbon-carbon ring. Here we designed an in vitro artificial NAD(P)-free 12-enzyme pathway that can effectively convert the five-carbon xylose to inositol involving xylose phosphorylation, carbon-carbon (C-C) rearrangement, C-C bond circulation, and dephosphorylation. The reaction conditions catalyzed by all thermostable enzymes from hyperthermophilic microorganisms Thermus thermophiles, Thermotoga maritima, and Archaeoglobus fulgidus were optimized in reaction temperature, buffer type and concentration, enzyme composition, Mg2+ concentration, and fed-batch addition of ATP. The 11-enzyme cocktail, whereas a fructose 1,6-bisphosphatase from T. maritima has another function of inositol monophosphatase, converted 20 mM xylose to 16.1 mM inositol with a conversion efficiency of 96.6% at 70 °C. Polyphosphate was found to replace ATP for xylulose phosphorylation due to broad substrate promiscuity of the T. maritima xylulokinase. The Tris-HCl buffer effectively mitigated the Maillard reaction at 70 °C or higher temperature. The co-production of value-added biochemicals, such as inositol, from wood sugar could greatly improve economics of new biorefineries, similar to oil refineries that make value-added plastic precursors to subsidize gasoline/diesel production.

Latent Infection of Powdery Mildew on Volunteer Wheat in Sichuan Province, China.

Wheat powdery mildew, caused by the fungal pathogen Blumeria graminis f. sp. tritici, is one of the most destructive wheat diseases in China, especially in Sichuan Province. Successfully oversummered B. graminis f. sp. tritici can become a primary infection source for wheat seedlings in the fall. Determining the latent infection level of B. graminis f. sp. tritici in volunteer wheat and the oversummering areas of B. graminis f. sp. tritici is important for estimating potential B. graminis f. sp. tritici epidemics. In this study, we clarified the critical role of volunteer wheat in the B. graminis f. sp. tritici oversummering cycle and determined whether latent B. graminis f. sp. tritici infection was present in volunteer wheat by using real-time polymerase chain reaction (real-time PCR). The results indicated that volunteer wheat was mostly found in the northeast and middle regions of Sichuan, where lower temperatures and higher precipitation are common. A total of 13.2% of samples showed symptoms of B. graminis f. sp. tritici (spores) in the field, and 36.8% of samples were found to carry the B. graminis f. sp. tritici pathogen, even though no symptoms were observed. Volunteer wheat with B. graminis f. sp. tritici infection symptoms was found at an altitude of 536 m but volunteer wheat latently infected by B. graminis f. sp. tritici was identified at the lowest altitude of 323 m. Crop shade (e.g., corn and lima bean) provided suitable conditions for the survival of volunteer wheat in the summer. In addition, volunteer wheat played a key role in the B. graminis f. sp. tritici oversummering cycle. Moreover, B. graminis f. sp. tritici could oversummer by infecting generations of volunteer wheat in the summer, thereby becoming the primary infection source for autumn-sown wheat. The results showed that the latent infection of wheat diseases could be rapidly quantified by real-time PCR. Here, the primary disease center of autumn-sown wheat in Ya'an and Wenjiang were detected accurately based on this method. This study provides solid evidence for identifying the disease center, which offers guidance for wheat disease control and management.

Spatiotemporal Phase Synchronization in Adaptive Reconfiguration from Action Observation Network to Mentalizing Network for Understanding Other's Action Intention.

In action intention understanding, the mirror system is involved in perception-action matching process and the mentalizing system underlies higher-level intention inference. By analyzing the dynamic functional connectivity in α (8-12 Hz) and ß (12-30 Hz) frequency bands over a "hand-cup interaction" observation task, this study investigates the topological transition from the action observation network (AON) to the mentalizing network (MZN), and estimates their functional relevance for intention identification from other's different action kinematics. Sequential brain microstates were extracted based on event-related potentials (ERPs), in which significantly differing neuronal responses were found in N170-P200 related to perceptually matching kinematic profiles and P400-700 involved in goal inference. Inter-electrode weighted phase lag index analysis on the ERP microstates revealed a shift of hub centrality salient in α frequency band, from the AON dominated by left-lateral frontal-premotor-temporal and temporal-parietooccipital synchronizations to the MZN consisting of more bilateral frontal-parietal and temporal-parietal synchronizations. As compared with usual actions, intention identification of unintelligible actions induces weaker synchronizations in the AON but dramatically increased connectivity in right frontal-temporal-parietal regions of the MZN, indicating a spatiotemporally complementary effect between the functional network configurations involved in mirror and mentalizing processes. Perceptual processing in observing usual/unintelligible actions decreases/increases requirements for intention inference, which would induce less/greater functional network reorganization on the way to mentalization. From the comparison, our study suggests that the adaptive topological changes from the AON to the MZN indicate implicit causal association between the mirror and mentalizing systems for decoding others' intentionality.

A Review of the Antiviral Role of Green Tea Catechins.

Over the centuries, infectious diseases caused by viruses have seriously threatened human health globally. Viruses are responsible not only for acute infections but also many chronic infectious diseases. To prevent diseases caused by viruses, the discovery of effective antiviral drugs, in addition to vaccine development, is important. Green tea catechins (GTCs) are polyphenolic compounds from the leaves of Camelliasinensis. In recent decades, GTCs have been reported to provide various health benefits against numerous diseases. Studies have shown that GTCs, especially epigallocatechin-3-gallate (EGCG), have antiviral effects against diverse viruses. The aim of this review is to summarize the developments regarding the antiviral activities of GTCs, to discuss the mechanisms underlying these effects and to offer suggestions for future research directions and perspectives on the antiviral effects of EGCG.

Novel Sinusoidal Signal Assisted Multivariate Variational Mode Decomposition Combined With Task-Related Component Analysis for Enhancing SSVEP-Based BCI Performance.

Brain-computer interfaces (BCIs) based on steady-state visually evoked potential (SSVEP) have a broad application prospect owing to their multiple command output and high performance. Each harmonic component of SSVEP individually contains unique features, which can be utilized to enhance the recognition performance of SSVEP-based BCIs. However, the existing subband analysis methods for SSVEP, including those based on filter banks and existing mode decomposition methods, have limitations in extracting and utilizing independent harmonic components. This study proposes a sinusoidal signal assisted multivariate variational mode decomposition (SA-MVMD) algorithm that allows the constraint of the center frequencies and narrowband filtering structures of the intrinsic mode functions (IMFs) based on the prior frequency knowledge of the signal. It preserves the target information of the signal during decomposition while avoiding mode mixing and incorrect decomposition, thereby enabling the effective extraction of each independent harmonic component of SSVEP. Building on this, a SA-MVMD based task-related component analysis (SA-MVMD-TRCA) method is further proposed to fully utilize the features within the overall SSVEP as well as its independent harmonics, thereby enhancing the recognition performance. Testing on the public SSVEP Benchmark dataset demonstrates that the proposed method significantly outperforms the filter bank-based control methods. This study confirms the effectiveness of SA-MVMD and the potential of this approach, which analyzes and utilizes each independent harmonic of SSVEP, providing new strategies and perspectives for performance enhancement in SSVEP-based BCIs.

Wasserstein Discriminant Dictionary Learning for Graph Representation.

Mining discriminative graph topological information plays an important role in promoting graph representation ability. However, it suffers from two main issues: (1) the difficulty/complexity of computing global inter-class/intra-class scatters, commonly related to mean and covariance of graph samples, for discriminant learning; (2) the huge complexity and variety of graph topological structure that is rather challenging to robustly characterize. In this paper, we propose the Wasserstein Discriminant Dictionary Learning (WDDL) framework to achieve discriminant learning on graphs with robust graph topology modeling, and hence facilitate graph-based pattern analysis tasks. Considering the difficulty of calculating global inter-class/intra-class scatters, a reference set of graphs (aka graph dictionary) is first constructed by generating representative graph samples (aka graph keys) with expressive topological structure. Then, a Wasserstein Graph Representation (WGR) process is proposed to project input graphs into a succinct dictionary space through the graph dictionary lookup. To further achieve discriminant graph learning, a Wasserstein discriminant loss (WD-loss) is defined on the graph dictionary, in which the graph keys are optimizable, to make the intra-class keys more compact and inter-class keys more dispersed. Hence, the calculation of global Wasserstein metric (W-metric) centers can be bypassed. For sophisticated topology mining in the WGR process, a joint-Wasserstein graph embedding module is constructed to model both between-node and between-edge relationships across inputs and graph keys by encapsulating both the Wasserstein metric (between cross-graph nodes) and proposed novel Kron-Gromov-Wasserstein (KGW) metric (between cross-graph adjacencies). Specifically, the KGW-metric comprehensively characterizes the cross-graph connection patterns with the Kronecker operation, then adaptively captures those salient patterns through connection pooling. To evaluate the proposed framework, we study two graph-based pattern analysis problems, i.e. graph classification and cross-modal retrieval, with the graph dictionary flexibly adjusted to cater to these two tasks. Extensive experiments are conducted to comprehensively compare with existing advanced methods, as well as dissect the critical component of our proposed architecture. The experimental results validate the effectiveness of the WDDL framework.

Convolutional Transformer-based Cross Subject Model for SSVEP-based BCI Classification.

Steady-state visual evoked potential (SSVEP) is a commonly used brain-computer interface (BCI) paradigm. The performance of cross-subject SSVEP classification has a strong impact on SSVEP-BCI. This study designed a cross subject generalization SSVEP classification model based on an improved transformer structure that uses domain generalization (DG). The global receptive field of multi-head self-attention is used to learn the global generalized SSVEP temporal information across subjects. This is combined with a parallel local convolution module, designed to avoid oversmoothing the oscillation characteristics of temporal SSVEP data and better fit the feature. Moreover, to improve the cross-subject calibration-free SSVEP classification performance, an DG method named StableNet is combined with the proposed convolutional transformer structure to form the DG-Conformer method, which can eliminate spurious correlations between SSVEP discriminative information and background noise to improve cross-subject generalization. Experiments on two public datasets, Benchmark and BETA, demonstrated the outstanding performance of the proposed DG-Conformer compared with other calibration-free methods, FBCCA, tt-CCA, Compact-CNN, FB-tCNN, and SSVEPNet. Additionally, DG-Conformer outperforms the classic calibration-required algorithms eCCA, eTRCA and eSSCOR when calibration is used. An incomplete partial stimulus calibration scheme was also explored on the Benchmark dataset, and it was demonstrated to be a potential solution for further high-performance personalized SSVEP-BCI with quick calibration.

Multi-scale 3D-CRU for EEG emotion recognition.

In this paper, we propose a novel multi-scale 3D-CRU model, with the goal of extracting more discriminative emotion feature from EEG signals. By concurrently exploiting the relative electrode locations and different frequency subbands of EEG signals, a three-dimensional feature representation is reconstructed wherein the Delta (δ) frequency pattern is included. We employ a multi-scale approach, termed 3D-CRU, to concurrently extract frequency and spatial features at varying levels of granularity within each time segment. In the proposed 3D-CRU, we introduce a multi-scale 3D Convolutional Neural Network (3D-CNN) to effectively capture discriminative information embedded within the 3D feature representation. To model the temporal dynamics across consecutive time segments, we incorporate a Gated Recurrent Unit (GRU) module to extract temporal representations from the time series of combined frequency-spatial features. Ultimately, the 3D-CRU model yields a global feature representation, encompassing comprehensive information across time, frequency, and spatial domains. Numerous experimental assessments conducted on publicly available DEAP and SEED databases provide empirical evidence supporting the enhanced performance of our proposed model in the domain of emotion recognition. These findings underscore the efficacy of the features extracted by the proposed multi-scale 3D-GRU model, particularly with the incorporation of the Delta (δ) frequency pattern. Specifically, on the DEAP dataset, the accuracy of Valence and Arousal are 93.12% and 94.31%, respectively, while on the SEED dataset, the accuracy is 92.25%.

Phosphate deficiency responsive TaSPX3 is involved in the regulation of shoot phosphorus in Arabidopsis plants.

SPX (SYG/PHO81/XPR1) domain genes have been reported to play vital roles in the Phosphorus (Pi) signaling network in Arabidopsis thaliana and rice. However, the functions of SPX proteins in wheat remain largely unknown. In this study, the full-length cDNA sequence of the TaSPX3 gene was cloned from the common wheat variety Zhengmai9023. The expression of TaSPX3 was up-regulated in eight different genotypes of wheat under low phosphorus (LP) stress, indicating that TaSPX3 responds to Pi limitation in multiple wheat genotypes. The transcription level of TaSPX3 was also detected in the absence of seven different elements, showing certain specificity for Pi deficiency in wheat. Over expressing TaSPX3 in Arabidopsis can alleviate Pi deficiency symptoms at the seedling stage and promote the growth of plant, and advance the flowering period at the adult stage. The expression of 7 genes associated with the Pi starvation signal pathways was analyzed using qRT-PCR. The results showed that TaSPX3, along with AtSPX1, AtRNS1, AtIPS1, AtPAP2, AtPAP17 and AtAT4, were all induced by Pi deficiency. This study reveals that the TaSPX3 gene in wheat is involved in the response to phosphorus stress and may affect shoot phosphorus levels through AT4 or PAPs-related pathways. Overall, our study provides new insights into the regulation of plant response under LP conditions and the molecular mechanism underlying the role of the wheat SPX gene in coping with LP stress.

Cross Domain Correlation Maximization for Enhancing the Target Recognition of SSVEP-Based Brain-Computer Interfaces.

The target recognition performance of steady-state visual evoked potential (SSVEP)-based brain-computer interfaces can be significantly improved with a training-based approach. However, the training procedure is time consuming and often causes fatigue. Consequently, the number of training data should be limited, which may reduce the classification performance. Thus, how to improve classification accuracy without increasing the training time is crucial to SSVEP-based BCI system. This study proposes a transfer-related component analysis (TransRCA) method for addressing the above issue. In this method, the SSVEP-related components are extracted from a small number of training data of the current individual and combined with those extracted from a large number of existing training data of other individuals. The TransRCA method maximizes not only the inter-trial covariances between the source and target subjects, but also the correlation between the reference signals and SSVEP signals from the source and target subjects. The proposed method was validated on the SSVEP public Benchmark and BETA datasets, and the classification accuracy and information transmission rate of the ensemble version of the proposed TransRCA method were compared with those of the state-of-the-art eCCA, eTRCA, ttCCA, LSTeTRCA, and eIISMC methods on both datasets. The comparison results indicate that the proposed method provides a superior performance compared with these state-of-the-art methods, and thus has high potential for the development of a SSVEP-based brain-computer interface system with high classification performance that only uses a small number of training data.

Effective Connectivity Analysis and Classification of Action Observation From Different Perspectives: An fMRI Study.

OBJECTIVE: Analyzing the effective connectivity characteristics of brain networks in the process of action observation is helpful for understanding the neurodynamic mechanisms during action observation. METHOD: In this study, functional magnetic resonance imaging (fMRI) images were obtained from 20 participants who performed hand-object interaction observation tasks from the first-person perspective (1PP) and third-person perspective (3PP). On the basis of a meta-analysis, 11 key brain regions were extracted as nodes to build an action observation network. The weighted and directional connections between all of the nodes were investigated using partial directional coherence (PDC) analysis in five narrow frequency bands. RESULTS: The statistical analysis indicated that the ultra-low frequency band ( ≤ 0.04 Hz) exhibited significant activation compared with other frequency bands for both 1PP and 3PP. In addition, it was found that 3PP induced significantly stronger brain activation than 1PP in the ultra-low frequency band. Moreover, this study attempted to classify fMRI data corresponding to different perspectives using brain network features. A comparative analysis revealed that the weighted and binary PDC matrix methods achieved classification accuracies of 86.3% and 80.8%, respectively. SIGNIFICANCE: The weighted PDC analysis exhibits a more comprehensive understanding of neural mechanisms during action observation in different visual perspectives. It also has potential applications value in human-computer interaction in the future.

EEG-based major depressive disorder recognition by selecting discriminative features via stochastic search.

Objective. Major depressive disorder (MDD) is a prevalent psychiatric disorder whose diagnosis relies on experienced psychiatrists, resulting in a low diagnosis rate. As a typical physiological signal, electroencephalography (EEG) has indicated a strong association with human beings' mental activities and can be served as an objective biomarker for diagnosing MDD.Approach. The basic idea of the proposed method fully considers all the channel information in EEG-based MDD recognition and designs a stochastic search algorithm to select the best discriminative features for describing the individual channels.Main results. To evaluate the proposed method, we conducted extensive experiments on the MODMA dataset (including dot-probe tasks and resting state), a 128-electrode public EEG-based MDD dataset including 24 patients with depressive disorder and 29 healthy controls. Under the leave-one-subject-out cross-validation protocol, the proposed method achieved an average accuracy of 99.53% in the fear-neutral face pairs cued experiment and 99.32% in the resting state, outperforming state-of-the-art MDD recognition methods. Moreover, our experimental results also indicated that negative emotional stimuli could induce depressive states, and high-frequency EEG features contributed significantly to distinguishing between normal and depressive patients, which can be served as a marker for MDD recognition.Significance. The proposed method provided a possible solution to an intelligent diagnosis of MDD and can be used to develop a computer-aided diagnostic tool to aid clinicians in early diagnosis for clinical purposes.

Gapless Genome Assembly of Puccinia triticina Provides Insights into Chromosome Evolution in Pucciniales.

Chromosome evolution drives species evolution, speciation, and adaptive radiation. Accurate genome assembly is crucial to understanding chromosome evolution of species, such as dikaryotic fungi. Rust fungi (Pucciniales) in dikaryons represent the largest group of plant pathogens, but the evolutionary process of adaptive radiation in Pucciniales remains poorly understood. Here, we report a gapless genome for the wheat leaf rust fungus Puccinia triticina determined using PacBio high-fidelity (HiFi) sequencing. This gapless assembly contains two sets of chromosomes, showing that one contig represents one chromosome. Comparisons of homologous chromosomes between the phased haplotypes revealed that highly frequent small-scale sequence divergence shapes haplotypic variation. Genome analyses of Puccinia triticina along with other rusts revealed that recent transposable element bursts and extensive segmental gene duplications synergistically highlight the evolution of chromosome structures. Comparative analysis of chromosomes indicated that frequent chromosomal rearrangements may act as a major contributor to rapid radiation of Pucciniales. This study presents the first gapless, phased assembly for a dikaryotic rust fungus and provides insights into adaptive evolution and species radiation in Pucciniales. IMPORTANCE Rust fungi (Pucciniales) are the largest group of plant pathogens. Adaptive radiation is a predominant feature in Pucciniales evolution. Chromosome evolution plays an important role in adaptive evolution. Accurate chromosome-scale assembly is required to understand the role of chromosome evolution in Pucciniales. We took advantage of HiFi sequencing to construct a gapless, phased genome for Puccinia triticina. Further analyses revealed that the evolution of chromosome structures in rust lineage is shaped by the combination of transposable element bursts and segmental gene duplications. Chromosome comparisons of Puccinia triticina and other rusts suggested that frequent chromosomal arrangements may make remarkable contributions to high species diversity of rust fungi. Our results present the first gapless genome for Pucciniales and shed light on the feature of chromosome evolution in Pucciniales.