A RT-PCR method for selective amplification and phenotypic characterization of all three serotypes of Sabin-related polioviruses from viral mixtures

Outbreaks caused by vaccine-derived polioviruses are challenging the final eradication of paralytic poliomyelitis. Therefore, the surveillance of the acute flaccid paralysis cases based on poliovirus isolation and characterization remains an essential activity. Due to the use of trivalent oral poliovirus vaccine (OPV), mixtures containing more than one serotype of Sabin-related polioviruses are frequently isolated from clinical samples. Because each poliovirus isolate needs to be individually analyzed, we designed polymerase chain reaction primers that can selectively distinguish and amplify a genomic segment of the three Sabin-related poliovirus serotypes present in mixtures, thus, optimizing the diagnosis and providing prompt information to support epidemiologic actions.

Object-oriented Bayesian networks for evaluating DIP-STR profiling results from unbalanced DNA mixtures.

The genetic characterization of unbalanced mixed stains remains an important area where improvement is imperative. In fact, with current methods for DNA analysis (Polymerase Chain Reaction with the SGM Plus™ multiplex kit), it is generally not possible to obtain a conventional autosomal DNA profile of the minor contributor if the ratio between the two contributors in a mixture is smaller than 1:10. This is a consequence of the fact that the major contributor's profile 'masks' that of the minor contributor. Besides known remedies to this problem, such as Y-STR analysis, a new compound genetic marker that consists of a Deletion/Insertion Polymorphism (DIP), linked to a Short Tandem Repeat (STR) polymorphism, has recently been developed and proposed elsewhere in literature [1]. The present paper reports on the derivation of an approach for the probabilistic evaluation of DIP-STR profiling results obtained from unbalanced DNA mixtures. The procedure is based on object-oriented Bayesian networks (OOBNs) and uses the likelihood ratio as an expression of the probative value. OOBNs are retained in this paper because they allow one to provide a clear description of the genotypic configuration observed for the mixed stain as well as for the various potential contributors (e.g., victim and suspect). These models also allow one to depict the assumed relevance relationships and perform the necessary probabilistic computations.

Overcoming the rare species modelling paradox: test of a novel hierarchical framework with an Iberian endemic plant

Rare species have restricted geographic ranges, habitat specialization, and/or small population sizes. Datasets on rare species distribution usually have few observations, limited spatial accuracy and lack of valid absences; conversely they provide comprehensive views of species distributions allowing to realistically capture most of their realized environmental niche. Rare species are the most in need of predictive distribution modelling but also the most difficult to model. We refer to this contrast as the "rare species modelling paradox" and propose as a solution developing modelling approaches that deal with a sufficiently large set of predictors, ensuring that statistical models aren't overfitted. Our novel approach fulfils this condition by fitting a large number of bivariate models and averaging them with a weighted ensemble approach. We further propose that this ensemble forecasting is conducted within a hierarchic multi-scale framework. We present two ensemble models for a test species, one at regional and one at local scale, each based on the combination of 630 models. In both cases, we obtained excellent spatial projections, unusual when modelling rare species. Model results highlight, from a statistically sound approach, the effects of multiple drivers in a same modelling framework and at two distinct scales. From this added information, regional models can support accurate forecasts of range dynamics under climate change scenarios, whereas local models allow the assessment of isolated or synergistic impacts of changes in multiple predictors. This novel framework provides a baseline for adaptive conservation, management and monitoring of rare species at distinct spatial and temporal scales.

Hierarchical analyses of genetic differentiation in a hybrid zone of Sorex araneus (Insectivora : Soricidae)

Microsatellites are used to unravel the fine-scale genetic structure of a hybrid zone between chromosome races Valais and Cordon of the common shrew (Sorex araneus) located in the French Alps. A total of 269 individuals collected between 1992 and 1995 was typed for seven microsatellite loci. A modified version of the classical multiple correspondence analysis is carried out. This analysis clearly shows the dichotomy between the two races. Several approaches are used to study genetic structuring. Gene flow is clearly reduced between these chromosome races and is estimated at one migrant every two generations using X-statistics and one migrant per generation using F-statistics. Hierarchical F- and R-statistics are compared and their efficiency to detect inter- and intraracial patterns of divergence is discussed. Within-race genetic structuring is significant, but remains weak. F-ST displays similar values on both sides of the hybrid zone, although no environmental barriers are found on the Cordon side, whereas the Valais side is divided by several mountain rivers. We introduce the exact G-test to microsatellite data which proved to be a powerful test to detect genetic differentiation within as well as among races. The genetic background of karyotypic hybrids was compared with the genetic background of pure parental forms using a CRT-MCA. Our results indicate that, without knowledge of the karyotypes, we would not have been able to distinguish these hybrids from karyotypically pure samples.

A hierarchical approach to model parameter optimization for developmental systems.

In the context of Systems Biology, computer simulations of gene regulatory networks provide a powerful tool to validate hypotheses and to explore possible system behaviors. Nevertheless, modeling a system poses some challenges of its own: especially the step of model calibration is often difficult due to insufficient data. For example when considering developmental systems, mostly qualitative data describing the developmental trajectory is available while common calibration techniques rely on high-resolution quantitative data. Focusing on the calibration of differential equation models for developmental systems, this study investigates different approaches to utilize the available data to overcome these difficulties. More specifically, the fact that developmental processes are hierarchically organized is exploited to increase convergence rates of the calibration process as well as to save computation time. Using a gene regulatory network model for stem cell homeostasis in Arabidopsis thaliana the performance of the different investigated approaches is evaluated, documenting considerable gains provided by the proposed hierarchical approach.

Hierarchical categorisation of tags for delicious

In the scenario of social bookmarking, a user browsing the Web bookmarks web pages and assigns free-text labels (i.e., tags) to them according to their personal preferences. In this technical report, we approach one of the practical aspects when it comes to represent users' interests from their tagging activity, namely the categorization of tags into high-level categories of interest. The reason is that the representation of user profiles on the basis of the myriad of tags available on the Web is certainly unfeasible from various practical perspectives; mainly concerning the unavailability of data to reliably, accurately measure interests across such fine-grained categorisation, and, should the data be available, its overwhelming computational intractability. Motivated by this, our study presents the results of a categorization process whereby a collection of tags posted at Delicious #http://delicious.com# are classified into 200 subcategories of interest.

Blended Cements Improving Concrete Properties Using Environmentally Responsible Mixtures, December 2003

Recent research evaluated the behavior of concrete made with supplementary cementitious materials (SCMs) such as fly ash and ground granulated blast-furnace slag under a variety of conditions. Correlations were found among the source and proportion of the SCMs, curing conditions, concrete set time, maturity, strength development, and cracking potential.

Risk assessment of herbicide mixtures in a large European lake

Lake Geneva is one of the largest European lakes with a surface area of 580 km2. Its catchment area covers 7400 km2, of which approximately 20% is arable land. Monitoring campaigns have been carried out in 2004 and 2005 to determine the contamination of the lake by pesticides. The results highlight the widespread presence of herbicides in water, the measured concentrations for most substances remaining constant in 2004 and 2005. However, for some individual herbicides the concentrations increased drastically (e.g., the herbicide foramsulfuron). We assessed the environmental risk of the herbicides detected in the lake using water quality criteria recently determined for the Swiss environmental protection agency. Furthermore, we assessed the risk of herbicide mixtures, grouped based upon their mode of action. Generally, the risk estimated for all single substances is low, except for some sulfonylurea compounds. For these substances, the measured concentrations are higher than the predicted no-effect concentration. Impact on the flora of the lake can therefore not be excluded. When mixtures of pesticides with similar mode of action are taken into account, the risk remains lower than the mixture water quality criteria for all groups, but can reach as high as one third of this quality criteria. A further step would therefore be to assess the risk of the total pesticide mixture, including similar and dissimilar modes of action

Hierarchical management of carbon sources is regulated similarly by the CbrA/B systems in Pseudomonas aeruginosa and Pseudomonas putida.

The CbrA/B system in pseudomonads is involved in the utilization of carbon sources and carbon catabolite repression (CCR) through the activation of the small RNAs crcZ in Pseudomonas aeruginosa, and crcZ and crcY in Pseudomonas putida. Interestingly, previous works reported that the CbrA/B system activity in P. aeruginosa PAO1 and P. putida KT2442 responded differently to the presence of different carbon sources, thus raising the question of the exact nature of the signal(s) detected by CbrA. Here, we demonstrated that the CbrA/B/CrcZ(Y) signal transduction pathway is similarly activated in the two Pseudomonas species. We show that the CbrA sensor kinase is fully interchangeable between the two species and, moreover, responds similarly to the presence of different carbon sources. In addition, a metabolomics analysis supported the hypothesis that CCR responds to the internal energy status of the cell, as the internal carbon/nitrogen ratio seems to determine CCR and non-CCR conditions. The strong difference found in the 2-oxoglutarate/glutamine ratio between CCR and non-CCR conditions points to the close relationship between carbon and nitrogen availability, or the relationship between the CbrA/B and NtrB/C systems, suggesting that both regulatory systems sense the same sort or interrelated signal.

Qualitative and Hierarchical Analysis of Protective Factors against Illicit Use of Doping Substances in Athletes Calling a National Anti-Doping Phone-Help Service

Evidence of a sport-specific hierarchy of protective factors against doping would thus be a powerful aid in adapting information and prevention campaigns to target the characteristics of specific athlete groups, and especially those athletes most vulnerable for doping control. The contents of phone calls to a free and anonymous national anti-doping service called 'ecoute dopage' were analysed (192 bodybuilders, 124 cyclists and 44 footballers). The results showed that the protective factors that emerged from analysis could be categorised into two groups. The first comprised 'Health concerns', 'Respect for the law' and 'Doping controls from the environment' and the second comprised 'Doubts about the effectiveness of illicit products, 'Thinking skills' and 'Doubts about doctors'. The ranking of the factors for the cyclists differed from that of the other athletes. The ordering of factors was 1) respect for the law, 2) doping controls from the environment, 3) health concerns 4) doubts about doctors, and 5) doubts about the effectiveness illicit products. The results are analysed in terms of the ranking in each athlete group and the consequences on the athletes' experience and relationship to doping. Specific prevention campaigns are proposed to limit doping behaviour in general and for each sport.

Developing a Simple and Rapid Test for Monitoring the Heat Evolution of Concrete Mixtures for Both Laboratory and Field Applications, January 2006

Various test methods exist for measuring heat of cement hydration; however, most current methods require expensive equipment, complex testing procedures, and/or extensive time, thus not being suitable for field application. The objectives of this research are to identify, develop, and evaluate a standard test procedure for characterization and quality control of pavement concrete mixtures using a calorimetry technique. This research project has three phases. Phase I was designed to identify the user needs, including performance requirements and precision and bias limits, and to synthesize existing test methods for monitoring the heat of hydration, including device types, configurations, test procedures, measurements, advantages, disadvantages, applications, and accuracy. Phase II was designed to conduct experimental work to evaluate the calorimetry equipment recommended from the Phase I study and to develop a standard test procedure for using the equipment and interpreting the test results. Phase II also includes the development of models and computer programs for prediction of concrete pavement performance based on the characteristics of heat evolution curves. Phase III was designed to study for further development of a much simpler, inexpensive calorimeter for field concrete. In this report, the results from the Phase I study are presented, the plan for the Phase II study is described, and the recommendations for Phase III study are outlined. Phase I has been completed through three major activities: (1) collecting input and advice from the members of the project Technical Working Group (TWG), (2) conducting a literature survey, and (3) performing trials at the CP Tech Center’s research lab. The research results indicate that in addition to predicting maturity/strength, concrete heat evolution test results can also be used for (1) forecasting concrete setting time, (2) specifying curing period, (3) estimating risk of thermal cracking, (4) assessing pavement sawing/finishing time, (5) characterizing cement features, (6) identifying incompatibility of cementitious materials, (7) verifying concrete mix proportions, and (8) selecting materials and/or mix designs for given environmental conditions. Besides concrete materials and mix proportions, the configuration of the calorimeter device, sample size, mixing procedure, and testing environment (temperature) also have significant influences on features of concrete heat evolution process. The research team has found that although various calorimeter tests have been conducted for assorted purposes and the potential uses of calorimeter tests are clear, there is no consensus on how to utilize the heat evolution curves to characterize concrete materials and how to effectively relate the characteristics of heat evolution curves to concrete pavement performance. The goal of the Phase II study is to close these gaps.

Patterns of calcium-binding proteins support parallel and hierarchical organization of human auditory areas.

The human primary auditory cortex (AI) is surrounded by several other auditory areas, which can be identified by cyto-, myelo- and chemoarchitectonic criteria. We report here on the pattern of calcium-binding protein immunoreactivity within these areas. The supratemporal regions of four normal human brains (eight hemispheres) were processed histologically, and serial sections were stained for parvalbumin, calretinin or calbindin. Each calcium-binding protein yielded a specific pattern of labelling, which differed between auditory areas. In AI, defined as area TC [see C. von Economo and L. Horn (1930) Z. Ges. Neurol. Psychiatr.,130, 678-757], parvalbumin labelling was dark in layer IV; several parvalbumin-positive multipolar neurons were distributed in layers III and IV. Calbindin yielded dark labelling in layers I-III and V; it revealed numerous multipolar and pyramidal neurons in layers II and III. Calretinin labelling was lighter than that of parvalbumin or calbindin in AI; calretinin-positive bipolar and bitufted neurons were present in supragranular layers. In non-primary auditory areas, the intensity of labelling tended to become progressively lighter while moving away from AI, with qualitative differences between the cytoarchitectonically defined areas. In analogy to non-human primates, our results suggest differences in intrinsic organization between auditory areas that are compatible with parallel and hierarchical processing of auditory information.