Fractional-order state space reconstruction: a new frontier in multivariate complex time series.

This paper presents a novel approach to the phase space reconstruction technique, fractional-order phase space reconstruction (FOSS), which generalizes the traditional integer-order derivative-based method. By leveraging fractional derivatives, FOSS offers a novel perspective for understanding complex time series, revealing unique properties not captured by conventional methods. We further develop the multi-span transition entropy component method (MTECM-FOSS), an advanced complexity measurement technique that builds upon FOSS. MTECM-FOSS decomposes complexity into intra-sample and inter-sample components, providing a more comprehensive understanding of the dynamics in multivariate data. In simulated data, we observe that lower fractional orders can effectively filter out random noise. Time series with diverse long- and short-term memory patterns exhibit distinct extremities at different fractional orders. In practical applications, MTECM-FOSS exhibits competitive or superior classification performance compared to state-of-the-art algorithms when using fewer features, indicating its potential for engineering tasks.

Type I arginine methyltransferases play crucial roles in development and pathogenesis of Phytophthora capsici.

Phytophthora capsici, a pathogenic oomycete, poses a serious threat to global vegetable production. This study investigated the role of protein arginine methylation, a notable post-translational modification, in the epigenetic regulation of P. capsici. We identified and characterized five protein arginine methyltransferases (PRMTs) in P. capsici, with a focus on four putative type I PRMTs exhibiting similar functional domain. Deletion of PcPRMT3, a homolog of PRMT3, significantly affected mycelial growth, asexual spore development, pathogenicity, and stress responses in P. capsici. Transcriptome analyses indicated that absence of PcPRMT3 disrupted multiple biological pathways. The PcPRMT3 deletion mutant displayed heightened susceptibility to oxidative stress, correlated with the downregulation of genes involved in peroxidase and peroxisome activities. Additionally, PcPRMT3 acted as a negative regulator, modulating the transcription levels of specific elicitins, which in turn affects the defense response of host plant against P. capsici. Furthermore, PcPRMT3 was found to affect global arginine methylation levels in P. capsici, implying potential alterations in the functions of its substrate proteins.

Intelligent ankle-foot prosthesis based on human structure and motion bionics.

The ankle-foot prosthesis aims to compensate for the missing motor functions by fitting the motion characteristics of the human ankle, which contributes to enabling the lower-limb amputees to take care of themselves and improve mobility in daily life. To address the problems of poor bionic motion of the ankle-foot prosthesis and the lack of natural interaction among the patient, prosthesis, and the environment, we developed a complex reverse-rolling conjugate joint based on the human ankle-foot structure and motion characteristics, the rolling joint was used to simulate the rolling-sliding characteristics of the knee joint. Meanwhile, we established a segmental dynamics model of the prosthesis in the stance phase, and the prosthetic structure parameters were obtained with the optimal prosthetic structure dimensions and driving force. In addition, a carbon fiber energy-storage foot was designed based on the human foot profile, and the dynamic response of its elastic strain energy at different thicknesses was simulated and analyzed. Finally, we integrated a bionic ankle-foot prosthesis and experiments were conducted to verify the bionic nature of the prosthetic joint motion and the energy-storage characteristics of the carbon fiber prosthetic foot. The proposed ankle-foot prosthesis provides ambulation support to assist amputees in returning to social life normally and has the potential to help improve clinical viability to reduce medical rehabilitation costs.

AlphaFold-guided redesign of a plant pectin methylesterase inhibitor for broad-spectrum disease resistance.

Plant cell walls are a critical site where plants and pathogens continuously struggle for physiological dominance. Here we show that dynamic remodeling of pectin methylesterification of plant cell walls is a component of the physiological and co-evolutionary struggles between hosts and pathogens. A pectin methylesterase (PsPME1) secreted by Phytophthora sojae decreases the degree of pectin methylesterification, thus synergizing with an endo-polygalacturonase (PsPG1) to weaken plant cell walls. To counter PsPME1-mediated susceptibility, a plant-derived pectin methylesterase inhibitor protein, GmPMI1, protects pectin to maintain a high methylesterification status. GmPMI1 protects plant cell walls from enzymatic degradation by inhibiting both soybean and P. sojae pectin methylesterases during infection. However, constitutive expression of GmPMI1 disrupted the trade-off between host growth and defense responses. We therefore used AlphaFold structure tools to design a modified form of GmPMI1 (GmPMI1R) that specifically targets and inhibits pectin methylesterases secreted from pathogens but not from plants. Transient expression of GmPMI1R enhanced plant resistance to oomycete and fungal pathogens. In summary, our work highlights the biochemical modification of the cell wall as an important focal point in the physiological and co-evolutionary conflict between hosts and microbes, providing an important proof of concept that AI-driven structure-based tools can accelerate the development of new strategies for plant protection.

Distributed Vibration Monitoring System for 10 kV-400 kVA 3D Wound Core Transformer under Progressive Short-Circuit Impulses.

As large-scale, high-proportion, and efficient distribution transformers surge into the grids, anti-short circuit capability testing of transformer windings in efficient distribution seems necessary and prominent. To deeply explore the influence of progressively short-circuit shock impulses on the core winding deformation of efficient power transformers, a finite element theoretical model was built by referring to a three-phase three-winding 3D wound core transformer with a model of S20-MRL-400/10-NX2. The distributions of internal equivalent force and total deformation of the 3D wound core transformer along different paths under progressively short-circuit shock impulses varying from 60% to 120% were investigated. Results show that the equivalent stress and total deformation change rate reach their maximum as the short-circuit current increases from 60% to 80%, and the maximum and average variation rate for the equivalent stress reach 177.75% and 177.43%, while the maximum and average variation rate for the total deformation corresponds to 178.30% and 177.45%, respectively. Meanwhile, the maximum equivalent stress and maximum total deformation reach 29.81 MPa and 38.70 µm, respectively, as the applied short-circuit current increased to 120%. In light of the above observations, the optimization and deployment of wireless sensor nodes was suggested. Therefore, a distributed monitoring system was developed for acquiring the vibration status of the windings in a 3D wound core transformer, which is a beneficial supplement to the traditional short-circuit reactance detection methods for an efficient grid access spot-check of distribution transformers.

Distinct small RNAs are expressed at different stages of Phytophthora capsici and play important roles in development and pathogenesis.

Small RNAs (sRNAs) are important non-coding RNA regulators that play key roles in the development and pathogenesis of plant pathogens, as well as in other biological processes. However, whether these abundant and varying sRNAs are involved in Phytophthora development or infection remains enigmatic. In this study, sRNA sequencing of 4 asexual stages of Phytophthora capsici (P. capsici), namely, as mycelia (HY), sporangia (SP), zoospores (ZO), cysts (CY), and pepper infected with P. capsici (IN), were performed, followed by sRNA analysis, microRNA (miRNA) identification, and miRNA target prediction. sRNAs were mainly distributed at 25-26 nt in HY, SP, and ZO but distributed at 18-34 nt in CY and IN. 92, 42, 176, 39, and 148 known miRNAs and 15, 19, 54, 13, and 1 novel miRNA were identified in HY, SP, ZO, CY, and IN, respectively. It was found that the expression profiles of known miRNAs vary greatly at different stages and could be divided into 4 categories. Novel miRNAs mostly belong to part I. Gene ontology (GO) analysis of known miRNA-targeting genes showed that they are involved in the catalytic activity pathway, binding function, and other biological processes. Kyoto Encyclopedia of Gene and Genome (KEGG) analysis of novel miRNA-targeting genes showed that they are involved in the lysine degradation pathway. The expression of candidate miRNAs was validated using quantitative reverse transcription-polymerase chain reaction (qRT-PCR), and miRNAs were downregulated in PcDCL1 or PcAGO1 mutants. To further explore the function of the detected miRNAs, the precursor of a novel miRNA, miR91, was knockout by CRISPR-Cas9, the mutants displayed decreased mycelial growth, sporangia production, and zoospore production. It was found that 503142 (Inositol polyphosphate 5-phosphatase and related proteins) can be predicted as a target of miR91, and the interaction between miR91 and 503142 was verified using the tobacco transient expression system. Overall, our results indicate that the diverse and differentially expressed sRNAs are involved in the development and pathogenesis of P. capsici.

Towards humanlike grasp in robotic hands: mechanical implementation of force synergies.

In the field of robotic hands, finger force coordination is usually achieved by complex mechanical structures and control systems. This study presents the design of a novel transmission system inspired from the physiological concept of force synergies, aiming to simplify the control of multifingered robotic hands. To this end, we collected human finger force data during six isometric grasping tasks, and force synergies (i.e. the synergy weightings and the corresponding activation coefficients) were extracted from the concatenated force data to explore their potential for force modulation. We then implemented two force synergies with a cable-driven transmission mechanism consisting of two spring-loaded sliders and five V-shaped bars. Specifically, we used fixed synergy weightings to determine the stiffness of the compression springs, and the displacements of sliders were determined by time-varying activation coefficients. The derived transmission system was then used to drive a five-finger robotic hand named SYN hand. We also designed a motion encoder to selectively activate desired fingers, making it possible for two motors to empower a variety of hand postures. Experiments on the prototype demonstrate successful grasp of a wide range of objects in everyday life, and the finger force distribution of SYN hand can approximate that of human hand during six typical tasks. To our best knowledge, this study shows the first attempt to mechanically implement force synergies for finger force modulation in a robotic hand. In comparison to state-of-the-art robotic hands with similar functionality, the proposed hand can distribute humanlike force ratios on the fingers by simple position control, rather than resorting to additional force sensors or complex control strategies. The outcome of this study may provide alternatives for the design of novel anthropomorphic robotic hands, and thus show application prospects in the field of hand prostheses and exoskeletons.

A novel and ubiquitous miRNA-involved regulatory module ensures precise phosphorylation of RNA polymerase II and proper transcription.

Proper transcription orchestrated by RNA polymerase II (RNPII) is crucial for cellular development, which is rely on the phosphorylation state of RNPII's carboxyl-terminal domain (CTD). Sporangia, developed from mycelia, are essential for the destructive oomycetes Phytophthora, remarkable transcriptional changes are observed during the morphological transition. However, how these changes are rapidly triggered and their relationship with the versatile RNPII-CTD phosphorylation remain enigmatic. Herein, we found that Phytophthora capsici undergone an elevation of Ser5-phosphorylation in its uncanonical heptapeptide repeats of RNPII-CTD during sporangia development, which subsequently changed the chromosomal occupation of RNPII and primarily activated transcription of certain genes. A cyclin-dependent kinase, PcCDK7, was highly induced and phosphorylated RNPII-CTD during this morphological transition. Mechanistically, a novel DCL1-dependent microRNA, pcamiR1, was found to be a feedback modulator for the precise phosphorylation of RNPII-CTD by complexing with PcAGO1 and regulating the accumulation of PcCDK7. Moreover, this study revealed that the pcamiR1-CDK7-RNPII regulatory module is evolutionarily conserved and the impairment of the balance between pcamiR1 and PcCDK7 could efficiently reduce growth and virulence of P. capsici. Collectively, this study uncovers a novel and evolutionary conserved mechanism of transcription regulation which could facilitate correct development and identifies pcamiR1 as a promising target for disease control.

Classification of Action Potentials With High Variability Using Convolutional Neural Network for Motor Unit Tracking.

The reliable classification of motor unit action potentials (MUAPs) provides the possibility of tracking motor unit (MU) activities. However, the variation of MUAP profiles caused by multiple factors in realistic conditions challenges the accurate classification of MUAPs. The goal of this study was to propose an effective method based on the convolutional neural network (CNN) to classify MUAPs with high levels of variation for MU tracking. MUAP variation was added artificially in the synthetic electromyogram (EMG) signals and was induced by changing the forearm postures in the experimental study. The proposed overlapped-segment-wise EMG decomposition method and the spike-triggered averaging method were combined to obtain the MUAP waveform samples of individual MUs in the experimental study, and the MUAP profile classification performance was tested. Since the ground-truth of MU discharge activities was known for the synthetic EMG, the MU tracking performance was further verified by mimicking the tracking procedure of MU discharge activities and the spike consistency with the true spike trains was tested in the simulation study. The conventional MUAP similarity index (SI)-based method was also performed as comparison. For both the experimental and the synthetic EMG signals, the CNN-based method significantly improved the MUAP tracking performance compared with the conventional SI-based method manifested as a higher classification accuracy (93.3%±5.4% vs 56.2%±13.9%) in the experimental study or higher spike consistency (71.1%±10.2% vs 29.2%±11.0%) in the simulation study with a smaller variation. These results demonstrated the efficiency and robustness of the proposed method to distinguish MUAPs with large variations accurately. Further development of the proposed method can promote the study on the physiological and pathological changes of the neuromuscular system where tracking MU activities is needed.

N6-methyloxyadenine-mediated detoxification and ferroptosis confer a trade-off between multi-fungicide resistance and fitness.

Multi-fungicide resistance (MFR) is a serious environmental problem, which results in the excessive use of fungicides. Fitness penalty, as a common phenomenon in MFR, can partially counteract the issue of resistance due to the weakened vigor of MFR pathogens. Their underlying mechanism and relationship remain unexplained. By Oxford Nanopore Technologies sequencing and dot blot, we found that N6-methyloxyadenine (6mA) modification, the dominate epigenetic marker in Phytophthora capsici, was significantly altered after MFR emerged. Among the differently methylated genes, PcGSTZ1 could efficiently detoxify SYP-14288, a novel uncoupler, through complexing the fungicide with glutathione and induce MFR. Interestingly, PcGSTZ1 overexpression was induced by elevated 6mA levels and chromatin accessibility to its genomic loci. Moreover, the overexpression led to reactive oxygen species burst and ferroptosis in SYP-14288-resistant mutants, which enhanced the resistance and induced fitness penalty in P. capsici through triggering low energy shock adaptive response. Furthermore, this study revealed that the 6mA-PcGSTZ1-ferroptosis axis could mediate intergenerational resistance memory transmission and enabled adaptive advantage to P. capsici. In conclusion, the findings provide new insights into the biological role of 6mA as well as the mechanisms underlying the trade-off between MFR and fitness. These could also benefit disease control through the blockade of the epigenetic axis to resensitize resistant isolates.IMPORTANCEN6-methyloxyadenine (6mA) modification on DNA is correlated with tolerance under different stress in prokaryotes. However, the role of 6mA in eukaryotes remains poorly understood. Our current study reveals that DNA adenine methyltransferase 1 (DAMT1)-mediated 6mA modification at the upstream region of GST zeta 1 (GSTZ1) is elevated in the resistant strain. This elevation promotes the detoxification uncoupler and induces multifungicide resistance (MFR). Moreover, the overexpression led to reactive oxygen species burst and ferroptosis in SYP-14288-resistant mutants, which enhanced the resistance and induced fitness penalty in Phytophthora capsici through triggering low energy shock adaptive response. Furthermore, this study revealed that the 6mA-PcGSTZ1-ferroptosis axis could mediate intergenerational resistance memory transmission and enabled adaptive advantage to P. capsici. Overall, our findings uncover an innovative mechanism underlying 6mA modification in regulating PcGSTZ1 transcription and the ferroptosis pathway in P. capsici.

Filter bank second-order underdamped stochastic resonance analysis for implementing a short-term high-speed SSVEP detection.

OBJECTIVE: The progression of brain-computer interfaces (BCIs) has been propelled by breakthroughs in neuroscience, signal processing, and machine learning, marking it as a dynamic field of study over the past few decades. Nevertheless, the nonlinear and non-stationary characteristics of steady-state visual evoked potentials (SSVEPs), coupled with the incongruity between frequently employed linear techniques and nonlinear signal attributes, resulted in the subpar performance of mainstream non-training algorithms like canonical correlation analysis (CCA), multivariate synchronization index (MSI), and filter bank CCA (FBCCA) in short-term SSVEP detection. METHODS: To tackle this problem, the novel fusions of common filter bank analysis, CCA dimensionality reduction methods, USSR models, and MSI recognition models are used in SSVEP signal recognition. RESULTS: Unlike conventional linear techniques such as CCA, MSI, and FBCCA, the filter bank second-order underdamped stochastic resonance (FBUSSR) analysis demonstrates superior efficacy in the detection of short-term high-speed SSVEPs. CONCLUSION: This research enlists 32 subjects and uses a public dataset to assess the proposed approach, and the experimental outcomes indicate that the non-training method can attain greater recognition precision and stability. Furthermore, under the conditions of the newly proposed fusion method and light stimulation, the USSR model exhibits the most optimal enhancement effect. SIGNIFICANCE: The findings of this study underscore the expansive potential for the application of BCI systems in the realm of neuroscience and signal processing.

Bionic intelligent ankle-foot prosthesis based on the conjugate curved surface.

Given the poor biomimetic motion of traditional ankle-foot prostheses, it is of great significance to develop an intelligent prosthesis that can realize the biomimetic mechanism of human feet and ankles. To this end, we presented a bionic intelligent ankle-foot prosthesis based on the complex conjugate curved surface. The proposed prosthesis is mainly composed of the rolling conjugated joints with a bionic design and the carbon fiber energy-storage foot. We investigated the flexibility of the prosthetic ankle joint movement, and the ability of the prosthetic foot to absorb ground impact during the gait cycle. Experimental results showed the matching of the ankle/toe position relationship of the human foot during simulated walking, which is helpful to realize the biomimetic motion of the human foot and ankle. It can also help therapists and clinicians provide better rehabilitation for lower-limb amputees.

A quantization algorithm of visual fatigue based on underdamped second order stochastic resonance for steady state visual evoked potentials.

Introduction: In recent years, more and more attention has been paid to the visual fatigue caused by steady state visual evoked potential (SSVEP) paradigm. It is well known that the large-scale application of brain-computer interface is closely related to SSVEP, and the fatigue caused by SSVEP paradigm leads to the reduction of application effect. At present, the mainstream method of objectively quantifying visual fatigue in SSVEP paradigm is based on traditional canonical correlation analysis (CCA). Methods: In this paper, we propose a new SSVEP paradigm visual fatigue quantification algorithm based on underdamped second-order stochastic resonance (USSR) to accurately quantify visual fatigue caused by SSVEP paradigm in different working modes using single-channel electroencephalogram (EEG) signals. This scheme uses the fixed-step energy parameter optimization algorithm we designed, combined with the USSR model, to significantly improve the signal-to-noise ratio of the processed signal at the target characteristic frequency. We not only compared the new algorithm with CCA, but also with the traditional subjective quantitative visual fatigue gold standard Likert fatigue scale. Results: There was no significant difference (p = 0.090) between the quantitative value of paradigm fatigue obtained by the single channel SSVEP processed by the new algorithm and the gold standard of subjective fatigue quantification, while there was a significant difference (p < 0.001***) between the quantitative value of paradigm fatigue obtained by the traditional multi-channel CCA algorithm and the gold standard of subjective fatigue quantification. Discussion: The conclusion shows that the quantization value obtained by the new algorithm can better match the subjective gold standard score, which also shows that the new algorithm is more reliable, which reflects the superiority of the new algorithm.

Concurrent and continuous estimation of multi-finger forces by synergy mapping and reconstruction: a pilot study.

Objective.The absence of intuitive control in present myoelectric interfaces makes it a challenge for users to communicate with assistive devices efficiently in real-world conditions. This study aims to tackle this difficulty by incorporating neurophysiological entities, namely muscle and force synergies, onto multi-finger force estimation to allow intuitive myoelectric control.Approach. Eleven healthy subjects performed six isometric grasping tasks at three muscle contraction levels. The exerted fingertip forces were collected concurrently with the surface electromyographic (sEMG) signals from six extrinsic and intrinsic muscles of hand. Muscle synergies were then extracted from recorded sEMG signals, while force synergies were identified from measured force data. Afterwards, a linear regressor was trained to associate the two types of synergies. This would allow us to predict multi-finger forces simply by multiplying the activation signals derived from muscle synergies with the weighting matrix of initially identified force synergies. To mitigate the false activation of unintended fingers, the force predictions were finally corrected by a finger state recognition procedure.Main results. We found that five muscle synergies and four force synergies are able to make a tradeoff between the computation load and the prediction accuracy for the proposed model; When trained and tested on all six grasping tasks, our method (SYN-II) achieved better performance (R2= 0.80 ± 0.04, NRMSE = 0.19 ± 0.01) than conventional sEMG amplitude-based method; Interestingly, SYN-II performed better than all other methods when tested on two unknown tasks outside the four training tasks (R2= 0.74 ± 0.03, NRMSE = 0.22 ± 0.02), which indicated better generalization ability.Significance. This study shows the first attempt to link between muscle and force synergies to allow concurrent and continuous estimation of multi-finger forces from sEMG. The proposed approach may lay the foundation for high-performance myoelectric interfaces that allow users to control robotic hands in a more natural and intuitive manner.

Development and validation of a novel nomogram predicting clinically significant prostate cancer in biopsy-naive men based on multi-institutional analysis.

BACKGROUND: Prediction of clinically significant prostate cancer (csPCa) is essential to select biopsy-naive patients for prostate biopsy. This study was to develop and validate a nomogram based on clinicodemographic parameters and exclude csPCa using prostate-specific antigen density (PSAD) stratification. METHODS: Independent predictors were determined via univariate and multivariate logistic analysis and adopted for developing a predictive nomogram, which was assessed in terms of discrimination, calibration, and net benefit. Different PSAD thresholds were used for deciding immediate biopsies in patients with Prostate Imaging-Reporting and Data System (PI-RADS) 3 lesions. RESULTS: A total of 932 consecutive patients who underwent ultrasound-guided transperineal cognitive biopsy were enrolled in our study. In the development cohort, age (odds ratio [OR], 1.075; 95% confidence interval [CI], 1.036-1.114), PSAD (OR, 6.003; 95% CI, 2.826-12.751), and PI-RADS (OR, 3.419; 95% CI, 2.453-4.766) were significant predictors for csPCa. On internal and external validation, this nomogram showed high areas under the curve of 0.943, 0.922, and 0.897, and low Brier scores of 0.092, 0.102, and 0.133 and insignificant unreliability tests of 0.713, 0.490, and 0.859, respectively. Decision curve analysis revealed this model could markedly improve clinical net benefit. The probability of excluding csPCa was 98.51% in patients with PI-RADS 3 lesions and PSAD <0.2 ng/ml2 . CONCLUSION: This novel nomogram including age, PSAD, and PI-RADS could be applied to accurately predict csPCa, and 44.08% of patients with equivocal imaging findings plus PSAD <0.2 ng/ml2 could safely forgo biopsy.

A novel untrained SSVEP-EEG feature enhancement method using canonical correlation analysis and underdamped second-order stochastic resonance.

Objective: Compared with the light-flashing paradigm, the ring-shaped motion checkerboard patterns avoid uncomfortable flicker or brightness modulation, improving the practical interactivity of brain-computer interface (BCI) applications. However, due to fewer harmonic responses and more concentrated frequency energy elicited by the ring-shaped checkerboard patterns, the mainstream untrained algorithms such as canonical correlation analysis (CCA) and filter bank canonical correlation analysis (FBCCA) methods have poor recognition performance and low information transmission rate (ITR). Methods: To address this issue, a novel untrained SSVEP-EEG feature enhancement method using CCA and underdamped second-order stochastic resonance (USSR) is proposed to extract electroencephalogram (EEG) features. Results: In contrast to typical unsupervised dimensionality reduction methods such as common average reference (CAR), principal component analysis (PCA), multidimensional scaling (MDS), and locally linear embedding (LLE), CCA exhibits higher adaptability for SSVEP rhythm components. Conclusion: This study recruits 42 subjects to evaluate the proposed method and experimental results show that the untrained method can achieve higher detection accuracy and robustness. Significance: This untrained method provides the possibility of applying a nonlinear model from one-dimensional signals to multi-dimensional signals.

The CAP superfamily protein PsCAP1 secreted by Phytophthora triggers immune responses in Nicotiana benthamiana through a leucine-rich repeat receptor-like protein.

The role of cysteine-rich secretory proteins, antigen 5, and pathogenesis-related 1 (CAP) superfamily proteins in the innate immune responses of mammals is well characterized. However, the biological function of CAP superfamily proteins in plant-microbe interactions is poorly understood. We used proteomics and transcriptome analyses to dissect the apoplastic effectors secreted by the oomycete Phytophthora sojae during early infection of soybean leaves. By transiently expressing these effectors in Nicotiana benthamiana, we identified PsCAP1, a novel type of secreted CAP protein that triggers immune responses in multiple solanaceous plants including N. benthamiana. This secreted CAP protein is conserved among oomycetes, and multiple PsCAP1 homologs can be recognized by N. benthamiana. PsCAP1-triggered immune responses depend on the N-terminal immunogenic fragment (aa 27-151). Pretreatment of N. benthamiana with PsCAP1 or the immunogenic fragment increases plant resistance against Phytophthora. The recognition of PsCAP1 and different homologs requires the leucine-rich repeat receptor-like protein RCAP1, which associates with two central receptor-like kinases BRI1-associated receptor kinase 1 (BAK1) and suppressor of BIR1-1 (SOBIR1) in planta. These findings suggest that the CAP-type apoplastic effectors act as an important player in plant-microbe interactions that can be perceived by plant membrane-localized receptor to activate plant resistance.

A Phytophthora receptor-like kinase regulates oospore development and can activate pattern-triggered plant immunity.

Plant cell-surface leucine-rich repeat receptor-like kinases (LRR-RLKs) and receptor-like proteins (LRR-RLPs) form dynamic complexes to receive a variety of extracellular signals. LRR-RLKs are also widespread in oomycete pathogens, whereas it remains enigmatic whether plant and oomycete LRR-RLKs could mediate cell-to-cell communications between pathogen and host. Here, we report that an LRR-RLK from the soybean root and stem rot pathogen Phytophthora sojae, PsRLK6, can activate typical pattern-triggered immunity in host soybean and nonhost tomato and Nicotiana benthamiana plants. PsRLK6 homologs are conserved in oomycetes and also exhibit immunity-inducing activity. A small region (LRR5-6) in the extracellular domain of PsRLK6 is sufficient to activate BAK1- and SOBIR1-dependent immune responses, suggesting that PsRLK6 is likely recognized by a plant LRR-RLP. Moreover, PsRLK6 is shown to be up-regulated during oospore maturation and essential for the oospore development of P. sojae. Our data provide a novel type of microbe-associated molecular pattern that functions in the sexual reproduction of oomycete, and a scenario in which a pathogen LRR-RLK could be sensed by a plant LRR-RLP to mount plant immunity.

Capturing synchronization with complexity measure of ordinal pattern transition network constructed by crossplot.

To evaluate the synchronization of bivariate time series has been a hot topic, and a number of measures have been proposed. In this work, by introducing the ordinal pattern transition network into the crossplot, a new method for measuring the synchronization of bivariate time series is proposed. After the crossplot been partitioned and coded, the coded partitions are defined as network nodes and a directed weighted network is constructed based on the temporal adjacency of the nodes. The crossplot transition entropy of the network is proposed as an indicator of the synchronization between two time series. To test the characteristics and performance of the method, it is used to analyse the unidirectional coupled Lorentz model and compared it with existing methods. The results showed the new method had the advantages of easy parameter setting, efficiency, robustness, good consistency and suitability for short time series. Finally, electroencephalogram (EEG) data from auditory-evoked potential EEG-biometric dataset are investigated, and some useful and interesting results are obtained.

Case report: High-frequency repetitive transcranial magnetic stimulation for treatment of hereditary spastic paraplegia type 11.

Hereditary spastic paraplegia (HSP) is a heterogeneous group of inherited neurodegenerative disorders that currently have no cure. HSP type 11 (SPG11-HSP) is a complex form carrying mutations in the SPG11 gene. Neuropathological studies demonstrate that motor deficits in these patients are mainly attributed to axonal degeneration of the corticospinal tract (CST). Repetitive transcranial magnetic stimulation (rTMS) is a non-invasive technique that can induce central nervous system plasticity and promote neurological recovery by modulating the excitability of cortical neuronal cells. Although rTMS is expected to be a therapeutic tool for neurodegenerative diseases, no previous studies have applied rTMS to treat motor symptoms in SPG11-HSP. Here, we report a case of SPG11-HSP with lower extremity spasticity and gait instability, which were improved by applying high-frequency rTMS (HF-rTMS) at the primary motor cortex (M1). Clinical and physiological features were measured throughout the treatment, including the Modified Ashworth Scale (MAS), Berg Balance Scale (BBS), the timed up and go (TUG) test and the 10-meter walk test time (10 MWT). The structure and excitability of the CST were assessed by diffusion tensor imaging (DTI) and transcranial magnetic stimulation (TMS), respectively. After treatment, the patient gained 17 points of BBS, along with a gradual decrease in MAS scores of the bilateral lower extremity. In addition, the TUG test and 10 MWT improved to varying degrees. TMS assessment showed increased motor evoked potential (MEP) amplitude, decreased resting motor threshold (RMT), decreased central motor conduction time (CMCT), and decreased difference in the cortical silent period (CSP) between bilateral hemispheres. Using the DTI technique, we observed increased fractional anisotropy (FA) values and decreased mean diffusivity (MD) and radial diffusivity (RD) values in the CST. It suggests that applying HF-rTMS over the bilateral leg area of M1 (M1-LEG) is beneficial for SPG11-HSP. In this study, we demonstrate the potential of rTMS to promote neurological recovery from both functional and structural perspectives. It may provide a clinical rationale for using rTMS in the rehabilitation of HSP patients.