Single Endemic Genotype of Measles Virus Continuously Circulating in China for at Least 16 Years

The incidence of measles in China from 1991 to 2008 was reviewed, and the nucleotide sequences from 1507 measles viruses (MeV) isolated during 1993 to 2008 were phylogenetically analyzed. The results showed that measles epidemics peaked approximately every 3 to 5 years with the range of measles cases detected between 56,850 and 140,048 per year. The Chinese MeV strains represented three genotypes; 1501 H1, 1 H2 and 5 A. Genotype H1 was the predominant genotype throughout China continuously circulating for at least 16 years. Genotype H1 sequences could be divided into two distinct clusters, H1a and H1b. A 4.2% average nucleotide divergence was found between the H1a and H1b clusters, and the nucleotide sequence and predicted amino acid homologies of H1a viruses were 92.3%–100% and 84.7%–100%, H1b were 97.1%–100% and 95.3%–100%, respectively. Viruses from both clusters were distributed throughout China with no apparent geographic restriction and multiple co-circulating lineages were present in many provinces. Cluster H1a and H1b viruses were co-circulating during 1993 to 2005, while no H1b viruses were detected after 2005 and the transmission of that cluster has presumably been interrupted. Analysis of the nucleotide and predicted amino acid changes in the N proteins of H1a and H1b viruses showed no evidence of selective pressure. This study investigated the genotype and cluster distribution of MeV in China over a 16-year period to establish a genetic baseline before MeV elimination in Western Pacific Region (WPR). Continuous and extensive MeV surveillance and the ability to quickly identify imported cases of measles will become more critical as measles elimination goals are achieved in China in the near future. This is the first report that a single endemic genotype of measles virus has been found to be continuously circulating in one country for at least 16 years

Low-temperature pretreatment by AlCl3-catalyzed 1,4-butanediol solution for producing ‘ideal’ lignin with super-high content of β-O-4 linkages

High contents of internal β-O-4 linkages in lignin are critical for high-yield production of high-value aromatic monomers by depolymerization. However, it remains great challenge due to lack of suitable protection strategy. In this work, a very effective lignin-first strategy was developed to produce ideal lignin with a super high content of β-O-4 linkages (up to 72 %) from poplar, in which the pretreatment was undertaken at low temperatures of 90–130 °C with the use of AlCl3-catalyzed 1, 4-butanediol solution. 2D-HSQC NMR spectra revealed that lignin β-O-4 linkages were protected from etherification of the OH group by 1, 4-butanediol at the α position of lignin aliphatic chains. Besides, the OH groups at the γ position of lignin was also etherified, leading the formation of a structure of Ph-CH=CHCH2O(CH2)4OH. Interestingly, structure protection facilitated the formation of lignin nanoparticles via self-assembly (<100 nm). In addition, it was observed from pyrolysis results that addition of 1, 4-butanediol remarkably protected the structure of lignin by avoiding condensation, promoting the production of aromatics. The cellulose-rich fraction possessed a high cellulose digestibility of 91.64 % by enzymatic hydrolysis at a cellulase dosage of 15 FPU/g cellulose, approximately 6-fold untreated poplar (15.91 %). This low-temperature lignin-first strategy was of great importance for multi-products biorefining lignocellulose because it leads to the production of both lignin with super high content of β-O-4 linkages for depolymerization and highly digestible cellulose for sugar production.</p

Joint Decision Model of Group Ticket Booking Limits and Individual Passenger Dynamic Pricing for the High-Speed Railway

Rail operators in many countries discount group tickets to improve revenue by increasing price-driven demand. For individual passengers, dynamic pricing is beneficial for maximizing revenue based on the price discrimination principle. Usually, group fares are cheaper than individual fares. If too many group tickets are sold, there will not be enough tickets available to meet high-priced individual demand; by contrast, if not enough group tickets are sold and there is insufficient individual demand, the unsold seats will not have value once the train departs. Therefore, for railway operators, it is worth looking for a balance between group discounts and dynamic pricing to maximize benefits. Essentially, rail operators need to find the symmetry point of the expected revenue between accepting group bookings and reserving tickets for individuals when making decisions. In this study, we formulated a joint decision model of group ticket booking control and dynamic pricing and investigated the effect of the joint decision. The results of numerical experiments showed that incorporating group discounts into dynamic pricing can improve expected revenue when passenger demand is weak, and compared to setting fixed quantities for group tickets, dynamically controlling the limit of group bookings can effectively increase expected revenue. Further analysis of the impacts of time, number of tickets sold, and group demand was helpful to implement the proposed joint policy

iTopic: influential topic discovery from information networks via keyword query

The rapid growth of information networks provides a significant opportunity for people to learn the world and find useful information for decision making. To find influential topics in a given context, instead of searching widely over the whole information network, normally it is wise to find the related communities first and then identify the influential topics in those communities. In this demonstration, we present a novel framework to compute the correlated sub-networks from a large information network such as CiteSeerX based on a user’s keyword query, and to extract the influential topics from each correlated network. To help users understand the influential topics as a whole, we utilize a word cloud to represent the discovered topics for each correlated network. As such, multiple word clouds can be generated for different correlated networks, by which users can easily pick up their interested ones by reading the visualized topic descriptions over word clouds. To determine the sizes of different terms in a word cloud, we introduce a scoring scheme for assessing the influence of these terms in the corresponding networks. We demonstrate the functionality of our influential topic system, called iTopic, using the CiteSeerX information network data

Intra- and Interrater Reliability of Infrared Image Analysis of Facial Acupoints in Individuals with Facial Paralysis

Infrared thermography (IRT), as a noncontact tool for temperature measurement, is widely applied in the study of acupuncture modernization. The aim of this study was to assess the intra- and interrater reliability of infrared image analysis of facial acupoints of subjects with facial paralysis and determine the factors influencing the variability of the measured values. A total of 26 patients with facial paralysis on one side, aged 26 to 53 years, participated voluntarily in the study. Facial infrared thermal images of all participants were analyzed by two trained raters at two different time points at a one-week interval. The intraclass correlation coefficient (ICC) was used to determine the intra- and interrater reliability of IRT measurements. The ICC values varied depending on the analyzed acupoints. The reliability of temperature measurement ranged from moderate to excellent (intrarater, ICC ranged from 0.669 to 0.990; interrater, ICC ranged from 0.661 to 0.987). The reliability of temperature difference measurement ranged from low to excellent (intrarater, ICC ranged from 0.412 to 0.882; interrater, ICC ranged from 0.334 to 0.828). The main influencing factor of reliability is the incomplete consistency in selecting acupoint positions when repeatedly positioning the same acupoint manually. Despite low reliability of temperature difference measurement at some acupoints, some auxiliary measures can be used to reduce the error of manual positioning. Thus, infrared thermal imaging still has the potential to assist in objective and quantitative research on acupuncture

iTopic: influential topic discovery from information networks via keyword query

The rapid growth of information networks provides a significant opportunity for people to learn the world and find useful information for decision making. To find influential topics in a given context, instead of searching widely over the whole information network, normally it is wise to find the related communities first and then identify the influential topics in those communities. In this demonstration, we present a novel framework to compute the correlated sub-networks from a large information network such as CiteSeerX based on a user’s keyword query, and to extract the influential topics from each correlated network. To help users understand the influential topics as a whole, we utilize a word cloud to represent the discovered topics for each correlated network. As such, multiple word clouds can be generated for different correlated networks, by which users can easily pick up their interested ones by reading the visualized topic descriptions over word clouds. To determine the sizes of different terms in a word cloud, we introduce a scoring scheme for assessing the influence of these terms in the corresponding networks. We demonstrate the functionality of our influential topic system, called iTopic, using the CiteSeerX information network data

Chemical constituents from the rhizome of Acorus tatarinowii Schott and their anti-inflammatory activities in LPS induced PC12 cells

Introduction: Acorus tatarinowii Schott is a traditional Chinese medicine that aromatizes dampness, opens the body and pacifies the mind, and is used medicinally as the dried rhizome of Acorus tatarinowii, family Tenaxaceae. Research has confirmed that it has a strong anti-inflammatory activity, however, its mechanism of anti-inflammatory is still unclear, and we continue to investigate its chemical composition and anti-inflammatory mechanism. Methods: The separation and purification of the EtOH extract was carried out by preparative thin layer chromatography and column chromatography. The structures of the isolated compounds were identified by NMR spectroscopy and comparing their spectral data with those previously reported in literature. CCK-8 method was used to evaluate the anti-inflammatory activity of all compounds. The MDA, NO, SOD, IL-10, IL-1β, IL-6 and TNF-α levels were analyzed using ELISA kits. TNF-α and Beclin-1 expression were examined by western blot and immunofluorescence. Results: Ten compounds, named cinnamic acid(1), sinapic acid(2), isoferulic acid(3), α-asarone(4), ferulic acid(5), arbutin (6), caffeic acid (7), 3-(3-hydroxyl phenyl)propanol(8), ethyl caffeate(9) and β-asarone(10) were isolated from the rhizome of Acorus tatarinowii Schott. Their structures were elucidated on the basis of extensive spectroscopic analyses, as well as by comparison with literature data. The anti-inflammatory effects of the all compounds were evaluated in lipopolysaccharide(LPS)-induced PC12 cell models in our study. The results of activity test showed that compounds 3 and 6 had good inhibitory effects on 5 μg·mL−1 LPS-induced PC12 cells. The IC50 of compounds 3 and 6 against PC12 cells were 27.41 ± 0.09 µmol·L−1 and 30.19 ± 0.10 µmol·L−1, respectively. Moreover, compounds 3 and 6 showed a significant protective effect on inflammation by increasing the IL-10 and SOD levels, and reducing the TNF-α, IL-6, IL-1β, MDA and NO levels. The most important point is that their anti-inflammatory effect is related to the autophagy factor Beclin-1. Conclusion: These findings imply that compounds 3 and 6 exerts anti-inflammatory effects by regulating TNF-α/Beclin-1 pathway, which provide a new basis for the anti-inflammatory activity of Acorus tatarinowii Schott