32 research outputs found

    LncRNA-Disease Association Prediction Using Two-Side Sparse Self-Representation

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    Evidences increasingly indicate the involvement of long non-coding RNAs (lncRNAs) in various biological processes. As the mutations and abnormalities of lncRNAs are closely related to the progression of complex diseases, the identification of lncRNA-disease associations has become an important step toward the understanding and treatment of diseases. Since only a limited number of lncRNA-disease associations have been validated, an increasing number of computational approaches have been developed for predicting potential lncRNA-disease associations. However, how to predict potential associations precisely through computational approaches remains challenging. In this study, we propose a novel two-side sparse self-representation (TSSR) algorithm for lncRNA-disease association prediction. By learning the self-representations of lncRNAs and diseases from known lncRNA-disease associations adaptively, and leveraging the information provided by known lncRNA-disease associations and the intra-associations among lncRNAs and diseases derived from other existing databases, our model could effectively utilize the estimated representations of lncRNAs and diseases to predict potential lncRNA-disease associations. The experiment results on three real data sets demonstrate that our TSSR outperforms other competing methods significantly. Moreover, to further evaluate the effectiveness of TSSR in predicting potential lncRNAs-disease associations, case studies of Melanoma, Glioblastoma, and Glioma are carried out in this paper. The results demonstrate that TSSR can effectively identify some candidate lncRNAs associated with these three diseases

    RepLong - de novo repeat identification using long read sequencing data

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    Abstract Motivation The identification of repetitive elements is important in genome assembly and phylogenetic analyses. The existing de novo repeat identification methods exploiting the use of short reads are impotent in identifying long repeats. Since long reads are more likely to cover repeat regions completely, using long reads is more favorable for recognizing long repeats. Results In this study, we propose a novel de novo repeat elements identification method namely RepLong based on PacBio long reads. Given that the reads mapped to the repeat regions are highly overlapped with each other, the identification of repeat elements is equivalent to the discovery of consensus overlaps between reads, which can be further cast into a community detection problem in the network of read overlaps. In RepLong, we first construct a network of read overlaps based on pair-wise alignment of the reads, where each vertex indicates a read and an edge indicates a substantial overlap between the corresponding two reads. Secondly, the communities whose intra connectivity is greater than the inter connectivity are extracted based on network modularity optimization. Finally, representative reads in each community are extracted to form the repeat library. Comparison studies on Drosophila melanogaster and human long read sequencing data with genome-based and short-read-based methods demonstrate the efficiency of RepLong in identifying long repeats. RepLong can handle lower coverage data and serve as a complementary solution to the existing methods to promote the repeat identification performance on long-read sequencing data. Availability and implementation The software of RepLong is freely available at https://github.com/ruiguo-bio/replong. Supplementary information Supplementary data are available at Bioinformatics online. </jats:sec

    Characterization of the Nucleocytoplasmic Transport Mechanisms of Epstein-Barr Virus BFLF2

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    Background/Aims: Epstein-Barr virus (EBV) BFLF2, the homologue of herpes simplex virus 1 (HSV-1) UL31, is crucial for the efficient viral DNA packaging and primary egress across the nuclear membrane. However, we still do not know its subcellular transport mechanisms. Methods: Interspecies heterokaryon assays were utilized to detect the nucleocytoplasmic shuttling of BFLF2, and mutation analysis, plasmid transfection and fluorescence microscopy assays were performed to identify the functional nuclear localization sequence (NLS) and nuclear export sequence (NES) of BFLF2 in live cells. Furthermore, the nuclear import and export of BFLF2 were assessed by confocal microscopy, co-immunoprecipitation and immunoblot assays. Results: BFLF2 was confirmed to shuttle between the nucleus and cytoplasm. Two predicted NESs were shown to be nonfunctional, yet we proved that the nuclear export of BFLF2 was mediated through transporter associated with antigen processing (TAP), but not chromosomal region maintenance 1 (CRM1) dependent pathway. Furthermore, one functional NLS, 22RRLMHPHHRNYTASKASAH40, was identified, and the aa22-23, aa22-25, aa28-30 and aa37-40 had an important role in the nuclear localization of BFLF2. Besides, the nuclear import of BFLF2 was demonstrated through Ran-, importin α7-, importin β1- and transportin-1-dependent mechanism that does not require importin α1, α3 and α5. Conclusion: These works are of significance for the further study of the functions of BFLF2 during EBV infection, as well as for further insights into the design of new antiviral drug target and vaccine development against EBV

    A study on the association between prefrontal functional connectivity and non-suicidal self-injury in adolescents with depression

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    ObjectiveAmong adolescents with depression, the occurrence of non-suicidal self-injury (NSSI) behavior is prevalent, constituting a high-risk factor for suicide. However, there has been limited research on the neuroimaging mechanisms underlying adolescent depression and NSSI behavior, and the potential association between the two remains unclear. Therefore, this study aims to investigate the alterations in functional connectivity (FC) of the regions in the prefrontal cortex with the whole brain, and elucidates the relationship between these alterations and NSSI behavior in adolescents with depression.MethodsA total of 68 participants were included in this study, including 35 adolescents with depression and 33 healthy controls. All participants underwent assessments using the 17-item Hamilton Depression Rating Scale (17-HAMD) and the Ottawa Self-Harm Inventory. In addition, functional magnetic resonance imaging (fMRI) data of the participants’ brains were collected. Subsequently, the FCs of the regions in the prefrontal cortex with the whole brain was calculated. The FCs showing significant differences were then subjected to correlation analyses with 17-HAMD scores and NSSI behavior scores.ResultCompared to the healthy control group, the adolescent depression group exhibited decreased FCs in several regions, including the right frontal eye field, left dorsolateral prefrontal cortex, right orbitofrontal cortex, left insula and right anterior cingulate coetex. The 17-HAMD score was positively correlated with the frequency of NSSI behavior within 1 year (rs = 0.461, p = 0.005). The FC between the right anterior cingulate cortex and the right precuneus showed a negative correlation with the 17-HAMD scores (rs = −0.401, p = 0.023). Additionally, the FC between the right orbitofrontal cortex and the right insula, demonstrated a negative correlation with the frequency of NSSI behavior within 1 year (rs = −0.438, p = 0.012, respectively).ConclusionAdolescents with depression showed decreased FCs of the prefrontal cortex with multiple brain regions, and some of these FCs were associated with the NSSI frequency within 1 year. This study provided neuroimaging evidence for the neurophysiological mechanisms underlying adolescent depression and its comorbidity with NSSI behavior

    Spatiotemporal Dynamics and Driving Forces of Land Urbanization in the Yangtze River Delta Urban Agglomeration

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    Land urbanization is a comprehensive mapping of the relationship between urban production, life and ecology in urban space and a spatial carrier for promoting the modernization of cities. Based on the remote sensing monitoring data of the land use status of the Yangtze River Delta urban agglomeration collected in 2010 and 2020, the spatial differentiation characteristics and influencing factors of land urbanization in the area were analyzed comprehensively using hot spot analysis, kernel density estimation, the multi-scale geographically weighted regression (MGWR) model and other methods. The results indicated the following: (1) From 2010 to 2020, the average annual growth rate of land urbanization in the Yangtze River Delta urban agglomeration was 0.50%, and nearly 64.28% of the counties had an average annual growth rate that lagged behind the overall growth rate. It exhibited dynamic convergence characteristics. (2) The differentiation pattern of land urbanization in the Yangtze River Delta urban agglomeration was obvious from the southeast to the northwest. The hot spots of land urbanization were consistently concentrated in the southeastern coastal areas and showed a trend of spreading, while the cold spots were concentrated in the northwest of Anhui Province, showing a shrinking trend. (3) Compared with the GWR model and the OLS model, the MGWR model has a better fitting effect and is more suitable for studying the influencing factors of land urbanization. In addition, there were significant spatial differences in the scale and degree of influence of different influencing factors. Analyzing and revealing the spatiotemporal characteristics and driving mechanism of land urbanization in the Yangtze River Delta urban agglomeration has important theoretical value and practical significance for the scientific understanding of new-type urbanization and the implementation of regional integration and rural revitalization strategies

    Continuous-Wave Fiber Cavity Ringdown Pressure Sensing Based on Frequency-Shifted Interferometry

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    We present a continuous-wave fiber cavity ringdown (FCRD) pressure-sensing method based on frequency-shifted interferometry (FSI). Compared with traditional CRD or FCRD techniques, this FSI-FCRD scheme deduces pressure by measuring the decay rate of continuous light exiting the fiber ringdown cavity (RDC) in the spatial domain (i.e., the CRD distance), without the requirement for optical pulsation and fast electronics. By using a section of fiber with the buffer layer stripped in the fiber RDC as the sensor head, pressures were measured within the range from 0 to 10.4 MPa. The sensitivity of 0.02356/(km∙MPa) was obtained with a measurement error of 0.1%, and the corresponding pressure resolution was 0.05 MPa. It was found that the measurement sensitivity can be improved by enlarging the interaction length of the sensor head. The results show the proposed sensor has the advantages of simple structure, low cost, high sensitivity, and high stability in pressure detection

    Comparative transcriptome revealed the molecular responses of Aconitum carmichaelii Debx. to downy mildew at different stages of disease development

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    Abstract Background Aconitum carmichaelii Debx. has been widely used as a traditional medicinal herb for a long history in China. It is highly susceptible to various dangerous diseases during the cultivation process. Downy mildew is the most serious leaf disease of A. carmichaelii, affecting plant growth and ultimately leading to a reduction in yield. To better understand the response mechanism of A. carmichaelii leaves subjected to downy mildew, the contents of endogenous plant hormones as well as transcriptome sequencing were analyzed at five different infected stages. Results The content of 3-indoleacetic acid, abscisic acid, salicylic acid and jasmonic acid has changed significantly in A. carmichaelii leaves with the development of downy mildew, and related synthetic genes such as 9-cis-epoxycarotenoid dioxygenase and phenylalanine ammonia lyase were also significant for disease responses. The transcriptomic data indicated that the differentially expressed genes were primarily associated with plant hormone signal transduction, plant-pathogen interaction, the mitogen-activated protein kinase signaling pathway in plants, and phenylpropanoid biosynthesis. Many of these genes also showed potential functions for resisting downy mildew. Through weighted gene co-expression network analysis, the hub genes and genes that have high connectivity to them were identified, which could participate in plant immune responses. Conclusions In this study, we elucidated the response and potential genes of A. carmichaelii to downy mildew, and observed the changes of endogenous hormones content at different infection stages, so as to contribute to the further screening and identification of genes involved in the defense of downy mildew
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