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Intracranial electrical stimulation (iES) of auditory cortex can elicit sound experiences with a variety of perceived contents (hallucination or illusion) and locations (contralateral or bilateral side), independent of actual acoustic inputs. However, the neural mechanisms underlying this elicitation heterogeneity remain undiscovered. Here, we collected subjective reports following iES at 3062 intracranial sites in 28 patients and identified 113 auditory cortical sites with iES-elicited sound experiences. We then decomposed the sound-induced intracranial electroencephalogram (iEEG) signals recorded from all 113 sites into time-frequency features. We found that the iES-elicited perceived contents can be predicted by the early high-γ features extract from sound-induced iEEG. In contrast, the perceived locations elicited by stimulating hallucination sites and illusion sites are determined by the late high-γ and long-lasting α features, respectively. Our study unveils the crucial neural signatures of iES-elicited sound experiences in human and presents a new strategy to hearing restoration for individuals suffering from deafness.

Objectives: At present, quality education has gradually been recognized by the whole society, and a consensus has been reached on its importance, which has put forward stricter requirements for the distribution of faculty in universities. Methods: In this paper, based on neuropsychology, the distribution of teaching staff in colleges and universities was studied, and the model of talent evaluation and distribution was constructed. Results: Firstly, the generalized regression neural network was optimized by genetic algorithm. Then, the genetic algorithm’s generalized regression neural network calculation process was designed. Conclusion: Finally, with the example of teacher resources in a university, the algorithm in this paper was tested. The results show that the results of the generalized regression neural network optimized by genetic algorithm can match the actual situation very well, and the method is feasible with certain advantages.

The outbreak of C. auratus gibelio gill hemorrhagic disease caused by CyHV-2 brought great losses to the gibel carp industry. Therefore, exploring the interaction between CyHV-2 and host and the molecular mechanism of viral infection is of great significance in preventing and treating the gibel carp gill hemorrhagic disease.

Linguistic communication is often regarded as an action that serves a function to convey the speaker's goal to the addressee. Here, with an functional magnetic resonance imaging (fMRI) study and a lesion study, we demonstrated that communicative functions are represented in the human premotor cortex. Participants read scripts involving 2 interlocutors. Each script contained a critical sentence said by the speaker with a communicative function of either making a Promise, a Request, or a Reply to the addressee's query. With various preceding contexts, the critical sentences were supposed to induce neural activities associated with communicative functions rather than specific actions literally described by these sentences. The fMRI results showed that the premotor cortex contained more information, as revealed by multivariate analyses, on communicative functions and relevant interlocutors' attitudes than the perisylvian language regions. The lesion study results showed that, relative to healthy controls, the understanding of communicative functions was impaired in patients with lesions in the premotor cortex, whereas no reliable difference was observed between the healthy controls and patients with lesions in other brain regions. These findings convergently suggest the crucial role of the premotor cortex in representing the functions of linguistic communications, supporting that linguistic communication can be seen as an action.

Although persistent efforts have identified and characterized a few candidate genes and related biological processes with potential functions in the adaptation of many species to extreme environments, few works have been conducted to determine the genomic basis of adaptation in endangered livestock breeds that have been living in extreme conditions for more than thousands of years. To fill this gap, we sequenced the whole genomes of nine individuals from three Chinese native endangered cattle breeds that are living in high‐altitude or arid environments. Phylogenetic and evolutionary history analyses of these three and other six breeds showed that the genetic structure of the cattle populations is primarily related to geographic location. Interestingly, we identified pervasive introgression from the yak to Zhangmu cattle (ZMC) that cover several genes (e.g., NOS2, EGLN1 and EPAS1) involved in the hypoxia response and previously identified as positive selection genes in other species, which suggested that the adaptive introgression from yak may have contributed to the adaptation of ZMC to high‐altitude environments. In addition, by contrasting the breeds in opposite living conditions, we revealed a set of candidate genes with various functions from hypoxia response, water metabolism, immune response and body shape change to embryo development and skeletal system development, etc., that may be related to high‐altitude or arid adaptation. Our research provides new insights into the recovery and adaptation of endangered native cattle and other species in extreme environments and valuable resources for future research on animal husbandry to cope with climate change.

SummaryLinguistic communication is often regarded as an action conveying the speaker’s communicative goal to the addressee. With both correlational (an fMRI study) and causal (a lesion study) evidence, we demonstrated that communicative goals are represented in human premotor cortex. Participants read scripts each containing a sentence said by the speaker with a goal of either a promise, a request, or a reply. The fMRI results showed that the premotor cortex represented more information on communicative goals than the perisylvian language regions. The lesion study results showed that, relative to healthy controls, the understanding of communicative goals was impaired in patients with lesions in the premotor cortex, whereas no reliable difference between the healthy controls and lesion controls. These findings convergently suggest that the premotor cortex is crucial for representing the goals conveyed by language, supporting the theoretical view that linguistic communication can be seen as a goal-directed action.

Chromatin accessibility and post-transcriptional histone modifications play important roles in gene expression regulation. However, little is known about the joint effect of multiple chromatin modifications on the gene expression level in plants, despite that the regulatory roles of individual histone marks such as H3K4me3 in gene expression have been well-documented. By using machine-learning methods, we systematically performed gene expression level prediction based on multiple chromatin modifications data in Arabidopsis and rice. We found that as few as four histone modifications were sufficient to yield good prediction performance, and H3K4me3 and H3K36me3 being the top two predictors with known functions related to transcriptional initiation and elongation, respectively. We demonstrated that the predictive powers differed between protein-coding and non-coding genes as well as between CpG-enriched and CpG-depleted genes. We also showed that the predictive model trained in one tissue or species could be applied to another tissue or species, suggesting shared underlying mechanisms. More interestingly, the gene expression levels of conserved orthologs are easier to predict than the species-specific genes. In addition, chromatin state of distal enhancers was moderately correlated to gene expression but was dispensable if given the chromatin features of the proximal regions of genes. We further extended the analysis to transcription factor (TF) binding data. Strikingly, the combinatorial effects of only a few TFs were roughly fit to gene expression levels in Arabidopsis. Overall, by using quantitative modeling, we provide a comprehensive and unbiased perspective on the epigenetic and TF-mediated regulation of gene expression in plants.

Though recent methods on semi-supervised video object segmentation (VOS) have achieved an appreciable improvement of segmentation accuracy, it is still hard to get an adequate speed-accuracy balance when facing real-world application scenarios. In this work, we propose Discriminative Matching for real-time Video Object Segmentation (DMVOS), a real-time VOS framework with high-accuracy to fill this gap. Based on the matching mechanism, our framework introduces discriminative information through the Isometric Correlation module and the Instance Center Offset module. Specifically, the isometric correlation module learns a pixel-level similarity map with semantic discriminability, and the instance center offset module is applied to exploit the instance-level spatial discriminability. Experiments on two benchmark datasets show that our model achieves state-of-the-art performance with extremely fast speed, for example, J&F of 87.8% on DAVIS-2016 validation set with 35 milliseconds per frame.

Distributed wind power (DWP) needs to be consumed locally under a 110 kV network without reverse power flow in China. To maximize the use of DWP, this paper proposes a novel method for capacity planning of DWP with participation of the energy storage system (ESS) in multiple scenarios by means of a variable-structure copula and optimization theory. First, wind power and local load are predicted at the planning stage by an autoregressive moving average (ARMA) model, then, variable-structure copula models are established based on different time segment strategies to depict the correlation of DWP and load, and the joint typical scenarios of DWP and load are generated by clustering, and a capacity planning model of DWP is proposed considering investment and operation cost, and environmental benefit and line loss cost under typical scenario conditions. Moreover, a collaborative capacity planning model for DWP and ESS is prospectively proposed. Based on the modified IEEE-33 bus system, the results of the case study show that the DWP capacity result is more reasonable after considering the correlation of wind and load by using a variable-structure copula. With consideration of the collaborative planning of DWP and load, the consumption of DWP is further improved, the annual cost of the system is more economical, and the quality of voltage is effectively improved. The study results validate the proposed method and provide effective reference for the planning strategy of DWP.

Background The systematic interrogation of reproduction-related genes was key to gain a comprehensive understanding of the molecular mechanisms underlying male reproductive traits in mammals. Here, based on the data collected from the NCBI SRA database, this study first revealed the genes involved in porcine male reproduction as well their uncharacterized transcriptional characteristics. Results Results showed that the transcription of porcine genome was more widespread in testis than in other organs (the same for other mammals) and that testis had more tissue-specific genes (1210) than other organs. GO and GSEA analyses suggested that the identified test is-specific genes (TSGs) were associated with male reproduction. Subsequently, the transcriptional characteristics of porcine TSGs, which were conserved across different mammals, were uncovered. Data showed that 195 porcine TSGs shared similar expression patterns with other mammals (cattle, sheep, human and mouse), and had relatively higher transcription abundances and tissue specificity than low-conserved TSGs. Additionally, further analysis of the results suggested that alternative splicing, transcription factors binding, and the presence of other functionally similar genes were all involved in the regulation of porcine TSGs transcription. Conclusions Overall, this analysis revealed an extensive gene set involved in the regulation of porcine male reproduction and their dynamic transcription patterns. Data reported here provide valuable insights for a further improvement of the economic benefits of pigs as well as future treatments for male infertility.

The scale of training data is significant in segmentation task, especially in segmenting the medical coronary artery angiograms. Traditional semantic segmentation networks have been restricted in this field, due to the particularity of cardiac coronary angiography data, that is, it is very difficult to balance the manual labeling costs and network accuracy. On the basis of these observations, we propose a new method to generate the so-called ‘pseudo-precise’ label and a complementary training pipeline, which can improve the performance of the networks on the premise of reducing labor costs as much as possible. Our method can thus increase the f1-score by 4%-11% with the same amount of precisely labeled data.

Additional file 1: Table S1. SRA samples and project numbers of twelve organs in five mammals. Table S2. Mapping statistics of different organs of pig (Sus scrofa). Table S3. Mapping statistics of different organs of cattle (Bos taurus). Table S4. Mapping statistics of different organs of sheep (Ovis aries). Table S5. Mapping statistics of different organs of human (Homo sapiens). Table S6. Mapping statistics of different organs of mouse (Mus musculus). Table S7. Examples of identified TSGs presented in Table S8. Figure S1. Mapped ratio of mapped to the reference genome in five mammals. Figure S2. Distribution difference of protein-coding genes between testis and other organs in pig. (A-I) Quantile-Quantile (q-q) Plots represent the distribution difference of all expressed protein-coding genes (log2-transformed FPKM) between the testis and other nine organs in pig. The blue lines (y = x) mean the same distribution. Figure S3. Identification of homologous families and homologous genes in five mammals. (A) Venn diagram showing the number of homologous gene families per species. (B) Distribution of 1:1 orthologous gene in five mammals is displayed. Figure S4. Screening of TSGs in other four mammals. The distribution of the tissue specificity index (τ) and the expression levels of TSGs are showed. The dotted lines represent the value of top 20% of τ scores and the significance is calculated using one-sided Wilcoxon rank-sum test (P

In eukaryotes, the three-dimensional (3D) conformation of the genome is far from random, and this nonrandom chromatin organization is strongly correlated with gene expression and protein function, which are two critical determinants of the selective constraints and evolutionary rates of genes. However, whether genes and other elements that are located close to each other in the 3D genome evolve in a coordinated way has not been investigated in any organism. To address this question, we constructed chromatin interaction networks (CINs) in Arabidopsis thaliana based on high-throughput chromosome conformation capture (Hi-C) data and demonstrated that adjacent large DNA fragments in the CIN indeed exhibit more similar levels of polymorphism and evolutionary rates than random fragment pairs. Using simulations that account for the linear distance between fragments, we proved that the 3D chromosomal organization plays a role in the observed correlated evolution. Spatially interacting fragments also exhibit more similar mutation rates and functional constraints in both coding and noncoding regions than the random expectations, indicating that the correlated evolution between 3D neighbors is a result of combined evolutionary forces. A collection of 39 genomic and epigenomic features can explain much of the variance in genetic diversity and evolutionary rates across the genome. Moreover, features that have a greater effect on the evolution of regional sequences tend to show higher similarity between neighboring fragments in the CIN, suggesting a pivotal role of epigenetic modifications and chromatin organization in determining the correlated evolution of large DNA fragments in the 3D genome.

Salinity decreases the yield and quality of crops. Silicon (Si) has been widely reported to have beneficial effects on plant growth and development under salt stress. However, the mechanism is still poorly understood. In an attempt to identify genes or gene networks that may be orchestrated to improve salt tolerance of cucumber plants, we sequenced the transcriptomes of both control and salt-stressed cucumber leaves in the presence or absence of added Si. Seedlings of cucumber ‘JinYou 1’ were subjected to salt stress (75 mM NaCl) without or with addition of 0.3 mM Si. Plant growth, photosynthetic gas exchange and transcriptomic dynamics were investigated. The results showed that Si addition improved the growth and photosynthetic performance of cucumber seedlings under salt stress. The comparative transcriptome analysis revealed that Si played an important role in shaping the transcriptome of cucumber: the expressions of 1469 genes were altered in response to Si treatment in the control conditions, and these genes were mainly involved in ion transport, hormone and signal transduction, biosynthetic and metabolic processes, and stress and defense responses. Under salt stress alone, 1482 genes with putative functions associated with metabolic processes and responses to environmental stimuli have changed their expression levels. Si treatment shifted the transcriptome of salt-stressed cucumber back to that of the control, as evidenced that among the 708 and 774 genes that were up- or down-regulated under salt stress, a large majority of them (609 and 595, respectively) were reverted to the normal expression levels. These results suggest that Si may act as an elicitor to precondition cucumber plants and induce salt tolerance. The study may help us understand the mechanism for silicon-mediated salt tolerance and provide a theoretical basis for silicon application in crop production in saline soils.

Endosperm is a product of double fertilization, and provides nutrients and signals to the embryo during seed development in flowering plants. Early stages of endosperm development are critical for the development of its storage capacity through synthesis and accumulation of starch and storage proteins. Here we report on the isolation and sequencing of mRNAs from the central portion of the starchy endosperm of Zea mays (maize) B73 at 6days after pollination. We detected a high level of correlation among the four biological replicates of RNAs isolated using laser-capture microdissection of the cell type. Because the assayed developmental stage precedes the synthesis and accumulation of the major storage proteins and starch in the endosperm, our dataset likely include mRNAs for genes that are involved in control and establishment of these storage programs. The mRNA-Seq data has been deposited in Gene Expression Omnibus (accession number GSE58504).

In this manuscript, chemical constituents, especially those with novel structures obtained from Acorus tatarinowii Schott (ATS), along with the pharmacological studies of those compounds, the volatile oil and the water soluble part of ATS, were reviewed.

In angiosperms, the endosperm provides nutrients for embryogenesis and seed germination and is the primary tissue where gene imprinting occurs. To identify the imprintome of early developing maize (Zea mays) endosperm, we performed high-throughput transcriptome sequencing of whole kernels at 0, 3, and 5 d after pollination (DAP) and endosperms at 7, 10, and 15 DAP, using B73 by Mo17 reciprocal crosses. We observed gradually increased expression of paternal transcripts in 3- and 5-DAP kernels. In 7-DAP endosperm, the majority of the genes tested reached a 2:1 maternal versus paternal ratio, suggesting that paternal genes are nearly fully activated by 7 DAP. A total of 116, 234, and 63 genes exhibiting parent-specific expression were identified at 7, 10, and 15 DAP, respectively. The largest proportion of paternally expressed genes was at 7 DAP, mainly due to the significantly deviated parental allele expression ratio of these genes at this stage, while nearly 80% of the maternally expressed genes (MEGs) were specific to 10 DAP and were primarily attributed to sharply increased expression levels compared with the other stages. Gene ontology enrichment analysis of the imprinted genes suggested that 10-DAP endosperm-specific MEGs are involved in nutrient uptake and allocation and the auxin signaling pathway, coincident with the onset of starch and storage protein accumulation.

Network biology is conceptualized as an interdisciplinary field, lying at the intersection among graph theory, statistical mechanics and biology. Great efforts have been made to promote the concept of network biology and its various applications in life s

Carrot is widely used as a foodstuff. The active components such as beta-carotene and panaxynol have been studied by many researchers. In this investigation of nonpolar active components from carrot, a new phenylpropanoid, epilaserine oxide ( 3), was isolated along with six known compounds, laserine ( 1), 2-epilaserine ( 2), panaxynol ( 4), ginsenoyne K ( 5), (8 E)-1,8-heptadecadiene-4,6-diyne-3,10-diol ( 6), and vaginatin ( 7). Their structures were deduced on the basis of spectroscopic methods. Significant cytotoxicity of 2-epilaserine against HL-60 cells was observed, which implied that phenylpropanoids were cytotoxic compounds in carrot. Laserine and 2-epilaserine in carrots from diverse locations in China were quantified by HPLC.

Endosperm is a filial structure resulting from a second fertilization event in angiosperms. As an absorptive storage organ, endosperm plays an essential role in support of embryo development and seedling germination. The accumulation of carbohydrate and protein storage products in cereal endosperm provides humanity with a major portion of its food, feed, and renewable resources. Little is known regarding the regulatory gene networks controlling endosperm proliferation and differentiation. As a first step toward understanding these networks, we profiled all mRNAs in the maize kernel and endosperm at eight successive stages during the first 12 d after pollination. Analysis of these gene sets identified temporal programs of gene expression, including hundreds of transcription-factor genes. We found a close correlation of the sequentially expressed gene sets with distinct cellular and metabolic programs in distinct compartments of the developing endosperm. The results constitute a preliminary atlas of spatiotemporal patterns of endosperm gene expression in support of future efforts for understanding the underlying mechanisms that control seed yield and quality.

Two new isoflavone tetraglycosides ( 1 and 2) and six known compounds were isolated from the leaves of Sophora japonica. The new glycosides are genistein 7- O-beta- d-glucopyranoside-4'- O-(6'''- O-alpha- l-rhamnopyranosyl)-beta-sophoroside ( 1) and genistein 7- O-alpha- l-rhamnopyranoside-4'- O-(6'''- O-alpha- l-rhamnopyranosyl)-beta-sophoroside ( 2). The structures of compounds 1 and 2 were established primarily by NMR experiments and chemical methods, and they are the first reported naturally occurring isoflavone glycosides with four attached sugar residues.

The evolution of a species involves changes in its genome and its transcriptome. Divergence in expression patterns may be more important than divergence in sequences for determining phenotypic changes, particularly among closely related species. We examined the relationships between organ evolution, sequence evolution, and expression evolution in Arabidopsis thaliana, rice (Oryza sativa), and maize (Zea mays). We found correlated divergence of gene sequences and expression patterns, with distinct divergence rates that depend on the organ types in which a gene is expressed. For instance, genes specifically expressed in reproductive organs (i.e., stamen) evolve more quickly than those specifically expressed in vegetative organs (e.g., root). The different rates in organ evolution may be due to different degrees of functional constraint associated with the different physiological functions of plant organs. Additionally, the evolutionary rate of a gene sequence is correlated with the breadth of its expression in terms of the number of tissues, the number of coregulation modules, and the number of species in which the gene is expressed, as well as the number of genes with which it may interact. This linkage supports the hypothesis that constitutively expressed genes may experience higher levels of functional constraint accumulated from multiple tissues than do tissue-specific genes.

The Brassicaceae family includes the most important plant model Arabidopsis thaliana and many cruciferous vegetable crops. A number of close relatives of Arabidopsis and economically important Brassica species are being sequenced with whole-genome shotgun sequencing technologies. However, de novo assembly of full chromosomes is difficult, since many non-model Brassicaceae species are lacking genetic and/or physical maps. As a unique feature for Brassicaceae, the genome of each member is composed of 24 conserved chromosomal blocks, and the arrangement of the 24 blocks can be obtained from karyotype analysis via comparative chromosome painting experiments. Taking this advantage, we developed a bioinformatic tool named KGBassembler to automatically finalize assembly of full chromosomes from contigs and/or scaffolds based on available karyotypes of Brassicaceae species.KGBassembler was implemented in C++ with a graphical user interface. It is freely available to academic users at http://www.cmbb.arizona.edu/KGBassembler/.xwang1@cals.arizona.edu.

Background MicroRNAs (miRNAs) play important roles in regulating the expression of protein-coding genes by directing the degradation and/or repression of the translation of gene transcripts. Growing evidence shows that miRNAs are indispensable player in organismal development with its regulatory role in the growth and differentiation of cell lineages. However, the roles of miRNA-mediated regulation in environmental adaptation of organisms are largely unknown. To examine this potential regulatory capability, we characterized microRNAomes from the brain of zebrafish raised under normal (28°C) and cold-acclimated (10°C, 10 days) conditions using Solexa sequencing. We then examined the expression pattern of the protein-coding genes under these two conditions with Affymetrix Zebrafish Genome Array profiling. The potential roles of the microRNAome in the transcriptomic cold regulation in the zebrafish brain were investigated by various statistical analyses. Results Among the total 214 unique, mature zebrafish miRNAs deposited on the miRBase website (release 16), 175 were recovered in this study. In addition, we identified 399 novel, mature miRNAs using multiple miRNA prediction methods. We defined a set of 25 miRNAs differentially expressed under the cold and normal conditions and predicted the molecular functions and biological processes that they involve through Gene Ontology (GO) annotation of their target genes. On the other hand, microarray analysis showed that genes related to mRNA processing and response to stress were overrepresented among the up-regulated genes in cold-stress, but are not directly corresponding to any of the GO molecular functions and biological processes predicted from the differential miRNAs. Using several statistical models including a novel, network-based approach, we found that miRNAs identified in this study, either individually or together, and either directly or indirectly (i.e., mediated by transcription factors), only make minor contribution to the change in gene expression patterns under the low-temperature condition. Conclusions Our results suggest that the cold-stress response of mRNA expression may be governed mainly through regulatory modes other than miRNA-mediated regulation. MiRNAs in animal brains might act more as developmental regulators than thermal adaptability regulators.

CpG islands (CGIs) are clusters of CpG dinucleotides in GC-rich regions and represent an important gene feature of mammalian genomes. Several algorithms have been developed to identify CGIs. Here we applied Support Vector Machine (SVM), a machine learning approach, to classify CGIs that are associated with the promoter regions of genes. We demonstrated that our SVM-based algorithm had much higher sensitivity and specificity in classifying promoter-associated CGIs than other algorithms, and had high reliability. The advantages of SVM in our method and future improvements were discussed.