BackgroundPlants have evolved multifaceted defence mechanisms to resist pathogen infection. Production of the pathogenesis-related (PR) proteins in response to pathogen attack has been implicated in plant disease resistance specialized in systemic-acquired resistance (SAR). Our earlier studies have reported that a full length TaLr35PR5 gene, encoding a protein exhibiting amino acid and structural similarity to a sweet protein thaumatin, was isolated from wheat near-isogenic line TcLr35. The present study aims to understand the function of TaLr35PR5 gene in Lr35-mediated adult resistance to Puccinia triticina.ResultsWe determined that the TaLr35PR5 protein contained a functional secretion peptide by utilizing the yeast signal sequence trap system. Using a heterologous expression assay on onion epidermal cells we found that TaLr35PR5 protein was secreted into the apoplast of onion cell. Expression of TaLr35PR5 was significantly reduced in BSMV-induced gene silenced wheat plants, and pathology test on these silenced plants revealed that Lr35-mediated resistance phenotype was obviously altered, indicating that Lr35-mediated resistance was compromised.ConclusionsAll these findings strongly suggest that TaLr35PR5 is involved in Lr35-mediated adult wheat defense in response to leaf rust attack.Electronic supplementary materialThe online version of this article (10.1186/s12870-018-1297-2) contains supplementary material, which is available to authorized users.

Disease progression prediction and therapeutic drug target discovery for Coronavirus disease 2019 (COVID-19) are particularly important, as there is still no effective strategy for severe COVID-19 patient treatment. Herein, we performed multi-platform omics analysis of serial plasma and urine samples collected from patients during the course of COVID-19. Integrative analyses of these omics data revealed several potential therapeutic targets, such as ANXA1 and CLEC3B. Molecular changes in plasma indicated dysregulation of macrophage and suppression of T cell functions in severe patients compared to those in non-severe patients. Further, we chose 25 important molecular signatures as potential biomarkers for the prediction of disease severity. The prediction power was validated using corresponding urine samples and plasma samples from new COVID-19 patient cohort, with AUC reached to 0.904 and 0.988, respectively. In conclusion, our omics data proposed not only potential therapeutic targets, but also biomarkers for understanding the pathogenesis of severe COVID-19.

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Cataracts, which are lenticular opacities that may occur at different lens locations, are the leading cause of visual impairment worldwide. Accurate and timely diagnosis can improve the quality of life of cataract patients. In this paper, a feature extraction-based method for grading cataract severity using retinal images is proposed. To obtain more appropriate features for the automatic grading, the Haar wavelet is improved according to the characteristics of retinal images. Retinal images of non-cataract, as well as mild, moderate, and severe cataracts, are automatically recognized using the improved Haar wavelet. A hierarchical strategy is used to transform the four-class classification problem into three adjacent two-class classification problems. Three sets of two-class classifiers based on a neural network are trained individually and integrated together to establish a complete classification system. The accuracies of the two-class classification (cataract and non-cataract) and four-class classification are 94.83% and 85.98%, respectively.The performance analysis demonstrates that the improved Haar wavelet feature achieves higher accuracy than the original Haar wavelet feature, and the fusion of three sets of two-class classifiers is superior to a simple four-class classifier. The discussion indicates that the retinal image-based method offers significant potential for cataract detection.

Cephalometric analysis is a standard tool for assessment and prediction of craniofacial growth, orthodontic diagnosis, and oral-maxillofacial treatment planning. The aim of this study is to develop a fully automatic system of cephalometric analysis, including cephalometric landmark detection and cephalometric measurement in lateral cephalograms for malformation classification and assessment of dental growth and soft tissue profile. First, a novel method of multiscale decision tree regression voting using SIFT-based patch features is proposed for automatic landmark detection in lateral cephalometric radiographs. Then, some clinical measurements are calculated by using the detected landmark positions. Finally, two databases are tested in this study: one is the benchmark database of 300 lateral cephalograms from 2015 ISBI Challenge, and the other is our own database of 165 lateral cephalograms. Experimental results show that the performance of our proposed method is satisfactory for landmark detection and measurement analysis in lateral cephalograms.

Understanding the mechanisms of plant salinity tolerance can facilitate plant engineering for enhanced salt stress tolerance. Sugar beet monosomic addition line M14 obtained from the intercross between Beta vulgaris L. and Beta corolliflora Zoss exhibits tolerance to salt stress. Here we report the salt-responsive characteristics of the M14 plants under 0, 200, and 400 mM NaCl conditions using quantitative proteomics approaches. Proteins from control and the salt treated M14 plants were separated using 2D-DIGE. Eighty-six protein spots representing 67 unique proteins in leaves and 22 protein spots representing 22 unique proteins in roots were identified. In addition, iTRAQ LC-MS/MS was employed to identify and quantify differentially expressed proteins under salt stress. Seventy-five differentially expressed proteins in leaves and 43 differentially expressed proteins in roots were identified. The proteins were mainly involved in photosynthesis, energy, metabolism, protein folding and degradation, and stress and defense. Moreover, gene transcription data obtained from the same samples were compared to the corresponding protein data. Thirteen proteins in leaves and 12 in roots showed significant correlation in gene expression and protein levels. These results suggest the important processes for the M14 tolerance to salt stress include enhancement of photosynthesis and energy metabolism, accumulation of osmolyte and antioxidant enzymes, and regulation of methionine metabolism and ion uptake/exclusion.

Simultaneous Localization And Mapping (SLAM) is the problem of constructing or updating a map of an unknown environment while simultaneously keeping track of an agent's location within it. How to enable SLAM robustly and durably on mobile, or even IoT grade devices, is the main challenge faced by the industry today. The main problems we need to address are: 1.) how to accelerate the SLAM pipeline to meet real-time requirements; and 2.) how to reduce SLAM energy consumption to extend battery life. After delving into the problem, we found out that feature extraction is indeed the bottleneck of performance and energy consumption. Hence, in this paper, we design, implement, and evaluate a hardware ORB feature extractor and prove that our design is a great balance between performance and energy consumption compared with ARM Krait and Intel Core i5.

Pathogenesis-related (PR) proteins encoded by plant defense genes play key roles in plant disease-resistance responses, specialized in systemic-acquired resistance. However, their roles in the response of wheat to fungal infection are still not well known. Our earlier studies have reported that a full-length TcLr19PR1 gene (818 bp) was isolated from wheat infected by leaf rust (Puccinia triticina). Here, we showed that TcLr19PR1 was induced earlier and its expression level was higher in the incompatible interaction between seedling stage of wheat and P. triticina than in compatible interactions. TcLr19PR1 was strongly induced after P. triticina inoculation and ABA and SA treatments, in which the expression level of TcLr19PR1 significantly increased and reached the maximum at 12 and 72 h, respectively. Furthermore, the transgenic T 1 -stable TcLr19PR1 lines generated in the susceptible wheat cultivar Zhengzhou 5389 background exhibited certain extent disease resistance against P. triticina infection by preventing disease development. In addition, Western blotting was conducted to confirm that TcLr19PR1 protein was induced by P. triticina infection in positive transgenic plants at the protein expression level. These findings suggest that TcLr19PR1 gene plays an important role in wheat development and resistance to leaf rust pathogen attack.