Does Product Type Affect Electronic Word-of-Mouth Richness Effectiveness? Influences of Message Valence and Consumer Knowledge

Drawing on the information richness theory, this study attempts to address how valence of electronic word-of-mouth (eWOM), product type and consumer knowledge will yield different levels of eWOM richness. The results based on an experimental study suggest that negative eWOM has a stronger effect in producing eWOM information richness than does positive eWOM, and such effect is more pronounced for a leisure farm tour (experience goods) than for digital camera (search goods). The tendency that negative eWOM will provide richer information for the leisure farm tour is more evident for high-knowledge consumers than for low-knowledge consumers. The study’s results caution against the aggravated harm of negative eWOM incurred from the dissatisfactory experience of a leisure farm tour

T Oligo-Primed Polymerase Chain Reaction (TOP-PCR): A Robust Method for the Amplification of Minute DNA Fragments in Body Fluids.

Body fluid DNA sequencing is a powerful noninvasive approach for the diagnosis of genetic defects, infectious agents and diseases. The success relies on the quantity and quality of the DNA samples. However, numerous clinical samples are either at low quantity or of poor quality due to various reasons. To overcome these problems, we have developed T oligo-primed polymerase chain reaction (TOP-PCR) for full-length nonselective amplification of minute quantity of DNA fragments. TOP-PCR adopts homogeneous "half adaptor" (HA), generated by annealing P oligo (carrying a phosphate group at the 5' end) and T oligo (carrying a T-tail at the 3' end), for efficient ligation to target DNA and subsequent PCR amplification primed by the T oligo alone. Using DNA samples from body fluids, we demonstrate that TOP-PCR recovers minute DNA fragments and maintains the DNA size profile, while enhancing the major molecular populations. Our results also showed that TOP-PCR is a superior method for detecting apoptosis and outperforms the method adopted by Illumina for DNA amplification

A Study of Machine Learning Models in Epidemic Surveillance: Using the Query Logs of Search Engines

Epidemics inevitably result in a large number of deaths and always cause considerable social and economic damage. Epidemic surveillance has thus become an important healthcare research issue. In 2009, Ginsberg et al. observed that the query logs of search engines can be used to estimate the status of epidemics in a timely manner. In this paper, we model epidemic surveillance as a classification problem and employ query statistics from Google to classify the status of a dengue fever epidemic. The query logs of twenty-three dengue-related keywords serve as observations for machine learning and testing, and a number of machine learning models are investigated to evaluate their surveillance performance. Evaluations based on a 5-year real world dataset demonstrate that search engine query logs can be used to construct accurate epidemic status classifiers. Moreover, the learned classifiers generally outperform conventional regression approaches. We also apply various machine learning models, including generative, discriminative, sequential, and non-sequential classification models, to demonstrate their applicability to epidemic surveillance

Efficacy of a paper-based interleukin-6 test strip combined with a spectrum-based optical reader for sequential monitoring and early recognition of respiratory failure in elderly pneumonia—a pilot study

Introduction: Community-acquired pneumonia (CAP) is lethal in elderly individuals who are more vulnerable to respiratory failure and require more emergency ventilation support than younger individuals. Interleukin-6 (IL-6) plays a crucial role and has predictive value in CAP; high serum IL-6 concentrations in adults are associated with high respiratory failure and mortality rates. Early detection of IL-6 concentrations can facilitate the timely stratification of patients at risk of acute respiratory failure. However, conventional enzyme-linked immunosorbent assay (ELISA) IL-6 measurement is laborious and time-consuming.Methods: The IL-6 rapid diagnostic system combined with a lateral flow immunoassay-based (LFA-based) IL-6 test strip and a spectrum-based optical reader is a novel tool developed for rapid and sequential bedside measurements of serum IL-6 concentrations. Here, we evaluated the correlation between the IL-6 rapid diagnostic system and the ELISA and the efficacy of the system in stratifying high-risk elderly patients with CAP. Thirty-six elderly patients (median age: 86.5 years; range: 65–97 years) with CAP were enrolled. CAP diagnosis was established based on the Infectious Diseases Society of America (IDSA) criteria. The severity of pneumonia was assessed using the CURB-65 score and Pneumonia Severity Index (PSI). IL-6 concentration was measured twice within 24 h of admission.Results: The primary endpoint variable was respiratory failure requiring invasive mechanical or non-invasive ventilation support after admission. IL-6 rapid diagnostic readouts correlated with ELISA results (p < 0.0001) for 30 samples. Patients were predominantly male and bedridden (69.4%). Ten patients (27.7%) experienced respiratory failure during admission, and five (13.9%) died of pneumonia. Respiratory failure was associated with a higher mortality rate (p = 0.015). Decreased serum IL-6 concentration within 24 h after admission indicated a lower risk of developing respiratory failure in the later admission course (Receiver Operating Characteristic [ROC] curve = 0.696).Conclusion: Sequential IL-6 measurements with the IL-6 rapid diagnostic system might be useful in early clinical risk assessment and severity stratification of elderly patients with pneumonia. This system is a potential point-of-care diagnostic device for sequential serum IL-6 measurements that can be applied in variable healthcare systems

Determination of Nucleopolyhedrovirus’ Taxonomic Position

To date , over 78 genomes of nucleopolyhedroviruses (NPVs) have been sequenced and deposited in NCBI. How to define a new virus from the infected larvae in the field is usually the first question. Two NPV strains, which were isolated from casuarina moth (L. xylina) and golden birdwing larvae (Troides aeacus), respectively, displayed the same question. Due to the identity of polyhedrin (polh) sequences of these two isolates to that of Lymantria dispar MNPV and Bombyx mori NPV, they are named LdMNPV-like virus and TraeNPV, provisionally. To further clarify the relationships of LdMNPV-like virus and TraeNPV to closely related NPVs, Kimura 2-parameter (K-2-P) analysis was performed. Apparently, the results of K-2-P analysis that showed LdMNPV-like virus is an LdMNPV isolate, while TraeNPV had an ambiguous relationship to BmNPV. Otherwise, MaviNPV, which is a mini-AcMNPV, also exhibited a different story by K-2-P analysis. Since K-2-P analysis could not cover all species determination issues, therefore, TraeNPV needs to be sequenced for defining its taxonomic position. For this purpose, different genomic sequencing technologies and bioinformatic analysis approaches will be discussed. We anticipated that these applications will help to exam nucleotide information of unknown species and give an insight and facilitate to this issue

The characterization of the saddle shaped nickel(III) porphyrin radical cation: an explicative NMR model for a ferromagnetically coupled metallo-porphyrin radical

Ni(III)(OETPP˙)(Br)2 is the first Ni(III) porphyrin radical cation with structural and (1)H and (13)C paramagnetic NMR data for porphyrinate systems. Associating EPR and NMR analyses with DFT calculations as a new model is capable of clearly determining the dominant state from two controversial spin distributions in the ring to be the Ni(III) LS coupled with an a1u spin-up radical