Melatonin (N‐acetyl‐5‐methoxytryptamine) plays important roles in plant defences against a variety of biotic and abiotic stresses, including UV‐B stress. Molecular mechanisms underlying functions of ...melatonin in plant UV‐B responses are poorly understood. Here, we show that melatonin effect on molecular signalling pathways, physiological changes and UV‐B stress resistance in Arabidopsis. Both exogenous and endogenous melatonin affected expression of UV‐B signal transduction pathway genes. Experiments using UV‐B signalling component mutants cop1‐4 and hy5‐215 revealed that melatonin not only acts as an antioxidant to promote UV‐B stress resistance, but also regulates expression of several key components of UV‐B signalling pathway, including ubiquitin‐degrading enzyme (COP1), transcription factors (HY5, HYH) and RUP1/2. Our findings indicate that melatonin delays and subsequently enhances expression of COP1, HY5, HYH and RUP1/2, which act as central effectors in UV‐B signalling pathway, thus regulating their effects on antioxidant systems to protect the plant from UV‐B stress.
Several studies have demonstrated that melatonin plays a role in UV‐B responses, however, the molecular mechanism whereby melatonin affects the UV‐B pathway was not clear. This study examined the function of melatonin in molecular signaling pathways, physiological changes, and UV‐B stress resistance under UV‐B radiation in Arabidopsis. Exogenous melatonin treatment experiment indicated that melatonin could enhance the transcriptional level of genes on UV‐B signaling pathway and ameliorate ROS damage caused by UV‐B stress. This result was verified in SNAT overexpressing lines and knock‐down mutant.
Consensusability of multi-agent systems (MASs) is a fundamental problem in the MAS research area, since when starting to design a consensus protocol, one should know whether or not there exists such ...a protocol that has the ability to make the MAS involved consensus. This technical note is aimed at studying the joint impact of the agent dynamic structure and the communication topology on consensusability. For the MASs with fixed topology and agents described by linear time-invariant systems, a necessary condition of consensusability with respect to a set of admissible consensus protocols is given, which is shown, under some mild conditions, to be necessary and sufficient.
Abstract
Motivation
Mitochondria are an essential organelle in most eukaryotes. They not only play an important role in energy metabolism but also take part in many critical cytopathological ...processes. Abnormal mitochondria can trigger a series of human diseases, such as Parkinson's disease, multifactor disorder and Type-II diabetes. Protein submitochondrial localization enables the understanding of protein function in studying disease pathogenesis and drug design.
Results
We proposed a new method, SubMito-XGBoost, for protein submitochondrial localization prediction. Three steps are included: (i) the g-gap dipeptide composition (g-gap DC), pseudo-amino acid composition (PseAAC), auto-correlation function (ACF) and Bi-gram position-specific scoring matrix (Bi-gram PSSM) are employed to extract protein sequence features, (ii) Synthetic Minority Oversampling Technique (SMOTE) is used to balance samples, and the ReliefF algorithm is applied for feature selection and (iii) the obtained feature vectors are fed into XGBoost to predict protein submitochondrial locations. SubMito-XGBoost has obtained satisfactory prediction results by the leave-one-out-cross-validation (LOOCV) compared with existing methods. The prediction accuracies of the SubMito-XGBoost method on the two training datasets M317 and M983 were 97.7% and 98.9%, which are 2.8–12.5% and 3.8–9.9% higher than other methods, respectively. The prediction accuracy of the independent test set M495 was 94.8%, which is significantly better than the existing studies. The proposed method also achieves satisfactory predictive performance on plant and non-plant protein submitochondrial datasets. SubMito-XGBoost also plays an important role in new drug design for the treatment of related diseases.
Availability and implementation
The source codes and data are publicly available at https://github.com/QUST-AIBBDRC/SubMito-XGBoost/.
Supplementary information
Supplementary data are available at Bioinformatics online.
Abstract
Appropriate ways to measure the similarity between single-cell RNA-sequencing (scRNA-seq) data are ubiquitous in bioinformatics, but using single clustering or classification methods to ...process scRNA-seq data is generally difficult. This has led to the emergence of integrated methods and tools that aim to automatically process specific problems associated with scRNA-seq data. These approaches have attracted a lot of interest in bioinformatics and related fields. In this paper, we systematically review the integrated methods and tools, highlighting the pros and cons of each approach. We not only pay particular attention to clustering and classification methods but also discuss methods that have emerged recently as powerful alternatives, including nonlinear and linear methods and descending dimension methods. Finally, we focus on clustering and classification methods for scRNA-seq data, in particular, integrated methods, and provide a comprehensive description of scRNA-seq data and download URLs.
Single-cell multi-omics (scMulti-omics) has brought transformative insights into immuno-oncology, demonstrating success in describing novel immune subsets and defining important regulators of ...antitumor immunity. Here, we give examples of how scMulti-omics has been used in specific tumor studies and discuss how this may develop in the future.
Single-cell RNA-sequencing (scRNA-Seq) is widely used to reveal the heterogeneity and dynamics of tissues, organisms, and complex diseases, but its analyses still suffer from multiple grand ...challenges, including the sequencing sparsity and complex differential patterns in gene expression. We introduce the scGNN (single-cell graph neural network) to provide a hypothesis-free deep learning framework for scRNA-Seq analyses. This framework formulates and aggregates cell-cell relationships with graph neural networks and models heterogeneous gene expression patterns using a left-truncated mixture Gaussian model. scGNN integrates three iterative multi-modal autoencoders and outperforms existing tools for gene imputation and cell clustering on four benchmark scRNA-Seq datasets. In an Alzheimer's disease study with 13,214 single nuclei from postmortem brain tissues, scGNN successfully illustrated disease-related neural development and the differential mechanism. scGNN provides an effective representation of gene expression and cell-cell relationships. It is also a powerful framework that can be applied to general scRNA-Seq analyses.
Artificial neuron is an important part of constructing neuromorphic network in which information can be computed with high parallelism and efficiency like in the human brain. However, owing to the ...poor biological plausibility, artificial neurons based on traditional complementary metal-oxide-semiconductor (CMOS) platform fail to reveal the rich ion dynamics of the biological counterparts. Organic–inorganic halide perovskites (OHPs) are prospective for imitating the ion dynamics on the membranes of biological neurons because of its intrinsic ion migration. Herein, a diffusive CH3NH3PbI3(MAPbI3)-based memristor with superior amplitude-frequency characteristics and highly linear conductivity modulation for more than 1000 states have been fabricated for the construction of a leaky integrate-and-fire (LIF) bio-inspired neuron. The as-designed LIF model can successfully emulate the leakage, spatiotemporal integration and firing functions in a biological neuron. Moreover, by connecting LIF neurons with a 2*2 non-volatile Al2O3-based synaptic array, a simple spiking neural network (SNN) which is called the 3rd generation of neural network has been implemented at the hardware level to study the cognitive performance of the network. The SNN exhibits outstanding selective sensitivity to particular input sequence, indicating the excellent adaptability and versatility of the network for future applications of neuromorphic computing by utilizing novel ionotropic device.
Herein, for the first time, a diffusive CH3NH3PbI3(MAPbI3)-based memristor with superior amplitude-frequency characteristics and highly linear conductivity modulation for more than 1000 states have been fabricated for the construction of a leaky integrate-and-fire (LIF) bio-inspired neuron. The as-designed LIF model can successfully emulate the leakage, spatiotemporal integration and firing functions in a biological neuron, indicating the great potential for neuromorphic computing. Furthermore, by connecting LIF neurons with a 2*2 non-volatile Al2O3-based synaptic array, a simple spiking neural network has been implemented at the hardware level to study the cognitive performance of the network. Display omitted
•The conductance states of MAPbI3-based memristor can be modulated linearly and consecutively for more than 1000 states.•The memristor exhibits superior amplitude-frequency response characteristics which may be also suitable for filter.•A leaky integrate-and-fire artificial neuron is implemented, and the leakage, spatiotemporal integration and firing functions are emulated successfully.•By combining the artificial neuron with an synaptic array, a simple spiking neural network has been implemented.
Hippophae rhamnoides L. (sea buckthorn), consumed as a food and health supplement worldwide, has rich nutritional and medicinal properties. Different parts of H. rhamnoides L. were used in ...traditional Chinese medicines for relieving cough, aiding digestion, invigorating blood circulation, and alleviating pain since ancient times. Phytochemical studies revealed a wide variety of phytonutrients, including nutritional components (proteins, minerals, vitamins, etc.) and functional components like flavonoids (1–99), lignans (100–143), volatile oils (144–207), tannins (208–230), terpenoids (231–260), steroids (261–270), organic acids (271–297), and alkaloids (298–305). The pharmacological studies revealed that some crude extracts or compounds of H. rhamnoides L. demonstrated various health benefits, such as anti-inflammatory, antioxidant, hepatoprotective, anticardiovascular disease, anticancer, hypoglycemic, hypolipidemic, neuroprotective, antibacterial activities, and their effective doses and experimental models were summarized and analyzed in this paper. The quality markers (Q-markers) of H. rhamnoides L. were predicted and analyzed based on protobotanical phylogeny, traditional medicinal properties, expanded efficacy, pharmacokinetics and metabolism, and component testability. The applications of H. rhamnoides L. in juice, wine, oil, ferment, and yogurt were also summarized and future prospects were examined in this review. However, the mechanism and structure–activity relationship of some active compounds are not clear, and quality control and potential toxicity are worth further study in the future.
Extracellular vesicles (EVs) are nano-sized membrane-bounded particles, released by all cells and capable of transporting bioactive cargoes, proteins, lipids, and nucleic acids, to regulate a variety ...of biological functions. Seminal plasma is enriched in EVs, and extensive evidence has revealed the role of EVs (e.g. prostasomes and epididymosomes) in the male genital tract. Recently, EVs released from testicular cells have been isolated and identified, and some new insights have been generated on their role in maintaining normal spermatogenesis and steroidogenesis in the testis. In the seminiferous tubules, Sertoli cell-derived EVs can promote the differentiation of spermatogonial stem cells (SSCs), and EVs secreted from undifferentiated A spermatogonia can inhibit the proliferation of SSCs. In the testicular interstitium, EVs have been identified in endothelial cells, macrophages, telocytes, and Leydig cells, although their roles are still elusive. Testicular EVs can also pass through the blood-testis barrier and mediate inter-compartment communication between the seminiferous tubules and the interstitium. Immature Sertoli cell-derived EVs can promote survival and suppress the steroidogenesis of Leydig cells. Exosomes isolated from macrophages can protect spermatogonia from radiation-induced injury. In addition to their role in intercellular communication, testicular EVs may also participate in the removal of aberrant proteins and the delivery of antigens for immune tolerance. EVs released from testicular cells can be detected in seminal plasma, which makes them potential biomarkers reflecting testicular function and disease status. The testicular EVs in seminal plasma may also affect the female reproductive tract to facilitate conception and may even affect early embryogenesis through modulating sperm RNA. EVs represent a new type of intercellular messenger in the testis. A detailed understanding of the role of testicular EV may contribute to the discovery of new mechanisms causing male infertility and enable the development of new diagnostic and therapeutic strategies for the treatment of infertile men.
This study considers the effects of measurement noises on bipartite consensus over undirected signed graphs. Each agent has to design a protocol based on imprecise information caused by noises. To ...reduce the detrimental effects of measurement noises, a time-varying consensus gain a(t) is introduced and then a time-varying stochastic-type protocol is presented to solve the bipartite consensus problem for the first time. By means of stochastic Lyapunov analysis and algebraic graph theory, the protocol is proved to be a mean-square bipartite consensus protocol. Particularly, in the noise-free case, not only sufficient, but also necessary conditions for ensuring a bipartite consensus are given. Conditions for the undirected signed graph to be structurally balanced and connected are shown to be the weakest assumptions on connectivity. Moreover, the structural unbalance case is studied in the presence of measurement noises. In this case, bipartite consensus value is proved to converge to zero in mean square for arbitrary initial conditions.
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