Influence of the LILRA3 Deletion on Multiple Sclerosis Risk: Original Data and Meta-Analysis.

BACKGROUND Multiple sclerosis (MS) is a neurodegenerative, autoimmune disease of the central nervous system. Genome-wide association studies (GWAS) have identified over hundred polymorphisms with modest individual effects in MS susceptibility and they have confirmed the main individual effect of the Major Histocompatibility Complex. Additional risk loci with immunologically relevant genes were found significantly overrepresented. Nonetheless, it is accepted that most of the genetic architecture underlying susceptibility to the disease remains to be defined. Candidate association studies of the leukocyte immunoglobulin-like receptor LILRA3 gene in MS have been repeatedly reported with inconsistent results. OBJECTIVES In an attempt to shed some light on these controversial findings, a combined analysis was performed including the previously published datasets and three newly genotyped cohorts. Both wild-type and deleted LILRA3 alleles were discriminated in a single-tube PCR amplification and the resulting products were visualized by their different electrophoretic mobilities. RESULTS AND CONCLUSION Overall, this meta-analysis involved 3200 MS patients and 3069 matched healthy controls and it did not evidence significant association of the LILRA3 deletion [carriers of LILRA3 deletion: p = 0.25, OR (95% CI) = 1.07 (0.95-1.19)], even after stratification by gender and the HLA-DRB1*15:01 risk allele.

The application of trend surface models to the analysis of time factors in Swiss cancer mortality.

To study different temporal components on cancer mortality (age, period and cohort) methods of graphic representation were applied to Swiss mortality data from 1950 to 1984. Maps using continuous slopes ("contour maps") and based on eight tones of grey according to the absolute distribution of rates were used to represent the surfaces defined by the matrix of various age-specific rates. Further, progressively more complex regression surface equations were defined, on the basis of two independent variables (age/cohort) and a dependent one (each age-specific mortality rate). General patterns of trends in cancer mortality were thus identified, permitting definition of important cohort (e.g., upwards for lung and other tobacco-related neoplasms, or downwards for stomach) or period (e.g., downwards for intestines or thyroid cancers) effects, besides the major underlying age component. For most cancer sites, even the lower order (1st to 3rd) models utilised provided excellent fitting, allowing immediate identification of the residuals (e.g., high or low mortality points) as well as estimates of first-order interactions between the three factors, although the parameters of the main effects remained still undetermined. Thus, the method should be essentially used as summary guide to illustrate and understand the general patterns of age, period and cohort effects in (cancer) mortality, although they cannot conceptually solve the inherent problem of identifiability of the three components.

On the use of spatially discrete data to compute energy and mass balance

In many practical applications the state of field soils is monitored by recording the evolution of temperature and soil moisture at discrete depths. We theoretically investigate the systematic errors that arise when mass and energy balances are computed directly from these measurements. We show that, even with no measurement or model errors, large residuals might result when finite difference approximations are used to compute fluxes and storage term. To calculate the limits set by the use of spatially discrete measurements on the accuracy of balance closure, we derive an analytical solution to estimate the residual on the basis of the two key parameters: the penetration depth and the distance between the measurements. When the thickness of the control layer for which the balance is computed is comparable to the penetration depth of the forcing (which depends on the thermal diffusivity and on the forcing period) large residuals arise. The residual is also very sensitive to the distance between the measurements, which requires accurately controlling the position of the sensors in field experiments. We also demonstrate that, for the same experimental setup, mass residuals are sensitively larger than the energy residuals due to the nonlinearity of the moisture transport equation. Our analysis suggests that a careful assessment of the systematic mass error introduced by the use of spatially discrete data is required before using fluxes and residuals computed directly from field measurements.

A genome-to-genome analysis of associations between human genetic variation, HIV-1 sequence diversity, and viral control.

HIV-1 sequence diversity is affected by selection pressures arising from host genomic factors. Using paired human and viral data from 1071 individuals, we ran >3000 genome-wide scans, testing for associations between host DNA polymorphisms, HIV-1 sequence variation and plasma viral load (VL), while considering human and viral population structure. We observed significant human SNP associations to a total of 48 HIV-1 amino acid variants (p<2.4 × 10(-12)). All associated SNPs mapped to the HLA class I region. Clinical relevance of host and pathogen variation was assessed using VL results. We identified two critical advantages to the use of viral variation for identifying host factors: (1) association signals are much stronger for HIV-1 sequence variants than VL, reflecting the 'intermediate phenotype' nature of viral variation; (2) association testing can be run without any clinical data. The proposed genome-to-genome approach highlights sites of genomic conflict and is a strategy generally applicable to studies of host-pathogen interaction. DOI:http://dx.doi.org/10.7554/eLife.01123.001.

Prenatal detection of congenital renal malformations by fetal ultrasonographic examination: an analysis of 709,030 births in 12 European countries.

The study was performed to evaluate the prevalence of prenatal ultrasound diagnoses for renal anomalies in 20 registries of 12 European countries, and to compare the different prenatal scanning policies. Standardized data were acquired from 709,030 livebirths, stillbirths, and induced abortions during the study period of 2.5 years and transmitted for central analysis. At least one renal malformation was diagnosed in 1130 infants and fetuses. Prenatal diagnosis (PD) was given in 81.8% of all cases, 29% of these pregnancies were terminated. The highest detection rate was reported for unilateral multicystic dysplastic kidneys with 97% (102/105). An early diagnosis was documented for exstrophy of bladder at a mean gestational age of 18.5 weeks. Dilatations of the upper urinary tract were seen late in pregnancy at 28.3 weeks. Terminations of pregnancies (TOP) were performed in 67% (58/86) of the detected bilateral renal agenesis/dysgenesis, but only 4% of the unilateral multicystic dysplastic renal malformations (4/102). In about 1/3 of the cases, renal malformations are within the category of associated malformations, which include multiple non-syndromal malformations, chromosomal aberrations, and non-chromosomal syndromes. Renal malformations were detected in 2/3 of the associated category by the first prenatal ultrasound scan. Detection rates vary in the different countries of the European community due to diverse policies, ethical, and religious background. Countries with no routine ultrasound show the lowest rates in detection, and termination of pregnancy. Prenatally detected renal malformations should result in a careful examination for further anomalies. Prenatal ultrasound fulfills the needs of screening examinations and is a good tool in detecting lethal and severe renal malformations.

Non-Destructive Evaluation of Iowa Pavements Phase 2: Development of a Fully Automated Software System for Rapid Analysis/Processing of the Falling Weight Deflectometer Data, 2009

The Office of Special Investigations at Iowa Department of Transportation (DOT) collects FWD data on regular basis to evaluate pavement structural conditions. The primary objective of this study was to develop a fully-automated software system for rapid processing of the FWD data along with a user manual. The software system automatically reads the FWD raw data collected by the JILS-20 type FWD machine that Iowa DOT owns, processes and analyzes the collected data with the rapid prediction algorithms developed during the phase I study. This system smoothly integrates the FWD data analysis algorithms and the computer program being used to collect the pavement deflection data. This system can be used to assess pavement condition, estimate remaining pavement life, and eventually help assess pavement rehabilitation strategies by the Iowa DOT pavement management team. This report describes the developed software in detail and can also be used as a user-manual for conducting simulation studies and detailed analyses. *********************** Large File ***********************

Addressing trypsin bias in large scale (phospho)proteome analysis by size exclusion chromatography and secondary digestion of large post-trypsin peptides.

In the vast majority of bottom-up proteomics studies, protein digestion is performed using only mammalian trypsin. Although it is clearly the best enzyme available, the sole use of trypsin rarely leads to complete sequence coverage, even for abundant proteins. It is commonly assumed that this is because many tryptic peptides are either too short or too long to be identified by RPLC-MS/MS. We show through in silico analysis that 20-30% of the total sequence of three proteomes (Schizosaccharomyces pombe, Saccharomyces cerevisiae, and Homo sapiens) is expected to be covered by Large post-Trypsin Peptides (LpTPs) with M(r) above 3000 Da. We then established size exclusion chromatography to fractionate complex yeast tryptic digests into pools of peptides based on size. We found that secondary digestion of LpTPs followed by LC-MS/MS analysis leads to a significant increase in identified proteins and a 32-50% relative increase in average sequence coverage compared to trypsin digestion alone. Application of the developed strategy to analyze the phosphoproteomes of S. pombe and of a human cell line identified a significant fraction of novel phosphosites. Overall our data indicate that specific targeting of LpTPs can complement standard bottom-up workflows to reveal a largely neglected portion of the proteome.

Combined use of the GGSFT data base and on Board Marine Collected Data to Model the Moho Beneath the Powell Basin, Antarctica

The Powell Basin is a small oceanic basin located at the NE end of the Antarctic Peninsula developed during the Early Miocene and mostly surrounded by the continental crusts of the South Orkney Microcontinent, South Scotia Ridge and Antarctic Peninsula margins. Gravity data from the SCAN 97 cruise obtained with the R/V Hespérides and data from the Global Gravity Grid and Sea Floor Topography (GGSFT) database (Sandwell and Smith, 1997) are used to determine the 3D geometry of the crustal-mantle interface (CMI) by numerical inversion methods. Water layer contribution and sedimentary effects were eliminated from the Free Air anomaly to obtain the total anomaly. Sedimentary effects were obtained from the analysis of existing and new SCAN 97 multichannel seismic profiles (MCS). The regional anomaly was obtained after spectral and filtering processes. The smooth 3D geometry of the crustal mantle interface obtained after inversion of the regional anomaly shows an increase in the thickness of the crust towards the continental margins and a NW-SE oriented axis of symmetry coinciding with the position of an older oceanic spreading axis. This interface shows a moderate uplift towards the western part and depicts two main uplifts to the northern and eastern sectors.

Quantitative integration of high-resolution hydrogeophysical data through Monte-Carlo-type conditional simulations

Geophysical techniques can help to bridge the inherent gap with regard to spatial resolution and the range of coverage that plagues classical hydrological methods. This has lead to the emergence of the new and rapidly growing field of hydrogeophysics. Given the differing sensitivities of various geophysical techniques to hydrologically relevant parameters and their inherent trade-off between resolution and range the fundamental usefulness of multi-method hydrogeophysical surveys for reducing uncertainties in data analysis and interpretation is widely accepted. A major challenge arising from such endeavors is the quantitative integration of the resulting vast and diverse database in order to obtain a unified model of the probed subsurface region that is internally consistent with all available data. To address this problem, we have developed a strategy towards hydrogeophysical data integration based on Monte-Carlo-type conditional stochastic simulation that we consider to be particularly suitable for local-scale studies characterized by high-resolution and high-quality datasets. Monte-Carlo-based optimization techniques are flexible and versatile, allow for accounting for a wide variety of data and constraints of differing resolution and hardness and thus have the potential of providing, in a geostatistical sense, highly detailed and realistic models of the pertinent target parameter distributions. Compared to more conventional approaches of this kind, our approach provides significant advancements in the way that the larger-scale deterministic information resolved by the hydrogeophysical data can be accounted for, which represents an inherently problematic, and as of yet unresolved, aspect of Monte-Carlo-type conditional simulation techniques. We present the results of applying our algorithm to the integration of porosity log and tomographic crosshole georadar data to generate stochastic realizations of the local-scale porosity structure. Our procedure is first tested on pertinent synthetic data and then applied to corresponding field data collected at the Boise Hydrogeophysical Research Site near Boise, Idaho, USA.

Rapid Sequestration of Leishmania mexicana by Neutrophils Contributes to the Development of Chronic Lesion.

The protozoan Leishmania mexicana parasite causes chronic non-healing cutaneous lesions in humans and mice with poor parasite control. The mechanisms preventing the development of a protective immune response against this parasite are unclear. Here we provide data demonstrating that parasite sequestration by neutrophils is responsible for disease progression in mice. Within hours of infection L. mexicana induced the local recruitment of neutrophils, which ingested parasites and formed extracellular traps without markedly impairing parasite survival. We further showed that the L. mexicana-induced recruitment of neutrophils impaired the early recruitment of dendritic cells at the site of infection as observed by intravital 2-photon microscopy and flow cytometry analysis. Indeed, infection of neutropenic Genista mice and of mice depleted of neutrophils at the onset of infection demonstrated a prominent role for neutrophils in this process. Furthermore, an increase in monocyte-derived dendritic cells was also observed in draining lymph nodes of neutropenic mice, correlating with subsequent increased frequency of IFNγ-secreting T helper cells, and better parasite control leading ultimately to complete healing of the lesion. Altogether, these findings show that L. mexicana exploits neutrophils to block the induction of a protective immune response and impairs the control of lesion development. Our data thus demonstrate an unanticipated negative role for these innate immune cells in host defense, suggesting that in certain forms of cutaneous leishmaniasis, regulating neutrophil recruitment could be a strategy to promote lesion healing.

Development of an enantioselective assay for simultaneous separation of venlafaxine and O-desmethylvenlafaxine by micellar electrokinetic chromatography-tandem mass spectrometry: Application to the analysis of drug-drug interaction.

To-date, there has been no effective chiral capillary electrophoresis-mass spectrometry (CE-MS) method reported for the simultaneous enantioseparation of the antidepressant drug, venlafaxine (VX) and its structurally-similar major metabolite, O-desmethylvenlafaxine (O-DVX). This is mainly due to the difficulty of identifying MS compatible chiral selector, which could provide both high enantioselectivity and sensitive MS detection. In this work, poly-sodium N-undecenoyl-L,L-leucylalaninate (poly-L,L-SULA) was employed as a chiral selector after screening several dipeptide polymeric chiral surfactants. Baseline separation of both O-DVX and VX enantiomers was achieved in 15min after optimizing the buffer pH, poly-L,L-SULA concentration, nebulizer pressure and separation voltage. Calibration curves in spiked plasma (recoveries higher than 80%) were linear over the concentration range 150-5000ng/mL for both VX and O-DVX. The limit of detection (LOD) was found to be as low as 30ng/mL and 21ng/mL for O-DVX and VX, respectively. This method was successfully applied to measure the plasma concentrations of human volunteers receiving VX or O-DVX orally when co-administered without and with indinivar therapy. The results suggest that micellar electrokinetic chromatography electrospray ionization-tandem mass spectrometry (MEKC-ESI-MS/MS) is an effective low cost alternative technique for the pharmacokinetics and pharmacodynamics studies of both O-DVX and VX enantiomers. The technique has potential to identify drug-drug interaction involving VX and O-DVX enantiomers while administering indinivar therapy.

Panel Data Stochastic Convergence Analysis of the Mexican Regions

The stochastic convergence amongst Mexican Federal entities is analyzed in panel data framework. The joint consideration of cross-section dependence and multiple structural breaks is required to ensure that the statistical inference is based on statistics with good statistical properties. Once these features are accounted for, evidence in favour of stochastic convergence is found. Since stochastic convergence is a necessary, yet insufficient condition for convergence as predicted by economic growth models, the paper also investigates whether-convergence process has taken place. We found that the Mexican states have followed either heterogeneous convergence patterns or divergence process throughout the analyzed period.

Combined experimental powder X-ray diffraction and DFT data to obtain the lowest energy molecular conformation of friedelin

Friedelin molecular conformers were obtained by Density Functional Theory (DFT) and by ab initio structure determination from powder X-ray diffraction. Their conformers with the five rings in chair-chair-chair-boat-boat, and with all rings in chair, are energy degenerated in gas-phase according to DFT results. The powder diffraction data reveals that rings A, B and C of friedelin are in chair, and rings D and E in boat-boat, conformation. The high correlation values among powder diffraction data, DFT and reported single-crystal data indicate that the use of conventional X-ray diffractometer can be applied in routine laboratory analysis in the absence of a single-crystal diffractometer.

Brain Tissue Classification from Multispectral MRI by Wavelet based Principal Component Analysis

In this paper, we propose a multispectral analysis system using wavelet based Principal Component Analysis (PCA), to improve the brain tissue classification from MRI images. Global transforms like PCA often neglects significant small abnormality details, while dealing with a massive amount of multispectral data. In order to resolve this issue, input dataset is expanded by detail coefficients from multisignal wavelet analysis. Then, PCA is applied on the new dataset to perform feature analysis. Finally, an unsupervised classification with Fuzzy C-Means clustering algorithm is used to measure the improvement in reproducibility and accuracy of the results. A detailed comparative analysis of classified tissues with those from conventional PCA is also carried out. Proposed method yielded good improvement in classification of small abnormalities with high sensitivity/accuracy values, 98.9/98.3, for clinical analysis. Experimental results from synthetic and clinical data recommend the new method as a promising approach in brain tissue analysis.