Mixture models for analysis of melting temperature data

<p>Abstract</p> <p>Background</p> <p>In addition to their use in detecting undesired real-time PCR products, melting temperatures are useful for detecting variations in the desired target sequences. Methodological improvements in recent years allow the generation of high-resolution melting-temperature (T_m) data. However, there is currently no convention on how to statistically analyze such high-resolution T_mdata.</p> <p>Results</p> <p>Mixture model analysis was applied to T_mdata. Models were selected based on Akaike's information criterion. Mixture model analysis correctly identified categories in T_mdata obtained for known plasmid targets. Using simulated data, we investigated the number of observations required for model construction. The precision of the reported mixing proportions from data fitted to a preconstructed model was also evaluated.</p> <p>Conclusion</p> <p>Mixture model analysis of T_mdata allows the minimum number of different sequences in a set of amplicons and their relative frequencies to be determined. This approach allows T_mdata to be analyzed, classified, and compared in an unbiased manner.</p

Emergence of G12 and G9 rotavirus genotypes in the Central African Republic, January 2014 to February 2016

Abstract Objectives Rotavirus gastroenteritis is a major cause of death among children under 5 years globally. A rotavirus gastroenteritis surveillance program started in October 2011 in the Central African Republic (CAR) with the Surveillance Epidémiologique en Afrique Centrale (SURVAC) project. We present here genotyping results showing the emergence of G9 and G12 genotypes in Central African Republic. Results Among 222 children hospitalized with acute gastroenteritis who had a stool sample collected at the sentinel site, Complexe Pédiatrique de Bangui (CPB), Bangui, Central African Republic, 100 (45%) were positive for rotavirus between January 2014 and February 2016. During this period the most common rotavirus strains were G1P[8] (37%), G12P[6] (27%) and G9P[8] (18%)

Use of a rapid digital microfluidics-powered immunoassay for assessing measles and rubella infection and immunity in outbreak settings in the Democratic Republic of the Congo.

The Democratic Republic of the Congo (DRC) has a high measles incidence despite elimination efforts and has yet to introduce rubella vaccine. We evaluated the performance of a prototype rapid digital microfluidics powered (DMF) enzyme-linked immunoassay (ELISA) assessing measles and rubella infection, by testing for immunoglobulin M (IgM), and immunity from natural infection or vaccine, by testing immunoglobulin G (IgG), in outbreak settings. Field evaluations were conducted during September 2017, in Kinshasa province, DRC. Blood specimens were collected during an outbreak investigation of suspected measles cases and tested for measles and rubella IgM and IgG using the DMF-ELISA in the field. Simultaneously, a household serosurvey for measles and rubella IgG was conducted in a recently confirmed measles outbreak area. DMF-ELISA results were compared with reference ELISA results tested at DRC's National Public Health Laboratory and the US Centers for Disease Control and Prevention. Of 157 suspected measles cases, rubella IgM was detected in 54% while measles IgM was detected in 13%. Measles IgG-positive cases were higher among vaccinated persons (87%) than unvaccinated persons (72%). In the recent measles outbreak area, measles IgG seroprevalence was 93% overall, while rubella seroprevalence was lower for children (77%) than women (98%). Compared with reference ELISA, DMF-ELISA sensitivity and specificity were 82% and 78% for measles IgG; 88% and 89% for measles IgM; 85% and 85% for rubella IgG; and 81% and 83% for rubella IgM, respectively. Rubella infection was detected in more than half of persons meeting the suspected measles case definition during a presumed measles outbreak, suggesting substantial unrecognized rubella incidence, and highlighting the need for rubella vaccine introduction into the national schedule. The performance of the DMF-ELISA suggested that this technology can be used to develop rapid diagnostic tests for measles and rubella