Larval dispersal and predation in experimental populations of Chrysomya albiceps and Cochliomyia macellaria (Diptera: Calliphoridae)

In this study we investigated the larval dispersal associated with larval predation in experimental populations of Chrysomya albiceps and Cochliomyia macellaria. Frequency distribution of sampling units (G test) in the substrate was used to evaluate variation in larval dispersal. An experimental acrylic channel (1 x 0.1 x 0.2 m) covered with wood shavings was used to observe larval dispersal prior to pupation. The acrylic channel was graduated at 0.05 m intervals, each representing a sampling unit; hence, 20 sampling units were set up. A Petri dish containing third instar larvae of single and double species was deposited at one edge of the acrylic channel allowing larvae to disperse. The number of buried pupae (0, 1, 2, …n) present in each sampling unit was recorded. For double species, the number of recovered larvae of C. albiceps was similar to the number initially released on the dish Petri. On the other hand, the number of recovered larvae of C. macellaria was significantly smaller than the initially released number. The results show that C. albiceps attacks C. macellaria larvae during the larval dispersal process. The larval distribution of C. albiceps did not differ significantly from C. macellaria in double species, but it differed significantly in single species. The larval aggregation level of C. macellaria decreased when C. albiceps was present and the larval aggregation level of C. albiceps increased when C. macellaria was present. The implications of such findings for the population dynamics of these species are discussed.

Temporal and spatial distribution of Leishmania mexicana infections in a population of Neotoma micropus

A 19-month mark-release-recapture study of Neotoma micropus with sequential screening for Leishmania mexicana was conducted in Bexar County, Texas, USA. The overall prevalence rate was 14.7% and the seasonal prevalence rates ranged from 3.8 to 26.7%. Nine incident cases were detected, giving an incidence rate of 15.5/100 rats/year. Follow-up of 101 individuals captured two or more times ranged from 14 to 462 days. Persistence of L. mexicana infections averaged 190 days and ranged from 104 to 379 days. Data on dispersal, density, dispersion, and weight are presented, and the role of N. micropus as a reservoir host for L. mexicana is discussed.

Dispersal of Aedes aegypti and Aedes albopictus (Diptera: Culicidae) in an urban endemic dengue area in the State of Rio de Janeiro, Brazil

Experimental releases of female Aedes (Stegomyia) aegypti and Aedes (Stegomyia) albopictus were performed in August and September 1999, in an urban area of Nova Iguaçu, State of Rio de Janeiro, Brazil, to estimate their flight range in a circular area of 1,600 m where 1,472 ovitraps were set. Releases of 3,055 Ae. aegypti and 2,225 Ae. albopictus females, fed with rubidium (Rb)-marked blood and surgically prevented from subsequent blood-feeding, were separated by 11 days. Rb was detected in ovitrap-collected eggs by atomic emission spectrophotometry. Rb-marked eggs of both species were detected up to 800 m from the release point. Eggs of Ae. albopictus were more numerous and more heterogeneously distributed in the area than those of Ae. aegypti. Eggs positively marked for Rb were found at all borders of the study area, suggesting that egg laying also occurred beyond these limits. Results from this study suggest that females can fly at least 800 m in 6 days and, if infected, potentially spread virus rapidly.

Coronary MR angiography: comparison of quantitative and qualitative data from four techniques.

OBJECTIVE: The optimal coronary MR angiography sequence has yet to be determined. We sought to quantitatively and qualitatively compare four coronary MR angiography sequences. SUBJECTS AND METHODS. Free-breathing coronary MR angiography was performed in 12 patients using four imaging sequences (turbo field-echo, fast spin-echo, balanced fast field-echo, and spiral turbo field-echo). Quantitative comparisons, including signal-to-noise ratio, contrast-to-noise ratio, vessel diameter, and vessel sharpness, were performed using a semiautomated analysis tool. Accuracy for detection of hemodynamically significant disease (> 50%) was assessed in comparison with radiographic coronary angiography. RESULTS: Signal-to-noise and contrast-to-noise ratios were markedly increased using the spiral (25.7 +/- 5.7 and 15.2 +/- 3.9) and balanced fast field-echo (23.5 +/- 11.7 and 14.4 +/- 8.1) sequences compared with the turbo field-echo (12.5 +/- 2.7 and 8.3 +/- 2.6) sequence (p < 0.05). Vessel diameter was smaller with the spiral sequence (2.6 +/- 0.5 mm) than with the other techniques (turbo field-echo, 3.0 +/- 0.5 mm, p = 0.6; balanced fast field-echo, 3.1 +/- 0.5 mm, p < 0.01; fast spin-echo, 3.1 +/- 0.5 mm, p < 0.01). Vessel sharpness was highest with the balanced fast field-echo sequence (61.6% +/- 8.5% compared with turbo field-echo, 44.0% +/- 6.6%; spiral, 44.7% +/- 6.5%; fast spin-echo, 18.4% +/- 6.7%; p < 0.001). The overall accuracies of the sequences were similar (range, 74% for turbo field-echo, 79% for spiral). Scanning time for the fast spin-echo sequences was longest (10.5 +/- 0.6 min), and for the spiral acquisitions was shortest (5.2 +/- 0.3 min). CONCLUSION: Advantages in signal-to-noise and contrast-to-noise ratios, vessel sharpness, and the qualitative results appear to favor spiral and balanced fast field-echo coronary MR angiography sequences, although subjective accuracy for the detection of coronary artery disease was similar to that of other sequences.

Machine learning algorithms for spatial data. Case studies: Environmental pollution, natural hazards, renewable resources

This paper presents general problems and approaches for the spatial data analysis using machine learning algorithms. Machine learning is a very powerful approach to adaptive data analysis, modelling and visualisation. The key feature of the machine learning algorithms is that they learn from empirical data and can be used in cases when the modelled environmental phenomena are hidden, nonlinear, noisy and highly variable in space and in time. Most of the machines learning algorithms are universal and adaptive modelling tools developed to solve basic problems of learning from data: classification/pattern recognition, regression/mapping and probability density modelling. In the present report some of the widely used machine learning algorithms, namely artificial neural networks (ANN) of different architectures and Support Vector Machines (SVM), are adapted to the problems of the analysis and modelling of geo-spatial data. Machine learning algorithms have an important advantage over traditional models of spatial statistics when problems are considered in a high dimensional geo-feature spaces, when the dimension of space exceeds 5. Such features are usually generated, for example, from digital elevation models, remote sensing images, etc. An important extension of models concerns considering of real space constrains like geomorphology, networks, and other natural structures. Recent developments in semi-supervised learning can improve modelling of environmental phenomena taking into account on geo-manifolds. An important part of the study deals with the analysis of relevant variables and models' inputs. This problem is approached by using different feature selection/feature extraction nonlinear tools. To demonstrate the application of machine learning algorithms several interesting case studies are considered: digital soil mapping using SVM, automatic mapping of soil and water system pollution using ANN; natural hazards risk analysis (avalanches, landslides), assessments of renewable resources (wind fields) with SVM and ANN models, etc. The dimensionality of spaces considered varies from 2 to more than 30. Figures 1, 2, 3 demonstrate some results of the studies and their outputs. Finally, the results of environmental mapping are discussed and compared with traditional models of geostatistics.

Foreign ant queens are accepted but produce fewer offspring.

Understanding social evolution requires us to understand the processes regulating the number of breeders within social groups and how they partition reproduction. Queens in polygynous (multiple queens per colony) ants often seek adoption in established colonies instead of founding a new colony independently. This mode of dispersal leads to potential conflicts, as kin selection theory predicts that resident workers should favour nestmate queens over foreign queens. Here we compared the survival of foreign and resident queens as well as their relative reproductive share. We used the ant Formica exsecta to construct colonies consisting of one queen with workers related to this resident queen and introduced a foreign queen. We found that the survival of foreign queens did not differ from that of resident queens over a period of 136 days. However, the genetic analyses revealed that resident queens produced a 1.5-fold higher number of offspring than introduced queens, and had an equal or higher share in 80% of the colonies. These data indicate that some discrimination can occur against dispersing individuals and that dispersal can thus have costs in terms of direct reproduction for dispersing queens.

Detecting the number of clusters of individuals using the software STRUCTURE: a simulation study.

The identification of genetically homogeneous groups of individuals is a long standing issue in population genetics. A recent Bayesian algorithm implemented in the software STRUCTURE allows the identification of such groups. However, the ability of this algorithm to detect the true number of clusters (K) in a sample of individuals when patterns of dispersal among populations are not homogeneous has not been tested. The goal of this study is to carry out such tests, using various dispersal scenarios from data generated with an individual-based model. We found that in most cases the estimated 'log probability of data' does not provide a correct estimation of the number of clusters, K. However, using an ad hoc statistic DeltaK based on the rate of change in the log probability of data between successive K values, we found that STRUCTURE accurately detects the uppermost hierarchical level of structure for the scenarios we tested. As might be expected, the results are sensitive to the type of genetic marker used (AFLP vs. microsatellite), the number of loci scored, the number of populations sampled, and the number of individuals typed in each sample.

Selecting control genes for RT-QPCR using public microarray data.

Background: Gene expression analysis has emerged as a major biological research area, with real-time quantitative reverse transcription PCR (RT-QPCR) being one of the most accurate and widely used techniques for expression profiling of selected genes. In order to obtain results that are comparable across assays, a stable normalization strategy is required. In general, the normalization of PCR measurements between different samples uses one to several control genes (e. g. housekeeping genes), from which a baseline reference level is constructed. Thus, the choice of the control genes is of utmost importance, yet there is not a generally accepted standard technique for screening a large number of candidates and identifying the best ones. Results: We propose a novel approach for scoring and ranking candidate genes for their suitability as control genes. Our approach relies on publicly available microarray data and allows the combination of multiple data sets originating from different platforms and/or representing different pathologies. The use of microarray data allows the screening of tens of thousands of genes, producing very comprehensive lists of candidates. We also provide two lists of candidate control genes: one which is breast cancer-specific and one with more general applicability. Two genes from the breast cancer list which had not been previously used as control genes are identified and validated by RT-QPCR. Open source R functions are available at http://www.isrec.isb-sib.ch/similar to vpopovic/research/ Conclusion: We proposed a new method for identifying candidate control genes for RT-QPCR which was able to rank thousands of genes according to some predefined suitability criteria and we applied it to the case of breast cancer. We also empirically showed that translating the results from microarray to PCR platform was achievable.

Communally breeding Bechstein's bats have a stable social system that is independent from the postglacial history and location of the populations.

Investigating macro-geographical genetic structures of animal populations is crucial to reconstruct population histories and to identify significant units for conservation. This approach may also provide information about the intraspecific flexibility of social systems. We investigated the history and current structure of a large number of populations in the communally breeding Bechstein's bat (Myotis bechsteinii). Our aim was to understand which factors shape the species' social system over a large ecological and geographical range. Using sequence data from one coding and one noncoding mitochondrial DNA region, we identified the Balkan Peninsula as the main and probably only glacial refugium of the species in Europe. Sequence data also suggest the presence of a cryptic taxon in the Caucasus and Anatolia. In a second step, we used seven autosomal and two mitochondrial microsatellite loci to compare population structures inside and outside of the Balkan glacial refugium. Central European and Balkan populations both were more strongly differentiated for mitochondrial DNA than for nuclear DNA, had higher genetic diversities and lower levels of relatedness at swarming (mating) sites than in maternity (breeding) colonies, and showed more differentiation between colonies than between swarming sites. All these suggest that populations are shaped by strong female philopatry, male dispersal, and outbreeding throughout their European range. We conclude that Bechstein's bats have a stable social system that is independent from the postglacial history and location of the populations. Our findings have implications for the understanding of the benefits of sociality in female Bechstein's bats and for the conservation of this endangered species.

HIV and STI surveillance in Northern Ireland 2010: An analysis of data for the calendar year 2009

This annual analysis of data provides an overview of HIV and STI epidemiology in Northern Ireland for the calendar year 2009. Information from a variety of sources is collated and analysed in detail, while any evident trends over time are highlightedwithgraphs and tables. As well as a general summary of STI diagnoses and a number of overall conclusions, the report looks specifically at each of the following STIs: chlamydia, gonorrhoea, genital herpes, genital warts, syphilis, lymphogranuloma venereum (LGV) and HIV.

Inca expansion and parasitism in the Lluta Valley: preliminary data

Assessing the impact of cultural change on parasitism has been a central goal in archaeoparasitology. The influence of civilization and the development of empires on parasitism has not been evaluated. Presented here is a preliminary analysis of the change in human parasitism associated with the Inca conquest of the Lluta Valley in Northern Chile. Changes in parasite prevalence are described. It can be seen that the change in life imposed on the inhabitants of the Lluta Valley by the Incas caused an increase in parasitism.