Modeling malaria vaccines. I: New uses for old ideas

Starting from a modification of the model of malaria transmission developed for the Garki project, this paper develops a model containing variables relevant to the stimulation of malaria vaccination programs. Modifications include (1) integration of maintenance of immunity dependent on boosting and the possibility of loss of immunity; (2) introduction of a boosting factor distinct from susceptibility to infection; (3) reinterpretation of the epidemiological compartments of positive immunes and nonimmunes in terms of severity of disease rather than just infection; (4) interpretation of the different stage-specific levels of immunity; (5) discrimination between different susceptibilities for the immune and nonimmune classes; (6) reformulation of the expression for acquisition of immunity to be biologically more acceptable. Simulations using the Garki model, Nedelman's modification of it, and our Basic model compare the similarities and differences in the predictive behavior of the models. Simulations using the Basic model reproduce observed periodic fluctuations of malaria attributed to the interplay of transmission-blocking immunity and loss of immunity in the absence of boosting in areas of unstable malaria transmission.     

A non-parametric method for the reconstruction of age- and time-dependent incidence from the prevalence data of irreversible diseases with differential mortality.

A method is proposed for reconstructing the time and age dependence of incidence rates from successive age-prevalence cross sections taken from the sentinel surveys of irreversible diseases when there is an important difference in mortality between the infected and susceptible subpopulations. The prevalence information at different time-age points is used to generate a surface; the time-age variations along the life line profiles of this surface and the difference in mortality rates are used to reconstruct the time and age dependence of the incidence rate. Past attempts were based on specified parametric forms for the incidence or on the hypothesis of time-invariant forms for the age-prevalence cross sections. The proposed method makes no such assumptions and is thus capable of coping with rapidly evolving prevalence situations. In the simulations carried out, it is found to be resilient to important random noise components added to a prescribed incidence rate input. The method is also tested on a real data set of successive HIV age-prevalence cross sections from Burundi coupled to differential mortality data on HIV(+) and HIV(-) individuals. The often-made assumption that the incidence rate can be written as the product of a calendar time component and an age component is also examined. In this case, a pooling procedure is proposed to estimate the time and the age profiles of the incidence rate using the reconstructed incidence rates at all time-age points.     

Application of an optimized marker amplification protocol in immunohistochemistry — a valuable tool for visualizing antigenic sites of low signal strength or sparse distribution

Amplification of immunohistochemical markers received considerable attention during the 1980s and 1990s. The amplification approach was largely abandoned following the development of antigen retrieval and reporter amplification techniques, because the latter were incorporated more easily into high throughput automated procedures in industrial and diagnostic laboratories. There remain, however, a number of instances where marker amplification still has much to offer. Consequently, we examined experimentally the utility of an optimized marker amplification technique in diagnostically relevant tissue where either the original signal strength was low or positive sites were visible, but sparsely distributed. Marker amplification in the former case not only improved the visibility of existing positive sites, but also revealed additional sites that previously were undetectable. In the latter case, positive sites were rendered more intense and therefore more easily seen during low magnification examination of large areas of tissue.     

EFFECT OF VITAMIN E SUPPLEMENTATION AND PARTIAL SUBSTITUTION OF POLY- WITH MONO-UNSATURATED FATTY ACIDS IN PIG DIETS ON MUSCLE,AND MICROSOME EXTRACT a-TOCOPHEROL CONCENTRATION AND LIPID OXIDATION

The experiment was organized in a 3×2 factorial arrangement with three dietary fat blends and a basal (20 mg kg^?1 diet) or supplemented (220 mg kg^?1) level of α-tocopheryl acetate. Dietary vitamin E and monounsaturated to polyunsaturated fatty acid ratio (dietary MUFA/PUFA) affected muscle α-tocopherol concentration (α-tocopherol [log μg g^?1]=0.18 (±0.105)+0.0034 (±0.0003)·dietary α-tocopherol [mg kg^?1 diet] (P<0.0001)+0.39 (±0.122)·dietary MUFA/PUFA (P<0.0036)). An interaction between dietary α-tocopherol and dietary MUFA/PUFA exists for microsome α-tocopherol concentration (α-tocopherol [log μg g^?1]=1.14 (±0.169) (P<0.0001)+0.0056 (±0.00099)·dietary α-tocopherol [mg kg^?1 diet] (P<0.0001)+0.54 (±0.206)·dietary MUFA/PUFA (P<0.0131)?0.0033 (±0.0011)·dietary α-tocopherol [mg kg^?1)]×dietary MUFA/PUFA (P<0.0067)), and hexanal concentration in meat (hexanal [ng·g^?1]=14807.9 (±1489.8)?28.8 (±10.6) dietary α-tocopherol [mg·kg^?1] (P<0.01)?8436.6 (±1701.6)·dietary MUFA/PUFA (P<0.001)+24.0 (±11.22)·dietary α-tocopherol·dietary MUFA/PUFA (P<0.0416)). It is concluded that partial substitution of dietary PUFA with MUFA lead to an increase in the concentration of α-tocopherol in muscle and microsome extracts. An interaction between dietary α-tocopherol and fatty acids exists, in which at low level of dietary vitamin E inclusion, a low MUFA/PUFA ratio leads to a reduction in the concentration of α-tocopherol in microsome extracts and a concentration of hexanal in meat above the expected values.     

Quirks of dye nomenclature. 5. Rhodamines

Rhodamines were first produced in the late 19^th century, when they constituted a new class of synthetic dyes. These compounds since have been used to color many things including cosmetics, inks, textiles, and in some countries, food products. Certain rhodamine dyes also have been used to stain biological specimens and currently are widely used as fluorescent probes for mitochondria in living cells. The early history and current biological applications are sketched briefly and an account of the ambiguities, complications and confusions concerning dye identification and nomenclature are discussed.     

Quirks of dye nomenclature. 6. Malachite green

Malachite green was discovered independently by two researchers in Germany in the 19^th century and found immediate employment as a dye and a pigment. Subsequently, other uses, such as staining biological specimens, emerged. A much later application was the control of fungal and protozoan infections in fish, for which the dye remains popular, although illegal in many countries owing to a variety of toxicity problems. In solution, malachite green can exist as five different species depending on the pH. The location of the positive charge of the colored cation on a carbon atom or a nitrogen atom is still debated. The original names of this dye, and their origins, are briefly surveyed.     

Uncertainties regarding dengue modeling in Rio de Janeiro, Brazil

Dengue fever is currently the most important arthropod-borne viral disease in Brazil. Mathematical modeling of disease dynamics is a very useful tool for the evaluation of control measures. To be used in decision-making, however, a mathematical model must be carefully parameterized and validated with epidemiological and entomological data. In this work, we developed a simple dengue model to answer three questions: (i) which parameters are worth pursuing in the field in order to develop a dengue transmission model for Brazilian cities; (ii) how vector density spatial heterogeneity influences control efforts; (iii) with a degree of uncertainty, what is the invasion potential of dengue virus type 4 (DEN-4) in Rio de Janeiro city. Our model consists of an expression for the basic reproductive number (R0) that incorporates vector density spatial heterogeneity. To deal with the uncertainty regarding parameter values, we parameterized the model using a priori probability density functions covering a range of plausible values for each parameter. Using the Latin Hypercube Sampling procedure, values for the parameters were generated. We conclude that, even in the presence of vector spatial heterogeneity, the two most important entomological parameters to be estimated in the field are the mortality rate and the extrinsic incubation period. The spatial heterogeneity of the vector population increases the risk of epidemics and makes the control strategies more complex. At last, we conclude that Rio de Janeiro is at risk of a DEN-4 invasion. Finally, we stress the point that epidemiologists, mathematicians, and entomologists need to interact more to find better approaches to the measuring and interpretation of the transmission dynamics of arthropod-borne diseases.     

A Bayesian Hierarchical Model for Estimation of Abundance and Spatial Density of Aedes aegypti

Strategies to minimize dengue transmission commonly rely on vector control, which aims to maintain Ae. aegypti density below a theoretical threshold. Mosquito abundance is traditionally estimated from mark-release-recapture (MRR) experiments, which lack proper analysis regarding accurate vector spatial distribution and population density. Recently proposed strategies to control vector-borne diseases involve replacing the susceptible wild population by genetically modified individuals’ refractory to the infection by the pathogen. Accurate measurements of mosquito abundance in time and space are required to optimize the success of such interventions. In this paper, we present a hierarchical probabilistic model for the estimation of population abundance and spatial distribution from typical mosquito MRR experiments, with direct application to the planning of these new control strategies. We perform a Bayesian analysis using the model and data from two MRR experiments performed in a neighborhood of Rio de Janeiro, Brazil, during both low- and high-dengue transmission seasons. The hierarchical model indicates that mosquito spatial distribution is clustered during the winter (0.99 mosquitoes/premise 95% CI: 0.80–1.23) and more homogeneous during the high abundance period (5.2 mosquitoes/premise 95% CI: 4.3–5.9). The hierarchical model also performed better than the commonly used Fisher-Ford’s method, when using simulated data. The proposed model provides a formal treatment of the sources of uncertainty associated with the estimation of mosquito abundance imposed by the sampling design. Our approach is useful in strategies such as population suppression or the displacement of wild vector populations by refractory Wolbachia-infected mosquitoes, since the invasion dynamics have been shown to follow threshold conditions dictated by mosquito abundance. The presence of spatially distributed abundance hotspots is also formally addressed under this modeling framework and its knowledge deemed crucial to predict the fate of transmission control strategies based on the replacement of vector populations.     

Quantitative variability of 342 plasma proteins in a human twin population

The degree and the origins of quantitative variability of most human plasma proteins are largely unknown. Because the twin study design provides a natural opportunity to estimate the relative contribution of heritability and environment to different traits in human population, we applied here the highly accurate and reproducible SWATH mass spectrometry technique to quantify 1,904 peptides defining 342 unique plasma proteins in 232 plasma samples collected longitudinally from pairs of monozygotic and dizygotic twins at intervals of 2–7 years, and proportioned the observed total quantitative variability to its root causes, genes, and environmental and longitudinal factors. The data indicate that different proteins show vastly different patterns of abundance variability among humans and that genetic control and longitudinal variation affect protein levels and biological processes to different degrees. The data further strongly suggest that the plasma concentrations of clinical biomarkers need to be calibrated against genetic and temporal factors. Moreover, we identified 13 cis‐SNPs significantly influencing the level of specific plasma proteins. These results therefore have immediate implications for the effective design of blood‐based biomarker studies.