58 research outputs found
Transcriptome profiling confirmed correlations between symptoms and transcriptional changes in RDV infected rice and revealed nucleolus as a possible target of RDV manipulation
High genetic homogeneity points to a single introduction event responsible for invasion of Cotton leaf curl Multan virus and its associated betasatellite into China
Identification of Pns6, a putative movement protein of RRSV, as a silencing suppressor
RNA silencing is a potent antiviral response in plants. As a counterdefense, most plant and some animal viruses encode RNA silencing suppressors. In this study, we showed that Pns6, a putative movement protein of Rice ragged stunt virus (RRSV), exhibited silencing suppressor activity in coinfiltration assays with the reporter green fluorescent protein (GFP) in transgenic Nicotiana benthamiana line 16c. Pns6 of RRSV suppressed local silencing induced by sense RNA but had no effect on that induced by dsRNA. Deletion of a region involved in RNA binding abolished the silencing suppressor activity of Pns6. Further, expression of Pns6 enhanced Potato virus × pathogenicity in N. benthamiana. Collectively, these results suggested that RRSV Pns6 functions as a virus suppressor of RNA silencing that targets an upstream step of the dsRNA formation in the RNA silencing pathway. This is the first silencing suppressor to be identified from the genus Oryzavirus
Variance Change Point Detection Under a Smoothly-Changing Mean Trend with Application to Liver Procurement
Literature on change point analysis mostly requires a sudden change in the data distribution, either in a few parameters or the distribution as a whole. We are interested in the scenario, where the variance of data may make a significant jump while the mean changes in a smooth fashion. The motivation is a liver procurement experiment monitoring organ surface temperature. Blindly applying the existing methods to the example can yield erroneous change point estimates since the smoothly changing mean violates the sudden-change assumption. We propose a penalized weighted least-squares approach with an iterative estimation procedure that integrates variance change point detection and smooth mean function estimation. The procedure starts with a consistent initial mean estimate ignoring the variance heterogeneity. Given the variance components the mean function is estimated by smoothing splines as the minimizer of the penalized weighted least squares. Given the mean function, we propose a likelihood ratio test statistic for identifying the variance change point. The null distribution of the test statistic is derived together with the rates of convergence of all the parameter estimates. Simulations show excellent performance of the proposed method. Application analysis offers numerical support to non invasive organ viability assessment by surface temperature monitoring. Supplementary materials for this article are available online
Electrochemical Biosensors for Detection of Foodborne Pathogens
Foodborne safety has become a global public health problem in both developed and developing countries. The rapid and precise monitoring and detection of foodborne pathogens has generated a strong interest by researchers in order to control and prevent human foodborne infections. Traditional methods for the detection of foodborne pathogens are often time-consuming, laborious, expensive, and unable to satisfy the demands of rapid food testing. Owing to the advantages of simplicity, real-time analysis, high sensitivity, miniaturization, rapid detection time, and low cost, electrochemical biosensing technology is more and more widely used in determination of foodborne pathogens. Here, we summarize recent developments in electrochemical biosensing technologies used to detect common foodborne pathogens. Additionally, we discuss research challenges and future prospects for this field of study
Electrochemical Sensors for Detection of Markers on Tumor Cells
In recent years, the increasing incidence and mortality of cancer have inspired the development of accurate and rapid early diagnosis methods in order to successfully cure cancer; however, conventional methods used for detecting tumor cells, including histopathological and immunological methods, often involve complex operation processes, high analytical costs, and high false positive rates, in addition to requiring experienced personnel. With the rapid emergence of sensing techniques, electrochemical cytosensors have attracted wide attention in the field of tumor cell detection because of their advantages, such as their high sensitivity, simple equipment, and low cost. These cytosensors are not only able to differentiate tumor cells from normal cells, but can also allow targeted protein detection of tumor cells. In this review, the research achievements of various electrochemical cytosensors for tumor cell detection reported in the past five years are reviewed, including the structures, detection ranges, and detection limits of the cytosensors. Certain trends and prospects related to the electrochemical cytosensors are also discussed
Design of real-time tracking monitoring and early warning system for coal mine groundwater
In order to improve hydrological monitoring of coal mine groundwater and water disaster prediction level, a real-time tracking monitoring and early warning system for coal mine groundwater based on intelligent water level meter was designed. The system uses metal probes of a water sensor to judge whether the intelligent water level meter is in aquifer, and downs the intelligent water level meter into water automatically when water level drops below the intelligent water lever meter, so as to avoid pseudo data. The system obtains water pressure data through a hydraulic sensor, and uses upper computer to fit and analyze the data, so as to calculate water level. The test results show that the system can run stably and early warn water level mutation of aquifer in 5 s, whose measurement error of water level is not more than 2 cm
How to Save your Annotation Cost for Panoptic Segmentation?
How to properly reduce the annotation cost for panoptic segmentation? How to leverage and optimize the cost-quality trade-off for training data and model? These questions are key challenges towards a label-efficient and scalable panoptic segmentation system due to its expensive instance/semantic pixel-level annotation requirements. By closely examining different kinds of cheaper labels, we introduce a novel multi-objective framework to automatically determine the allocation of different annotations, so as to reach a better segmentation quality with a lower annotation cost. Specifically, we design a Cost-Quality Balanced Network (CQB-Net) to generate the panoptic segmentation map, which distills the crucial relations between various supervisions including panoptic labels, image-level classification labels, bounding boxes, and the semantic coherence information between the foreground and background. Instead of ad-hoc allocation during training, we formulate the optimization of cost-quality trade-off as a Multi-Objective Optimization Problem (MOOP). We model the marginal quality improvement of each annotation and approximate the Pareto-front to enable a label-efficient allocation ratio. Extensive experiments on COCO benchmark show the superiority of our method, e.g. achieving a segmentation quality of 43.4% compared to 43.0% of OCFusion while saving 2.4x annotation cost
Bidirectional threshold switching characteristics in Ag/ZrO2/Pt electrochemical metallization cells
A bidirectional threshold switching (TS) characteristic was demonstrated in Ag/ZrO2/Pt electrochemical metallization cells by using the electrochemical active Ag electrode and appropriate programming operation strategies The volatile TS was stable and reproducible and the rectify ratio could be tuned to ∼107 by engineering the compliance current. We infer that the volatile behavior is essentially due to the moisture absorption in the electron beam evaporated films, which remarkably improved the anodic oxidation as well as the migration of Ag+ ions. The resultant electromotive force would act as a driving force for the metal filaments dissolution, leading to the spontaneous volatile characteristics. Moreover, conductance quantization behaviors were also achieved owing to formation and annihilation of atomic scale metal filaments in the film matrix. Our results illustrate that the Ag/ZrO2/Pt device with superior TS performances is a promising candidate for selector applications in passive crossbar arrays
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