We determined reaction norms for developmental time and weight at eclosion for 2 isozygous and 11 genetically mixed strains of Drosophila mercatorum in four culture media differing in yeast concentration. With decreasing yeast concentration, development was delayed, the weight of emerging flies decreased, and the phenotypic variance of both variables increased. Differences among stocks and significant stock x yeast interactions indicated genetic variance for both variables within environment and different phenotypic responses of stocks across environments. The phenotypic correlation between developmental time and weight was negative at low yeast concentrations and disappeared gradually with increasing yeast. The comparison of completely homozygous with genetically heterogenous stocks showed that most of the increase of variability with deteriorating environment was due to the changing expression of genetic variance. The genetic correlation between developmental time and weight turned from negative in poor to positive in rich medium, while the environmental covariance was negative in all media. Plotting the reaction norms in the developmental time-weight plane rather than separately for each trait reveals most of these results at a glance. It also suggests that much of the genetic variance might be additive, because an effect of the half-sib family structure inherent in the design is clearly visible in the plot. We interpret the pattern of changing variances and covariances, pointing out that the special growth physiology of Drosophila and the way environmental factors affect it must be taken into account. We briefly discuss the implications of changing genetic correlations among traits for the evolution of phenotypic plasticity in general.

BackgroundKnowledge of the number of recent HIV infections is important for epidemiologic surveillance. Over the past decade approaches have been developed to estimate this number by testing HIV-seropositive specimens with assays that discriminate the lower concentration and avidity of HIV antibodies in early infection. We have investigated whether this “recency” information can also be gained from an HIV confirmatory assay.Methods and FindingsThe ability of a line immunoassay (INNO-LIA HIV I/II Score, Innogenetics) to distinguish recent from older HIV-1 infection was evaluated in comparison with the Calypte HIV-1 BED Incidence enzyme immunoassay (BED-EIA). Both tests were conducted prospectively in all HIV infections newly diagnosed in Switzerland from July 2005 to June 2006. Clinical and laboratory information indicative of recent or older infection was obtained from physicians at the time of HIV diagnosis and used as the reference standard. BED-EIA and various recency algorithms utilizing the antibody reaction to INNO-LIA's five HIV-1 antigen bands were evaluated by logistic regression analysis. A total of 765 HIV-1 infections, 748 (97.8%) with complete test results, were newly diagnosed during the study. A negative or indeterminate HIV antibody assay at diagnosis, symptoms of primary HIV infection, or a negative HIV test during the past 12 mo classified 195 infections (26.1%) as recent (≤ 12 mo). Symptoms of CDC stages B or C classified 161 infections as older (21.5%), and 392 patients with no symptoms remained unclassified. BED-EIA ruled 65% of the 195 recent infections as recent and 80% of the 161 older infections as older. Two INNO-LIA algorithms showed 50% and 40% sensitivity combined with 95% and 99% specificity, respectively. Estimation of recent infection in the entire study population, based on actual results of the three tests and adjusted for a test's sensitivity and specificity, yielded 37% for BED-EIA compared to 35% and 33% for the two INNO-LIA algorithms. Window-based estimation with BED-EIA yielded 41% (95% confidence interval 36%–46%).ConclusionsRecency information can be extracted from INNO-LIA-based confirmatory testing at no additional costs. This method should improve epidemiologic surveillance in countries that routinely use INNO-LIA for HIV confirmation.

BackgroundNew HIV infections in men who have sex with men (MSM) have increased in Switzerland since 2000 despite combination antiretroviral therapy (cART). The objectives of this mathematical modelling study were: to describe the dynamics of the HIV epidemic in MSM in Switzerland using national data; to explore the effects of hypothetical prevention scenarios; and to conduct a multivariate sensitivity analysis.Methodology/Principal FindingsThe model describes HIV transmission, progression and the effects of cART using differential equations. The model was fitted to Swiss HIV and AIDS surveillance data and twelve unknown parameters were estimated. Predicted numbers of diagnosed HIV infections and AIDS cases fitted the observed data well. By the end of 2010, an estimated 13.5% (95% CI 12.5, 14.6%) of all HIV-infected MSM were undiagnosed and accounted for 81.8% (95% CI 81.1, 82.4%) of new HIV infections. The transmission rate was at its lowest from 1995–1999, with a nadir of 46 incident HIV infections in 1999, but increased from 2000. The estimated number of new infections continued to increase to more than 250 in 2010, although the reproduction number was still below the epidemic threshold. Prevention scenarios included temporary reductions in risk behaviour, annual test and treat, and reduction in risk behaviour to levels observed earlier in the epidemic. These led to predicted reductions in new infections from 2 to 26% by 2020. Parameters related to disease progression and relative infectiousness at different HIV stages had the greatest influence on estimates of the net transmission rate.Conclusions/SignificanceThe model outputs suggest that the increase in HIV transmission amongst MSM in Switzerland is the result of continuing risky sexual behaviour, particularly by those unaware of their infection status. Long term reductions in the incidence of HIV infection in MSM in Switzerland will require increased and sustained uptake of effective interventions.

Background Serologic testing algorithms for recent HIV seroconversion (STARHS) provide important information for HIV surveillance. We have previously demonstrated that a patient's antibody reaction pattern in a confirmatory line immunoassay (INNO-LIA™ HIV I/II Score) provides information on the duration of infection, which is unaffected by clinical, immunological and viral variables. In this report we have set out to determine the diagnostic performance of Inno-Lia algorithms for identifying incident infections in patients with known duration of infection and evaluated the algorithms in annual cohorts of HIV notifications. Methods Diagnostic sensitivity was determined in 527 treatment-naive patients infected for up to 12 months. Specificity was determined in 740 patients infected for longer than 12 months. Plasma was tested by Inno-Lia and classified as either incident (< = 12 m) or older infection by 26 different algorithms. Incident infection rates (IIR) were calculated based on diagnostic sensitivity and specificity of each algorithm and the rule that the total of incident results is the sum of true-incident and false-incident results, which can be calculated by means of the pre-determined sensitivity and specificity. Results The 10 best algorithms had a mean raw sensitivity of 59.4% and a mean specificity of 95.1%. Adjustment for overrepresentation of patients in the first quarter year of infection further reduced the sensitivity. In the preferred model, the mean adjusted sensitivity was 37.4%. Application of the 10 best algorithms to four annual cohorts of HIV-1 notifications totalling 2'595 patients yielded a mean IIR of 0.35 in 2005/6 (baseline) and of 0.45, 0.42 and 0.35 in 2008, 2009 and 2010, respectively. The increase between baseline and 2008 and the ensuing decreases were highly significant. Other adjustment models yielded different absolute IIR, although the relative changes between the cohorts were identical for all models. Conclusions The method can be used for comparing IIR in annual cohorts of HIV notifications. The use of several different algorithms in combination, each with its own sensitivity and specificity to detect incident infection, is advisable as this reduces the impact of individual imperfections stemming primarily from relatively low sensitivities and sampling bias.

All 36 possible crosses among 6 homozygous lines of Drosophila melunoguster were tested for their phenotypic response in developmental time and dry weight at eclosion to variation in temperature and yeast concentration. This method was chosen because it allows one to produce the same heterozygous offspring repeatedly for testing under more conditions than could be handled at once. We estimated the effects of yeast concentration and temperature and their interaction on both the phenotypic and the environmental components of variation and covariation of the two traits. Development was slower at low temperatures and yeast concentrations, and dry weight and viability were lower at higher temperatures and lower yeast levels. Interactions of the two factors with the crosses and with each other indicated that there were genetic differences in plasticity and that the sensitivity of a trait to one factor depended on the level of the other. The covariation of the two traits was generally weak within an environment. Across environments, its sign depended on the factor that changed between the environments: positive for temperature, negative for yeast concentration. These findings can be explained in terms of an established growth model for Drosophilu larvae. We conclude that for plastic traits with moderate or low heritability, the relationship between the phenotypic and genetic covariance matrices may be a complex function of the environmental factors that affect the traits. Some implications for the prediction of the evolution in fluctuating environments are outlined.