Red-Backed Vole Brain Promotes Highly Efficient In Vitro Amplification of Abnormal Prion Protein from Macaque and Human Brains Infected with Variant Creutzfeldt-Jakob Disease Agent

Rapid antemortem tests to detect individuals with transmissible spongiform encephalopathies (TSE) would contribute to public health. We investigated a technique known as protein misfolding cyclic amplification (PMCA) to amplify abnormal prion protein (PrP^TSE) from highly diluted variant Creutzfeldt-Jakob disease (vCJD)-infected human and macaque brain homogenates, seeking to improve the rapid detection of PrP^TSE in tissues and blood. Macaque vCJD PrP^TSE did not amplify using normal macaque brain homogenate as substrate (intraspecies PMCA). Next, we tested interspecies PMCA with normal brain homogenate of the southern red-backed vole (RBV), a close relative of the bank vole, seeded with macaque vCJD PrP^TSE. The RBV has a natural polymorphism at residue 170 of the PrP-encoding gene (N/N, S/S, and S/N). We investigated the effect of this polymorphism on amplification of human and macaque vCJD PrP^TSE. Meadow vole brain (170N/N PrP genotype) was also included in the panel of substrates tested. Both humans and macaques have the same 170S/S PrP genotype. Macaque PrP^TSE was best amplified with RBV 170S/S brain, although 170N/N and 170S/N were also competent substrates, while meadow vole brain was a poor substrate. In contrast, human PrP^TSE demonstrated a striking narrow selectivity for PMCA substrate and was successfully amplified only with RBV 170S/S brain. These observations suggest that macaque PrP^TSE was more permissive than human PrP^TSE in selecting the competent RBV substrate. RBV 170S/S brain was used to assess the sensitivity of PMCA with PrP^TSE from brains of humans and macaques with vCJD. PrP^TSE signals were reproducibly detected by Western blot in dilutions through 10^-12 of vCJD-infected 10% brain homogenates. This is the first report showing PrP^TSE from vCJD-infected human and macaque brains efficiently amplified with RBV brain as the substrate. Based on our estimates, PMCA showed a sensitivity that might be sufficient to detect PrP^TSE in vCJD-infected human and macaque blood.     

Ca transients from Ca channel activity in rat cardiac myocytes reveal dynamics of dyad cleft and troponin C Ca binding

The properties of the dyad cleft can in principle significantly impact excitation-contraction coupling, but these properties are not easily amenable to experimental investigation. We simultaneously measured the time course of the rise in integrated Ca current (I_Ca) and the rise in concentration of fura 2 with Ca bound ([Ca-fura 2]) with high time resolution in rat myocytes for conditions under which Ca entry is only via L-type Ca channels and sarcoplasmic reticulum (SR) Ca release is blocked, and compared these measurements with predictions from a finite-element model of cellular Ca diffusion. We found that 1) the time course of the rise of [Ca-fura 2] follows the time course of integrated I_Ca plus a brief delay (1.36 ± 0.43 ms, n = 6 cells); 2) from the model, high-affinity Ca binding sites in the dyad cleft at the level previously envisioned would result in a much greater delay (=" BORDER="0">3 ms) and are therefore unlikely to be present at that level; 3) including ATP in the model promoted Ca efflux from the dyad cleft by a factor of 1.57 when low-affinity cleft Ca binding sites were present; 4) the data could only be fit to the model if myofibrillar troponin C (TnC) Ca binding were low affinity (4.56 µM), like that of soluble troponin C, instead of the high-affinity value usually used (0.38 µM). In a "good model," the rate constants for Ca binding and dissociation were 0.375 times the values for soluble TnC; and 5) consequently, intracellular Ca buffering at the rise of the Ca transient is inferred to be low. excitation-contraction coupling; adenosine triphosphate; fura 2; modeling; fuzzy space     

Integrated survival analysis using an event‐time approach in a Bayesian framework

Event‐time or continuous‐time statistical approaches have been applied throughout the biostatistical literature and have led to numerous scientific advances. However, these techniques have traditionally relied on knowing failure times. This has limited application of these analyses, particularly, within the ecological field where fates of marked animals may be unknown. To address these limitations, we developed an integrated approach within a Bayesian framework to estimate hazard rates in the face of unknown fates. We combine failure/survival times from individuals whose fates are known and times of which are interval‐censored with information from those whose fates are unknown, and model the process of detecting animals with unknown fates. This provides the foundation for our integrated model and permits necessary parameter estimation. We provide the Bayesian model, its derivation, and use simulation techniques to investigate the properties and performance of our approach under several scenarios. Lastly, we apply our estimation technique using a piece‐wise constant hazard function to investigate the effects of year, age, chick size and sex, sex of the tending adult, and nesting habitat on mortality hazard rates of the endangered mountain plover (Charadrius montanus) chicks. Traditional models were inappropriate for this analysis because fates of some individual chicks were unknown due to failed radio transmitters. Simulations revealed biases of posterior mean estimates were minimal (≤ 4.95%), and posterior distributions behaved as expected with RMSE of the estimates decreasing as sample sizes, detection probability, and survival increased. We determined mortality hazard rates for plover chicks were highest at <5 days old and were lower for chicks with larger birth weights and/or whose nest was within agricultural habitats. Based on its performance, our approach greatly expands the range of problems for which event‐time analyses can be used by eliminating the need for having completely known fate data.     

PHYTOTOXIC VOLATILES FROM TRICHOSTEMA LANCEOLATUM (LABIATAE)

Trichostema lanceolatum Benth. (vinegar weed), an annual herb of the California grassland, contains 2.9 ml of volatile essential oil per 100 g of fresh foliage. Vapors from leaves and extracted oil inhibited growth of other plants in laboratory tests. Volatiles from 0.12–0.15 g green Trichostema leaf caused a 50% reduction in radicle elongation of Bromus mollis L. and Hordeum vulgare L. seeds in petri dishes. Vapors from 1.5 and 3.2 μl essential oil in sealed and non-sealed dishes, respectively, had a similar effect on Hordeum seeds. Exposure of dry Bromus seeds for 1 day, and dry Hordeum seeds for 3 days, to volatiles from Trichostema foliage inhibited growth when the seeds were later moistened. The toxic volatiles had a high affinity for vegetable oil and were not readily removed from seeds by rinsing with water. The major volatile inhibitor from Trichostema was terpinen-4-ol. This monoterpene alcohol was about 0.3 and 1.9 times as inhibitory as camphor and 1,8-cineole, terpenes that have previously been shown to influence vegetation patterning near Salvia leucophylla Greene shrubs. These results suggest Trichostema lanceolatum may also have allelopathic potential.     

Using amplified fragment length polymorphism analysis to differentiate isolates of Pasteurella multocida serotype 1

Avian cholera, an infectious disease caused by the bacterium Pasteurella multocida, kills thousands of North American wild waterfowl annually. Pasteurella multocida serotype 1 isolates cultured during a laboratory challenge study of Mallards (Anas platyrhynchos) and collected from wild birds and environmental samples during avian cholera outbreaks were characterized using amplified fragment length polymorphism (AFLP) analysis, a whole-genome DNA fingerprinting technique. Comparison of the AFLP profiles of 53 isolates from the laboratory challenge demonstrated that P. multocida underwent genetic changes during a 3-mo period. Analysis of 120 P. multocida serotype 1 isolates collected from wild birds and environmental samples revealed that isolates were distinguishable from one another based on regional and temporal genetic characteristics. Thus, AFLP analysis had the ability to distinguish P. multocida isolates of the same serotype by detecting spatiotemporal genetic changes and provides a tool to advance the study of avian cholera epidemiology. Further application of AFLP technology to the examination of wild bird avian cholera outbreaks may facilitate more effective management of this disease by providing the potential to investigate correlations between virulence and P. multocida genotypes, to identify affiliations between bird species and bacterial genotypes, and to elucidate the role of specific bird species in disease transmission.     

Mapping Brucellosis Increases Relative to Elk Density Using Hierarchical Bayesian Models

The relationship between host density and parasite transmission is central to the effectiveness of many disease management strategies. Few studies, however, have empirically estimated this relationship particularly in large mammals. We applied hierarchical Bayesian methods to a 19-year dataset of over 6400 brucellosis tests of adult female elk (Cervus elaphus) in northwestern Wyoming. Management captures that occurred from January to March were over two times more likely to be seropositive than hunted elk that were killed in September to December, while accounting for site and year effects. Areas with supplemental feeding grounds for elk had higher seroprevalence in 1991 than other regions, but by 2009 many areas distant from the feeding grounds were of comparable seroprevalence. The increases in brucellosis seroprevalence were correlated with elk densities at the elk management unit, or hunt area, scale (mean 2070 km²; range  = [95–10237]). The data, however, could not differentiate among linear and non-linear effects of host density. Therefore, control efforts that focus on reducing elk densities at a broad spatial scale were only weakly supported. Additional research on how a few, large groups within a region may be driving disease dynamics is needed for more targeted and effective management interventions. Brucellosis appears to be expanding its range into new regions and elk populations, which is likely to further complicate the United States brucellosis eradication program. This study is an example of how the dynamics of host populations can affect their ability to serve as disease reservoirs.     

Generalizing Double and Triple Sampling for Repeated Surveys and Partial Verification

Population composition is often estimated by double sampling in which the value of a covariate is noted on each of a large number of randomly selected units and the value of the covariate and the exact class to which the unit belongs is noted for a smaller sample. The cross‐classified sample can be used to estimate the classification rates and these, in turn, can be used in conjunction with the estimated distribution of the covariate to obtain an improved estimate of the population composition over that obtained by direct observation of the identity of the individuals in a small sample. There are two approaches to this problem characterized by the way in which the classification rates are defined. The simplest approach uses estimates of the probability P(i | j) that the unit is actually in class i given that the covariate is in class j. The more complicated approach uses estimates of the probability Pi | j) that the covariate falls in class j given that the unit is actually in class i. The latter approach involves estimating more parameters than the former but avoids the necessity for the two samples to be drawn from the same population. We show the two approaches can be combined when there are multiple surveys. For example, one might conduct a disease survey for several years; in each year the accurate and/or error‐prone techniques may be applied to samples. The sensitivities and specificities of the error‐prone test are assumed constant across surveys. Generalizations allow for more than one error‐prone classifier and partial verification (estimation of misclassification rates by application of the accurate technique to fixed subsamples from each error‐prone category). The general approach is illustrated by considering a repeated survey for malaria.     

A probabilistic rule of mixtures for elastic moduli

A novel approach is developed for mathematically modeling the variability observed in experimentally determined elastic moduli of longitudinally oriented fibrous tissues such as ligaments and tendons. The elastic modulus of these tissues is modeled with a rule of mixtures (ROM) where each parameter (fibril and matrix moduli and fibril volume fraction) is assumed to be an independent random variable. A joint density function formed from the independent densities results in a probabilistic ROM (pROM). This pROM is used to generate a distribution of moduli which agrees well with moduli determined from tests of rabbit medial collateral ligaments (Woo and Ohland, 1994, Unpublished experimental data as gift). Minimizing the error between the pROM and experimental distributions resulted in an integrated error of 9% for a constrained set of independent distribution parameters derived from the literature. This pROM thus incorporates microstructural observations (fibril and matrix moduli and fibril volume fraction) to partially explain the experimentally observed variability in a macroscopic property (tissue modulus).