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"Chen, Ping"
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Viral Metagenomics Revealed Sendai Virus and Coronavirus Infection of Malayan Pangolins (Manis javanica)
Pangolins are endangered animals in urgent need of protection. Identifying and cataloguing the viruses carried by pangolins is a logical approach to evaluate the range of potential pathogens and help with conservation. This study provides insight into viral communities of Malayan Pangolins (Manis javanica) as well as the molecular epidemiology of dominant pathogenic viruses between Malayan Pangolin and other hosts. A total of 62,508 de novo assembled contigs were constructed, and a BLAST search revealed 3600 ones (≥300 nt) were related to viral sequences, of which 68 contigs had a high level of sequence similarity to known viruses, while dominant viruses were the Sendai virus and Coronavirus. This is the first report on the viral diversity of pangolins, expanding our understanding of the virome in endangered species, and providing insight into the overall diversity of viruses that may be capable of directly or indirectly crossing over into other mammals.
Journal Article
Mid-level visual features underlie the high-level categorical organization of the ventral stream
Human object-selective cortex shows a large-scale organization characterized by the high-level properties of both animacy and object size. To what extent are these neural responses explained by primitive perceptual features that distinguish animals from objects and big objects from small objects? To address this question, we used a texture synthesis algorithm to create a class of stimuli—texforms—which preserve some mid-level texture and form information from objects while rendering them unrecognizable. We found that unrecognizable texforms were sufficient to elicit the large-scale organizations of object-selective cortex along the entire ventral pathway. Further, the structure in the neural patterns elicited by texforms was well predicted by curvature features and by intermediate layers of a deep convolutional neural network, supporting the mid-level nature of the representations. These results provide clear evidence that a substantial portion of ventral stream organization can be accounted for by coarse texture and form information without requiring explicit recognition of intact objects.
Journal Article
Dietary Fiber and Metabolic Syndrome: A Meta-Analysis and Review of Related Mechanisms
(1) Background: Dietary fiber intake may provide beneficial effects on the components of metabolic syndrome (MetS); however, observational studies reported inconsistent results for the relationship between dietary fiber intake and MetS risk. We conducted a meta-analysis to quantify previous observational studies and a narrative review to summarize mechanisms involved in the potential relationship. (2) Methods: The literature was searched on PubMed and Web of Science until 28 November 2017. A random-effects model was used to calculate the summary risk estimates. Eleven cross-sectional studies and three cohort studies were included in the meta-analysis. Results from the original studies were reported as odds ratios (ORs) or relative ratios (RRs) of the MetS associated with different levels of dietary fiber intake, and the ORs/RRs comparing the highest with lowest categories of the intake were pooled. (3) Results: For the cross-sectional studies, the pooled OR was 0.70 (95% confidence interval (CI): 0.61–0.82) with evidence of high heterogeneity (I2 = 74.4%, p < 0.001) and publication bias (p for Egger’s test < 0.001). After removing four studies, results remained significant (OR = 0.67, 95% CI: 0.58–0.78) and the heterogeneity was largely reduced (I2 = 32.4%, p = 0.181). For the cohort studies, the pooled RR was 0.86 (95% CI: 0.70–1.06). (4) Conclusion: Although the meta-analysis suggests an inverse association between dietary fiber intake and risk of MetS, and the association was supported by a wide range of mechanism studies, the findings are limited by insufficient cohort data. More prospective studies are needed to further verify the association between dietary fiber intake and the risk of MetS.
Journal Article
Translation and cross-cultural communication studies in the Asia Pacific
Translation and interpreting (T/I) and cross-cultural communication activities in the Asia Pacific are unique in that they involve vastly different languages and cultures. Such differences pose challenges for T/I practitioners and researchers as well as scholars of cross-cultural studies. In this book, Leong Ko and Ping Chen provide a comprehensive and in-depth account of various issues encountered in translation and interpreting activities and cross-cultural communication in the Asia Pacific. 0The book covers six areas including translation research from the historical perspective and different issues in translation studies; research on literary translation; studies on translation for special purposes; research on interpreting; translation and interpreting training; and research on issues in cross-cultural communication.
Book
Mechanical shear flow regulates the malignancy of colorectal cancer cells
Colorectal cancer (CRC) is notable for its high mortality and high metastatic characteristics. The shear force generated by bloodstream provides mechanical signals regulating multiple responses of cells, including metastatic cancer cells, dispersing in blood vessels. We, therefore, studied the effect of shear flow on circulating CRC cells in the present study. The CRC cell line SW620 was subjected to shear flow of 12.5 dynes/cm2 for 1 and 2 h separately. Resulting elevated caspase‐9 and ‐3 indicated that shear flow initiated the apoptosis of SW620. Enlarged cell size associated with a higher level of cyclin D1 was coincident with the flow cytometric results indicating that the cell cycle was arrested at the G1 phase. An elevated phosphor‐eNOSS1177 increased the production of nitric oxide and led to reactive oxygen species‐mediated oxidative stress. Shear flow also regulated epithelial–mesenchymal transition (EMT) by increasing E‐cadherin and ZO‐1 while decreasing Snail and Twist1. The migration and invasion of sheared SW620 were also substantially decreased. Further investigations showed that mitochondrial membrane potential was significantly decreased, whereas mitochondrial mass and ATP production were not changed. In addition to the shear flow of 12.5 dynes/cm2, the expressions of EMT were compared at lower (6.25 dynes/cm2) and at higher (25 dynes/cm2) shear flow. The results showed that lower shear flow increased mesenchymal characteristics and higher shear flow increased epithelial characteristics. Shear flow reduces the malignancy of CRC in their metastatic dispersal that opens up new ways to improve cancer therapies by applying a mechanical shear flow device.
Journal Article
Automated bone mineral density prediction and fracture risk assessment using plain radiographs via deep learning
Dual-energy X-ray absorptiometry (DXA) is underutilized to measure bone mineral density (BMD) and evaluate fracture risk. We present an automated tool to identify fractures, predict BMD, and evaluate fracture risk using plain radiographs. The tool performance is evaluated on 5164 and 18175 patients with pelvis/lumbar spine radiographs and Hologic DXA. The model is well calibrated with minimal bias in the hip (slope = 0.982, calibration-in-the-large = −0.003) and the lumbar spine BMD (slope = 0.978, calibration-in-the-large = 0.003). The area under the precision-recall curve and accuracy are 0.89 and 91.7% for hip osteoporosis, 0.89 and 86.2% for spine osteoporosis, 0.83 and 95.0% for high 10-year major fracture risk, and 0.96 and 90.0% for high hip fracture risk. The tool classifies 5206 (84.8%) patients with 95% positive or negative predictive value for osteoporosis, compared to 3008 DXA conducted at the same study period. This automated tool may help identify high-risk patients for osteoporosis.
Dual-energy X-ray absorptiometry and the Fracture Risk Assessment Tool are recommended tools for osteoporotic fracture risk evaluation, but are underutilized. Here, the authors present an opportunistic tool to identify fractures, predict bone mineral density and evaluate fracture risk using plain pelvis and lumbar spine radiographs.
Journal Article
Reliability evaluation and big data analytics architecture for a stochastic flow network with time attribute
A network with multi-state (stochastic) elements (arcs or nodes) is commonly called a stochastic flow network. It is important to measure the system reliability of a stochastic flow network from the perspective of operations management. In the real world, the system reliability of a stochastic flow network can vary over time. Hence, a critical issue emerges—characterizing the time attribute in a stochastic flow network. To solve this issue, this study bridges (classical) reliability theory and the reliability of a stochastic flow network. This study utilizes Weibull distribution as a possible reliability function to quantify the time attribute in a stochastic flow network. For more general cases, the proposed model and algorithm can apply any reliability function and is not limited to Weibull distribution. First, the reliability of every single component is modeled by Weibull distribution to consider the time attribute, where such components comprise a multi-state element. Once the time constraint is given, the capacity probability distribution of elements can be derived. Second, an algorithm to generate minimal component vectors for given demand is provided. Finally, the system reliability can be calculated in terms of the derived capacity probability distribution and the generated minimal component vectors. In addition, a big data architecture is proposed for the model to collect and estimate the parameters of the reliability function. For future research in which very large volumes of data may be collected, the proposed model and architecture can be applied to time-dependent monitoring.
Journal Article