Effects of fleas on nest success of Arctic barnacle geese:experimentally testing the mechanism

Parasites have detrimental effects on their hosts' fitness. Therefore, behavioural adaptations have evolved to avoid parasites or, when an individual is already in contact with a parasite, prevent or minimize infections. Such anti-parasite behaviours can be very effective, but can also be costly for the host. Specifically, ectoparasites can elicit strong host anti-parasite behaviours and interactions between fleas (Siphonaptera) and their hosts are one of the best studied. In altricial bird species, nest fleas can negatively affect both parent and offspring fitness components. However, knowledge on the effects of fleas on precocial bird species is scarce. Research on geese in the Canadian Arctic indicated that fleas have a negative impact on reproductive success. One possible hypothesis is that fleas may affect female incubation behaviour. Breeding females with many fleas in their nest may increase the frequency and/or duration of incubation breaks and could even totally desert their nest. The aim of our study was to 1) determine if a similar negative relationship existed between flea abundance and reproductive success in our study colony of Arctic breeding barnacle geese Branta leucopsis and 2) experimentally quantify if such effects could be explained by a negative effect of nest fleas on female behaviour. We compared host anti-parasite and incubation behaviour between experimentally flea-reduced and control nests using wildlife cameras and temperature loggers. We found that flea abundance was negatively associated with hatching success. We found little experimental support, however, for changes in behaviour of the breeding female as a possible mechanism to explain this effect

The effects of vaccination and immunity on bacterial infection dynamics in vivo.

Salmonella enterica infections are a significant global health issue, and development of vaccines against these bacteria requires an improved understanding of how vaccination affects the growth and spread of the bacteria within the host. We have combined in vivo tracking of molecularly tagged bacterial subpopulations with mathematical modelling to gain a novel insight into how different classes of vaccines and branches of the immune response protect against secondary Salmonella enterica infections of the mouse. We have found that a live Salmonella vaccine significantly reduced bacteraemia during a secondary challenge and restrained inter-organ spread of the bacteria in the systemic organs. Further, fitting mechanistic models to the data indicated that live vaccine immunisation enhanced both the bacterial killing in the very early stages of the infection and bacteriostatic control over the first day post-challenge. T-cell immunity induced by this vaccine is not necessary for the enhanced bacteriostasis but is required for subsequent bactericidal clearance of Salmonella in the blood and tissues. Conversely, a non-living vaccine while able to enhance initial blood clearance and killing of virulent secondary challenge bacteria, was unable to alter the subsequent bacterial growth rate in the systemic organs, did not prevent the resurgence of extensive bacteraemia and failed to control the spread of the bacteria in the body.This work was supported by the Biotechnology and Biological Sciences Research Council [grant number BB/I002189/1].This is the published manuscript. It was originally published by PLOS One here: http://www.plospathogens.org/article/info%3Adoi%2F10.1371%2Fjournal.ppat.1004359

Does Reduced IGF-1R Signaling in Igf1r+/− Mice Alter Aging?

Mutations in insulin/IGF-1 signaling pathway have been shown to lead to increased longevity in various invertebrate models. Therefore, the effect of the haplo- insufficiency of the IGF-1 receptor (Igf1r+/−) on longevity/aging was evaluated in C57Bl/6 mice using rigorous criteria where lifespan and end-of-life pathology were measured under optimal husbandry conditions using large sample sizes. Igf1r+/− mice exhibited reductions in IGF-1 receptor levels and the activation of Akt by IGF-1, with no compensatory increases in serum IGF-1 or tissue IGF-1 mRNA levels, indicating that the Igf1r+/− mice show reduced IGF-1 signaling. Aged male, but not female Igf1r+/− mice were glucose intolerant, and both genders developed insulin resistance as they aged. Female, but not male Igf1r+/− mice survived longer than wild type mice after lethal paraquat and diquat exposure, and female Igf1r+/− mice also exhibited less diquat-induced liver damage. However, no significant difference between the lifespans of the male Igf1r+/− and wild type mice was observed; and the mean lifespan of the Igf1r+/− females was increased only slightly (less than 5%) compared to wild type mice. A comprehensive pathological analysis showed no significant difference in end-of-life pathological lesions between the Igf1r+/− and wild type mice. These data show that the Igf1r+/− mouse is not a model of increased longevity and delayed aging as predicted by invertebrate models with mutations in the insulin/IGF-1 signaling pathway

Molecular detection of Coxiella burnetii infection in small mammals from Moshi Rural and Urban Districts, northern Tanzania

Coxiella burnetii is an obligate intracellular bacterium that causes Q fever, a zoonotic disease of public health importance. In northern Tanzania, Q fever is a known cause of human febrile illness, but little is known about its distribution in animal hosts. We used a quantitative real‐time PCR (qPCR) targeting the insertion element IS1111 to determine the presence and prevalence of C. burnetii infections in small mammals trapped in 12 villages around Moshi Rural and Moshi Urban Districts, northern Tanzania. A total of 382 trapped small mammals of seven species were included in the study; Rattus rattus (n = 317), Mus musculus (n = 44), Mastomys natalensis (n = 8), Acomys wilson (n = 6), Mus minutoides (n = 3), Paraxerus flavovottis (n = 3) and Atelerix albiventris (n = 1). Overall, 12 (3.1%) of 382 (95% CI: 1.6–5.4) small mammal spleens were positive for C. burnetii DNA. Coxiella burnetii DNA was detected in five of seven of the small mammal species trapped; R. rattus (n = 7), M. musculus (n = 1), A. wilson (n = 2), P. flavovottis (n = 1) and A. albiventris (n = 1). Eleven (91.7%) of twelve (95% CI: 61.5–99.8) C. burnetii DNA positive small mammals were trapped within Moshi Urban District. These findings demonstrate that small mammals in Moshi, northern Tanzania are hosts of C. burnetii and may act as a source of C. burnetii infection to humans and other animals. This detection of C. burnetii infections in small mammals should motivate further studies into the contribution of small mammals to the transmission of C. burnetii to humans and animals in this region

A novel multiplex real-time PCR for the identification of mycobacteria associated with zoonotic tuberculosis.

Tuberculosis (TB) is the leading cause of death worldwide from a single infectious agent. An ability to detect the Mycobacterium tuberculosis complex (MTC) in clinical material while simultaneously differentiating its members is considered important. This allows for the gathering of epidemiological information pertaining to the prevalence, transmission and geographical distribution of the MTC, including those MTC members associated with zoonotic TB infection in humans. Also differentiating between members of the MTC provides the clinician with inherent MTC specific drug susceptibility profiles to guide appropriate chemotherapy

The Central Limit Theorem

The applets in this section of Statistical Java allow you to see how the Central Limit Theorem works. The main page gives the characteristics of five non-normal distributions (Bernoulli, Poisson, Exponential, U-shaped, and Uniform). Users then select one of the distributions and change the sample size to see how the distribution of the sample mean approaches normality. Users can also change the number of samples. To select between the different applets you can click on Statistical Theory, the Central Limit Theorem and then the Main Page. At the bottom of this page you can make your applet selection

Exponential Probabilities

The applet, created by Virginia Tech's Department of Statistics, allows you see how probabilities are determined from the exponential distribution. The user determines the mean of the distribution and the limits of probability. Three different probability expressions are available. Click "Calculate" to see the pdf and the cdf. The probability is highlighted in green on the pdf. This is a nice reference tool for anyone studying statistics

Confidence Intervals

The applets in this section of Statistical Java allow you to see how levels of confidence are achieved through repeated sampling. The confidence intervals are related to the probability of successes in a Binomial experiment. The main page gives the equation for finding confidence intervals and describes the parameters (p, n, alpha). Each applet allows you to change a different parameter and simulate sampling to demonstrate the long run proportion of intervals that contain the true probability of success. The applets are available from a pull-down menu at the bottom of the page

Correlation

The applets, created by Virginia Tech's Department of Statistics, allow you to see how different bivariate data look under different correlation structures. The "Movie" applet either creates data for a particular correlation or animates a multitude data sets ranging correlations from -1 to 1. The "Creation" applet allows the user to create a data set by adding or deleting points from the screen

T Probabilities

The applet, created by Virginia Tech's Department of Statistics, allows you to see how the T distribution is related to the Standard Normal distribution by calculating probabilities. The T distribution is primarily used to make inferences on a Normal mean when the variance is unknown. If the variance is known inference on the mean can be done using the Standard Normal. The user has a choice of three different probability expressions, then can change the degrees of freedom and the limits of probability