Quantitative evaluation of the proposed methods by comparison to manual segmentation.

<p>‘SM1’ and ‘RM1’ represents the comparison of the automatic segmentation by SVM and RF with the manual segmentation (M1), respectively. ‘M1M3’ compares the manual segmentations of two independent experts. ‘M1M2’ compares two manual segmentation repetitions of one expert. (A) Dice similarity coefficient. (B) False positive ratio. (C) False negative ratio. (* Indicates <i>p</i> < 0.05.)</p

Flow chart of the image segmentation scheme.

<p>The proposed segmentation algorithm includes five consecutive steps: DCE micro-CT images acquisition, data dimension reduction, supervoxel generation, supervoxel classification, and target organs’ extraction.</p

Influence of the number of training samples on segmentation accuracy.

<p>10%, 30%, 50%, 70%, and 90% of the total samples of each category were selected randomly from the total data set and consisted of training sets for classification. Each case was repeated five times. The means and standard deviations of Dice similarity coefficients for the heart, liver, spleen, lung, and kidney were calculated (compared with M1). (A) The DSC of the organs classified by SVM. (B) The DSC of the organs classified by RF. For the lung, one value at 10% and two values at 30% were excluded from statistics because it failed to extract the lung by post-processing.</p

Visual comparison of the segmentation results with the reference datasets, shown in 3-D isosurface rendering.

<p>Left column: left lateral view. Right column: posterior view. Top row: manual segmentation (M1). Middle row: segmentation obtained by the SVM. Bottom row: segmentation obtained by the RF.</p

Dynamic contrast enhancement procedure after contrast agent administration.

<p>(A) Representative coronal micro-CT images before contrast agent injection and at 0 s, 50 s, 100 s, 150 s, and 200 s post-contrast injection. The image at 0 s was acquired during the inflow of contrast agent. All of the images are displayed with the same gray scale window. (B) The relative signal enhancement versus time curves of regions depicted by the arrows in (A) with the same colors.</p

Number of supervoxels for each category chosen to constitute the total data set.

<p>Number of supervoxels for each category chosen to constitute the total data set.</p

Visual comparison of the segmentation results with the reference datasets, shown in 2-D images.

<p>The organ boundaries of manual segmentation (M1) and automatic segmentation based on the SVM and the RF are superimposed on two coronal images (A, B) and two sagittal images (C, D).</p

Real-Time Monitoring of Translocation, Dissipation, and Cumulative Risk of Maleic Hydrazide in Potato Plants and Tubers by Ion Exclusion Chromatography

In this paper, a high-performance ion exclusion chromatographic (ICE) method was developed and applied for monitoring maleic hydrazide (MH) translocation in complex potato plant tissue and tuber matrices. After middle leaf uptake, most MH was trapped and dissipated in the middle leaf, and the rest was transported to other parts mainly through the phloem. Soil absorption significantly reduced the uptake efficiency of the root system, in which MH was partitioned to dissipate in root protoplasts or transfer through the xylem and persisted in the plant. Tuber uptake enabled MH to remain in the flesh and maintain stable levels under storage conditions, but during germination, MH was translocated from the flesh to the growing buds, where it dissipated through the short-day photoperiodic regime. The results demonstrated successful application of the ICE method and provided necessary insights for real-time monitoring of MH translocation behavior to effectively improve potato edible safety

Two Genotypes of Coxsackievirus A2 Associated with Hand, Foot, and Mouth Disease Circulating in China since 2008

<div><p>Coxsackievirus A2 (CV-A2) has been frequently detected and commonly associated with hand, foot, and mouth disease (HFMD) in China since 2008. However, limited sequences of CV-A2 are currently available. As a result, we have been focusing on the genetic characteristics of CV-A2 in the mainland of China during 2008–2015 based on national HFMD surveillance. In this study, 20 CV-A2 strains were isolated and phylogenetic analyses of the <i>VP1</i> sequences were performed. Full-length genome sequences of two representative CV-A2 isolates were acquired and similarity plot and bootscanning analyses were performed. The phylogenetic dendrogram indicated that all CV-A2 strains could be divided into four genotypes (Genotypes A–D). The CV-A2 prototype strain (Fleetwood) was the sole member of genotype A. From 2008 to 2015, the CV-A2 strains isolated in China dispersed into two different genotypes (B and D). And the genotype D became the dominant circulating strains in China. Strains isolated in Russia and India from 2005 to 2011 converged into genotype C. Intertypic recombination occurred between the Chinese CV-A2 strains and other enterovirus-A donor sequences. This result reconfirmed that recombination is a common phenomenon among enteroviruses. This study helps expand the numbers of whole virus genome sequence and entire <i>VP1</i> sequence of CV-A2 in the GenBank database for further researcher.</p></div

The nucleotide sequence and deduced amino acid sequence identities between two CV-A2 strains (BJ13-53 and HeN13-6) and prototype EV-A strains.

<p>The nucleotide sequence and deduced amino acid sequence identities between two CV-A2 strains (BJ13-53 and HeN13-6) and prototype EV-A strains.</p