PSEUDOMARKER: a powerful program for joint linkage and/or linkage disequilibrium analysis on mixtures of singletons and related individuals

A decade ago, there was widespread enthusiasm for the prospects of genome-wide association studies to identify common variants related to common chronic diseases using samples of unrelated individuals from populations. Although technological advancements allow us to query more than a million SNPs across the genome at low cost, a disappointingly small fraction of the genetic portion of common disease etiology has been uncovered. This has led to the hypothesis that less frequent variants might be involved, stimulating a renaissance of the traditional approach of seeking genes using multiplex families from less diverse populations. However, by using the modern genotyping and sequencing technology, we can now look not just at linkage, but jointly at linkage and linkage disequilibrium (LD) in such samples. Software methods that can look simultaneously at linkage and LD in a powerful and robust manner have been lacking. Most algorithms cannot jointly analyze datasets involving families of varying structures in a statistically or computationally efficient manner. We have implemented previously proposed statistical algorithms in a user-friendly software package, PSEUDOMARKER. This paper is an announcement of this software package. We describe the motivation behind the approach, the statistical methods, and software, and we briefly demonstrate PSEUDOMARKER's advantages over other packages by example.     

Thermal effects of mobile phone RF fields on children: a provocation study

The aim of this study was to examine thermal and local blood flow responses in the head area of the preadolescent boys during exposure to radiofrequency (RF) electromagnetic fields produced by a GSM mobile phone. The design was a double-blinded sham-controlled study of 26 boys, aged 14-15 years. The SAR distribution was calculated and modelled in detail. The duration of the sham periods and exposures with GSM 900 phone was 15 min each, and the tests were carried out in a climatic chamber in controlled thermoneutral conditions. The ear canal temperatures were registered from both ear canals, and the skin temperatures at several sites of the head, trunk and extremities. The local cerebral blood flow was monitored by a near-infrared spectroscopy (NIRS), and the autonomic nervous system function by recordings of ECG and continuous blood pressure. During the short-term RF exposure, local cerebral blood flow did not change, the ear canal temperature did not increase significantly and autonomic nervous system was not interfered. The strengths of this study were the age of the population, multifactorial physiological monitoring and strictly controlled thermal environment. The limitations of the study were large inter-individual variation in the physiological responses, and short duration of the exposure. Longer provocation protocols, however, might cause in children distress related confounding physiological responses.     

Construction and structural analysis of tethered lipid bilayer containing photosynthetic antenna proteins for functional analysis

The construction and structural analysis of a tethered planar lipid bilayer containing bacterial photosynthetic membrane proteins, light-harvesting complex 2 (LH2), and light-harvesting core complex (LH1-RC) is described and establishes this system as an experimental platform for their functional analysis. The planar lipid bilayer containing LH2 and/or LH1-RC complexes was successfully formed on an avidin-immobilized coverglass via an avidin-biotin linkage. Atomic force microscopy (AFM) showed that a smooth continuous membrane was formed there. Lateral diffusion of these membrane proteins, observed by a fluorescence recovery after photobleaching (FRAP), is discussed in terms of the membrane architecture. Energy transfer from LH2 to LH1-RC within the tethered membrane was observed by steady-state fluorescence spectroscopy, indicating that the tethered membrane can mimic the natural situation.     

Methane-cycling microbial communities and methane emission in natural and restored peatlands

We addressed how restoration of forestry-drained peatlands affects CH(4)-cycling microbes. Despite similar community compositions, the abundance of methanogens and methanotrophs was lower in restored than in natural sites and correlated with CH(4) emission. Poor establishment of methanogens may thus explain low CH(4) emissions on restored peatlands even 10 to 12 years after restoration.     

Lentiviral vector-derived shRNAs confer enhanced suppression of Semliki forest virus replication in BHK-21 cells compared to shRNAs expressed from plasmids

Semliki forest virus (SFV) is a pathogen causing lethal encephalitis in laboratory mice. In this study, we obtained three short hairpin RNAs (shRNAs) which could specifically target SFV sequence in GFP reporting systems and effectively suppress SFV replication in luciferase-containing reporter virus system. At a multiplicity of infection (MOI) of 0.001, the luciferase reporter activity was reduced by 78–92% by shRNA expression plasmids and virus yields reduced 2 to 10-fold at 20 h post-infection. When lentiviral vector-derived shRNAs were employed, the virus titers decreased 8 to 126-fold at 24 h post-infection and 6 to 19-fold at 48 h post-infection and the cell survival was prolonged. These data formed the basis for further in vivo studies of RNA interference in mouse models.     

Wrapper-based selection of genetic features in genome-wide association studies through fast matrix operations

ABSTRACT: BACKGROUND: Through the wealth of information contained within them, genome-wide association studies (GWAS) have the potential to provide researchers with a systematic means of associating genetic variants with a wide variety of disease phenotypes. Due to the limitations of approaches that have analyzed single variants one at a time, it has been proposed that the genetic basis of these disorders could be determined through detailed analysis of the genetic variants themselves and in conjunction with one another. The construction of models that account for these subsets of variants requires methodologies that generate predictions based on the total risk of a particular group of polymorphisms. However, due to the excessive number of variants, constructing these types of models has so far been computationally infeasible. RESULTS: We have implemented an algorithm, known as greedy RLS, that we use to perform the first known wrapper-based feature selection on the genome-wide level. The running time of greedy RLS grows linearly in the number of training examples, the number of features in the original data set, and the number of selected features. This speed is achieved through computational short-cuts based on matrix calculus. Since the memory consumption in present-day computers can form an even tighter bottleneck than running time, we also developed a space efficient variation of greedy RLS which trades running time for memory. These approaches are then compared to traditional wrapper-based feature selection implementations based on support vector machines (SVM) to reveal the relative speed-up and to assess the feasibility of the new algorithm. As a proof of concept, we apply greedy RLS to the Hypertension - UK National Blood Service WTCCC dataset and select the most predictive variants using 3-fold external cross-validation in less than 26 minutes on a high end desktop. On this dataset, we also show that greedy RLS has a better classification performance on independent test data than a classifier trained using features selected by a statistical p-value-based filter, which is currently the most popular approach for constructing predictive models in GWAS. CONCLUSIONS: Greedy RLS is the first known implementation of a machine learning based method with the capability to conduct a wrapper-based feature selection on an entire GWAS containing several thousand examples and over 400,000 variants. In our experiments, greedy RLS selected a highly predictive subset of genetic variants in a fraction of the time spent by wrapper-based selection methods used together with SVM classifiers. The proposed algorithms are freely available as part of the RLScore software library at http://users.utu.fi/aatapa/RLScore/.     

Exchange of CO2, CH4 and N2O between the atmosphere and two northern boreal ponds with catchments dominated by peatlands or forests

Concentrations of carbon dioxide (CO₂), methane (CH₄) and nitrous oxide (N₂O) in the water column and their exchange at the water/air interface were studied during the open water period in two freshwater ponds with different catchment characteristics in the northern boreal zone in Finland; either peatlands or coniferous upland forests dominated the catchment of the ponds. Both ponds were supersaturated with dissolved CO₂ and CH₄ with respect to the equilibrium with the atmosphere, but were close to the equilibrium with N₂O. The mean CO₂ efflux from the pond was higher in the peatland-dominated catchment (22 mg m^–2 h^–1) than in the forested catchment (0.7 mg m^–2 h^–1), whereas the mean CH₄ emissions were similar (7.6 and 3.5 mg m^–2 d^–1, respectively). The fluxes of N₂O were generally negligible. The higher CO₂ concentrations and efflux in the pond with the peatland-dominated catchment were attributed to a greater input of allochthonous carbon to that pond from its catchment due to its higher water colour and higher total organic carbon (TOC) concentration. The water pH, which also differed between the ponds, could additionally affect the CO₂ dynamics. Since the catchment characteristics can regulate aquatic carbon cycles, catchment-scale studies are needed to attain a deeper understanding of the aquatic greenhouse gas dynamics.     

Particle Size, Moisture, and Fluidization Variations Described by Indirect In-line Physical Measurements of Fluid Bed Granulation

The aim of this study was to evaluate an instrumentation system for a bench scale fluid bed granulator to determine the parameters expressing the changing conditions during the spraying phase of a fluid bed process. The study focused mainly on four in-line measurements (dependent variables): fluidization parameter (calculated by inlet air flow rate and rotor speed), pressure difference over the upper filters, pressure difference over the granules (lower filter), and temperature of the fluidizing mass. In-line particle size measured by the spatial filtering technique was an essential predictor variable. Other physical process measurements of the automated granulation system, 25 direct and 12 derived parameters, were also utilized for multivariate modeling. The correlation and partial least squares analyses revealed significant relationships between various process parameters highlighting the particle size, moisture, and fluidization effect. Fluidization parameter and pressure difference over upper filters were found to correlate with in-line particle size and therefore could be used as estimates of particle size during granulation. The pressure difference over the granules and the temperature of the fluidizing mass expressed the moisture conditions of wet granulation. The instrumentation system evaluated here is an invaluable aid to gaining more control for fluid bed processing to obtain repeatable granules for further processing.     

A New Rapid On-Line Imaging Method to Determine Particle Size Distribution of Granules

The purpose of this research was to study the feasibility of the new image analysis method in the particle size determination of the granules. The method is capable of forming a three-dimensional topographic image of a sample surface from a digital picture. In the method, a flat granule bed surface was illuminated from three different directions, using the three primary colors (red, green, and blue). One color picture was taken by a digital camera, after which a topographic image of the object surface was constructed. The particle size distribution was then calculated from the image data. The particle size analysis method was tested both off-line and on-line. Off-line particle size measurement results determined by the image analysis method corresponded quite well to those of sieve analysis in the size fraction range 250–1,000 μm. In on-line application, images were successfully retrieved and median granule size trend could be calculated and followed during fluid bed granulations.