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Several laboratory assays on cross-sectional specimens for detecting recent HIV infections were developed, but these assays could not be applied in resource-limited and high HIV-incidence areas. This study describes the development of a rapid assay that can simultaneously detect the presence of HIV-1 antibodies of current and/or recent infection. The dot immuno-gold filtration assay (DIGFA) was used to detect recent infection on the principle of antibody avidity changes between recent and long-term infections. The dot immuno-gold silver staining filtration assay (DIGSSA) increases the sensitivity and accuracy of antibody detection by adding a silver staining step to the DIGFA. In the meantime the digital results were produced by the scanner for ambiguous specimens. Further, HIV-1 routine diagnostic antibody was detected simultaneously for improving practicability. The performance of the assays was then assessed through five serum panels with known serological statuses and seroconversion dates. The proportion of false recent infection (PFR) of the DIGSSA was obtained. Through the optimization of basic parameters for DIGSSA, six specimens were all classified correctly. DIGSSA demonstrated good repeatability and high sensitivity. The agreement of DIGSSA with the BED assay was 92.10% (κ = 0.65) and 95.36% with the LAg-Avidity assay (κ = 0.75). Moreover, the gray values of DIGSSA correlated well with BED ODn (R2 = 0.9397) and LAg-Avidity ODn (R2 = 0.9549). The PFR of DIGSSA was 2.73%, which was lower than that of the BED assay but higher than that of the LAg-Avidity assay. The DIGSSA can feasibly be applied to detect HIV infection and estimate HIV incidence.

The efficacy of an inactivated foot-and-mouth disease (FMD) vaccine is mainly dependent on the integrity of the foot-and-mouth disease virus (FMDV) particles. At present, the standard method to quantify the active component, the 146S antigen, of FMD vaccines is sucrose density gradient (SDG) analysis. However, this method is highly operator dependent and difficult to automate. In contrast, the enzyme-linked immunosorbent assay (ELISA) is a time-saving technique that provides greater simplicity and sensitivity. To establish a valid method to detect and quantify the 146S antigen of a serotype O FMD vaccine, a double-antibody sandwich (DAS) ELISA was compared with an SDG analysis. The DAS ELISA was highly correlated with the SDG method (R2 = 0.9215, P

Quantifying the impact of a scholarly paper is of great significance, yet the effect of geographical distance of cited papers has not been explored. In this paper, we examine 30,596 papers published in Physical Review C, and identify the relationship between citations and geographical distances between author affiliations. Subsequently, a relative citation weight is applied to assess the impact of a scholarly paper. A higher-order weighted quantum PageRank algorithm is also developed to address the behavior of multiple step citation flow. Capturing the citation dynamics with higher-order dependencies reveals the actual impact of papers, including necessary self-citations that are sometimes excluded in prior studies. Quantum PageRank is utilized in this paper to help differentiating nodes whose PageRank values are identical. Refereed/Peer-reviewed

Background Twitter offers a platform for rapid diffusion of information and its users' attitudes and behaviors. Insights about information propagation via retweets (the message forwarding function) offer observable explanations of ways in which modern human interactions get organized in the form of online networks, and contextualized in the form of public health, policy decisions, disaster management, and civic participation. This study conceptualized and validated the Why We Retweet Scale to contextualize retweeting behavior. Objective Twitter users were identified using clustering algorithms that consider a users’ position in their network and invited for an online survey. Participants (N = 1433) responded to 19 questions about why they retweet. Exploratory factor Analysis (EFA) was conducted on a scale development sample (70% of original sample), which informed the Confirmatory Factor Analysis (CFA) on a scale testing sample (30% of the original sample). Varimax rotation was used to obtain a rotated factor solution, which resulted in interpretable factors. Demographic differences among scale factors were analyzed using one-way ANOVA or independent samples t-tests. Results The final model (χ221 = 28, RMSEA = .03 [90% CI, 0.00–0.06], CFA = .99, TLI = 0.99) represented a parsimonious solution with 4 factors, measured by 2–3 items each, creating a final scale consisting of 9 items. Factor labels and definitions were: (1) Show approval, “Show support to the tweeter”; (2) Argue, “To argue against a tweet that I disagree with”; (3) Gain attention, “Add followers or gain attention”; and (4) Entertain, “Create humor/amusement”. Demographic differences were also reported. Conclusions The Why We Retweet Scale offers a useful conceptualization and assessment of motivations for retweeting. In the future, communication strategists might consider the factors associated with information propagation when designing campaign messages to maximize message reach and engagement on Twitter.