BlastR--fast and accurate database searches for non-coding RNAs.

We present and validate BlastR, a method for efficiently and accurately searching non-coding RNAs. Our approach relies on the comparison of di-nucleotides using BlosumR, a new log-odd substitution matrix. In order to use BlosumR for comparison, we recoded RNA sequences into protein-like sequences. We then showed that BlosumR can be used along with the BlastP algorithm in order to search non-coding RNA sequences. Using Rfam as a gold standard, we benchmarked this approach and show BlastR to be more sensitive than BlastN. We also show that BlastR is both faster and more sensitive than BlastP used with a single nucleotide log-odd substitution matrix. BlastR, when used in combination with WU-BlastP, is about 5% more accurate than WU-BlastN and about 50 times slower. The approach shown here is equally effective when combined with the NCBI-Blast package. The software is an open source freeware available from www.tcoffee.org/blastr.html.

Fast docking using the CHARMM force field with EADock DSS.

The prediction of binding modes (BMs) occurring between a small molecule and a target protein of biological interest has become of great importance for drug development. The overwhelming diversity of needs leaves room for docking approaches addressing specific problems. Nowadays, the universe of docking software ranges from fast and user friendly programs to algorithmically flexible and accurate approaches. EADock2 is an example of the latter. Its multiobjective scoring function was designed around the CHARMM22 force field and the FACTS solvation model. However, the major drawback of such a software design lies in its computational cost. EADock dihedral space sampling (DSS) is built on the most efficient features of EADock2, namely its hybrid sampling engine and multiobjective scoring function. Its performance is equivalent to that of EADock2 for drug-like ligands, while the CPU time required has been reduced by several orders of magnitude. This huge improvement was achieved through a combination of several innovative features including an automatic bias of the sampling toward putative binding sites, and a very efficient tree-based DSS algorithm. When the top-scoring prediction is considered, 57% of BMs of a test set of 251 complexes were reproduced within 2 Å RMSD to the crystal structure. Up to 70% were reproduced when considering the five top scoring predictions. The success rate is lower in cross-docking assays but remains comparable with that of the latest version of AutoDock that accounts for the protein flexibility. © 2011 Wiley Periodicals, Inc. J Comput Chem, 2011.

Cortical fast-spiking parvalbumin interneurons enwrapped in the perineuronal net express the metallopeptidases Adamts8, Adamts15 and Neprilysin.

The in situ hybridization Allen Mouse Brain Atlas was mined for proteases expressed in the somatosensory cerebral cortex. Among the 480 genes coding for protease/peptidases, only four were found enriched in cortical interneurons: Reln coding for reelin; Adamts8 and Adamts15 belonging to the class of metzincin proteases involved in reshaping the perineuronal net (PNN) and Mme encoding for Neprilysin, the enzyme degrading amyloid β-peptides. The pattern of expression of metalloproteases (MPs) was analyzed by single-cell reverse transcriptase multiplex PCR after patch clamp and was compared with the expression of 10 canonical interneurons markers and 12 additional genes from the Allen Atlas. Clustering of these genes by K-means algorithm displays five distinct clusters. Among these five clusters, two fast-spiking interneuron clusters expressing the calcium-binding protein Pvalb were identified, one co-expressing Pvalb with Sst (PV-Sst) and another co-expressing Pvalb with three metallopeptidases Adamts8, Adamts15 and Mme (PV-MP). By using Wisteria floribunda agglutinin, a specific marker for PNN, PV-MP interneurons were found surrounded by PNN, whereas the ones expressing Sst, PV-Sst, were not.

An efficient total variation algorithm for super-resolution in fetal brain MRI with adaptive regularization.

Although fetal anatomy can be adequately viewed in new multi-slice MR images, many critical limitations remain for quantitative data analysis. To this end, several research groups have recently developed advanced image processing methods, often denoted by super-resolution (SR) techniques, to reconstruct from a set of clinical low-resolution (LR) images, a high-resolution (HR) motion-free volume. It is usually modeled as an inverse problem where the regularization term plays a central role in the reconstruction quality. Literature has been quite attracted by Total Variation energies because of their ability in edge preserving but only standard explicit steepest gradient techniques have been applied for optimization. In a preliminary work, it has been shown that novel fast convex optimization techniques could be successfully applied to design an efficient Total Variation optimization algorithm for the super-resolution problem. In this work, two major contributions are presented. Firstly, we will briefly review the Bayesian and Variational dual formulations of current state-of-the-art methods dedicated to fetal MRI reconstruction. Secondly, we present an extensive quantitative evaluation of our SR algorithm previously introduced on both simulated fetal and real clinical data (with both normal and pathological subjects). Specifically, we study the robustness of regularization terms in front of residual registration errors and we also present a novel strategy for automatically select the weight of the regularization as regards the data fidelity term. Our results show that our TV implementation is highly robust in front of motion artifacts and that it offers the best trade-off between speed and accuracy for fetal MRI recovery as in comparison with state-of-the art methods.

Fast and Rigorous Computation of Gene and Pathway Scores from SNP-Based Summary Statistics.

Integrating single nucleotide polymorphism (SNP) p-values from genome-wide association studies (GWAS) across genes and pathways is a strategy to improve statistical power and gain biological insight. Here, we present Pascal (Pathway scoring algorithm), a powerful tool for computing gene and pathway scores from SNP-phenotype association summary statistics. For gene score computation, we implemented analytic and efficient numerical solutions to calculate test statistics. We examined in particular the sum and the maximum of chi-squared statistics, which measure the strongest and the average association signals per gene, respectively. For pathway scoring, we use a modified Fisher method, which offers not only significant power improvement over more traditional enrichment strategies, but also eliminates the problem of arbitrary threshold selection inherent in any binary membership based pathway enrichment approach. We demonstrate the marked increase in power by analyzing summary statistics from dozens of large meta-studies for various traits. Our extensive testing indicates that our method not only excels in rigorous type I error control, but also results in more biologically meaningful discoveries.

An objective anisotropic elastic plastic model and Algorithm applicable to bone mechanics

The implicit projection algorithm of isotropic plasticity is extended to an objective anisotropic elastic perfectly plastic model. The recursion formula developed to project the trial stress on the yield surface, is applicable to any non linear elastic law and any plastic yield function.A curvilinear transverse isotropic model based on a quadratic elastic potential and on Hill's quadratic yield criterion is then developed and implemented in a computer program for bone mechanics perspectives. The paper concludes with a numerical study of a schematic bone-prosthesis system to illustrate the potential of the model.

A drug administration decision support system

Drug delivery is one of the most common clinical routines in hospitals, and is critical to patients' health and recovery. It includes a decision making process in which a medical doctor decides the amount (dose) and frequency (dose interval) on the basis of a set of available patients' feature data and the doctor's clinical experience (a priori adaptation). This process can be computerized in order to make the prescription procedure in a fast, objective, inexpensive, non-invasive and accurate way. This paper proposes a Drug Administration Decision Support System (DADSS) to help clinicians/patients with the initial dose computing. The system is based on a Support Vector Machine (SVM) algorithm for estimation of the potential drug concentration in the blood of a patient, from which a best combination of dose and dose interval is selected at the level of a DSS. The addition of the RANdom SAmple Consensus (RANSAC) technique enhances the prediction accuracy by selecting inliers for SVM modeling. Experiments are performed for the drug imatinib case study which shows more than 40% improvement in the prediction accuracy compared with previous works. An important extension to the patient features' data is also proposed in this paper.

Fast screening and confirmation of doping agents by UHPLC-QTOF-MS/MS

Introduction: The general strategy to perform anti-doping analysis starts with a screening followed by a confirmatory step when a sample is suspected to be positive. The screening step should be fast, generic and able to highlight any sample that may contain a prohibited substance by avoiding false negative and reducing false positive results. The confirmatory step is a dedicated procedure comprising a selective sample preparation and detection mode. Aim: The purpose of the study is to develop rapid screening and selective confirmatory strategies to detect and identify 103 doping agents in urine. Methods: For the screening, urine samples were simply diluted by a factor 2 with ultra-pure water and directly injected ("dilute and shoot") in the ultrahigh- pressure liquid chromatography (UHPLC). The UHPLC separation was performed in two gradients (ESI positive and negative) from 5/95 to 95/5% of MeCN/Water containing 0.1% formic acid. The gradient analysis time is 9 min including 3 min reequilibration. Analytes detection was performed in full scan mode on a quadrupole time-of-flight (QTOF) mass spectrometer by acquiring the exact mass of the protonated (ESI positive) or deprotonated (ESI negative) molecular ion. For the confirmatory analysis, urine samples were extracted on SPE 96-well plate with mixed-mode cation (MCX) for basic and neutral compounds or anion exchange (MAX) sorbents for acidic molecules. The analytes were eluted in 3 min (including 1.5 min reequilibration) with a S1-25 Ann Toxicol Anal. 2009; 21(S1) Abstracts gradient from 5/95 to 95/5% of MeCN/Water containing 0.1% formic acid. Analytes confirmation was performed in MS and MS/MS mode on a QTOF mass spectrometer. Results: In the screening and confirmatory analysis, basic and neutral analytes were analysed in the positive ESI mode, whereas acidic compounds were analysed in the negative mode. The analyte identification was based on retention time (tR) and exact mass measurement. "Dilute and shoot" was used as a generic sample treatment in the screening procedure, but matrix effect (e.g., ion suppression) cannot be avoided. However, the sensitivity was sufficient for all analytes to reach the minimal required performance limit (MRPL) required by the World Anti Doping Agency (WADA). To avoid time-consuming confirmatory analysis of false positive samples, a pre-confirmatory step was added. It consists of the sample re-injection, the acquisition of MS/MS spectra and the comparison to reference material. For the confirmatory analysis, urine samples were extracted by SPE allowing a pre-concentration of the analyte. A fast chromatographic separation was developed as a single analyte has to be confirmed. A dedicated QTOF-MS and MS/MS acquisition was performed to acquire within the same run a parallel scanning of two functions. Low collision energy was applied in the first channel to obtain the protonated molecular ion (QTOF-MS), while dedicated collision energy was set in the second channel to obtain fragmented ions (QTOF-MS/MS). Enough identification points were obtained to compare the spectra with reference material and negative urine sample. Finally, the entire process was validated and matrix effects quantified. Conclusion: Thanks to the coupling of UHPLC with the QTOF mass spectrometer, high tR repeatability, sensitivity, mass accuracy and mass resolution over a broad mass range were obtained. The method was sensitive, robust and reliable enough to detect and identify doping agents in urine. Keywords: screening, confirmatory analysis, UHPLC, QTOF, doping agents

Real-time imaging of regional myocardial function using fast-SENC.

A technique for fast imaging of regional myocardial function using a spiral acquisition in combination with strain-encoded (SENC) magnetic resonance imaging (MRI) is presented in this paper. This technique, which is termed fast-SENC, enables scan durations as short as a single heartbeat. A reduced field of view (FOV) without foldover artifacts was achieved by localized SENC, which selectively excited the region around the heart. The two images required for SENC imaging (low- and high-tuning) were acquired in an interleaved fashion throughout the cardiac cycle to further shorten the scan time. Regional circumferential contraction and longitudinal shortening of both the left ventricle (LV) and right ventricle (RV) were examined in long- and short-axis views, respectively. The in vivo results obtained from five human subjects and five infarcted dogs are presented. The results of the fast-SENC technique in a single heartbeat acquisition were comparable to those obtained by conventional SENC in a long acquisition time. Therefore, fast-SENC may prove useful for imaging during stress or arrhythmia.

Dynamic simulation of regulatory networks using SQUAD.

BACKGROUND: The ambition of most molecular biologists is the understanding of the intricate network of molecular interactions that control biological systems. As scientists uncover the components and the connectivity of these networks, it becomes possible to study their dynamical behavior as a whole and discover what is the specific role of each of their components. Since the behavior of a network is by no means intuitive, it becomes necessary to use computational models to understand its behavior and to be able to make predictions about it. Unfortunately, most current computational models describe small networks due to the scarcity of kinetic data available. To overcome this problem, we previously published a methodology to convert a signaling network into a dynamical system, even in the total absence of kinetic information. In this paper we present a software implementation of such methodology. RESULTS: We developed SQUAD, a software for the dynamic simulation of signaling networks using the standardized qualitative dynamical systems approach. SQUAD converts the network into a discrete dynamical system, and it uses a binary decision diagram algorithm to identify all the steady states of the system. Then, the software creates a continuous dynamical system and localizes its steady states which are located near the steady states of the discrete system. The software permits to make simulations on the continuous system, allowing for the modification of several parameters. Importantly, SQUAD includes a framework for perturbing networks in a manner similar to what is performed in experimental laboratory protocols, for example by activating receptors or knocking out molecular components. Using this software we have been able to successfully reproduce the behavior of the regulatory network implicated in T-helper cell differentiation. CONCLUSION: The simulation of regulatory networks aims at predicting the behavior of a whole system when subject to stimuli, such as drugs, or determine the role of specific components within the network. The predictions can then be used to interpret and/or drive laboratory experiments. SQUAD provides a user-friendly graphical interface, accessible to both computational and experimental biologists for the fast qualitative simulation of large regulatory networks for which kinetic data is not necessarily available.

Simultaneous B(0)- and B(1)+-map acquisition for fast localized shim, frequency, and RF power determination in the heart at 3 T.

High-field (>or=3 T) cardiac MRI is challenged by inhomogeneities of both the static magnetic field (B(0)) and the transmit radiofrequency field (B(1)+). The inhomogeneous B fields not only demand improved shimming methods but also impede the correct determination of the zero-order terms, i.e., the local resonance frequency f(0) and the radiofrequency power to generate the intended local B(1)+ field. In this work, dual echo time B(0)-map and dual flip angle B(1)+-map acquisition methods are combined to acquire multislice B(0)- and B(1)+-maps simultaneously covering the entire heart in a single breath hold of 18 heartbeats. A previously proposed excitation pulse shape dependent slice profile correction is tested and applied to reduce systematic errors of the multislice B(1)+-map. Localized higher-order shim correction values including the zero-order terms for frequency f(0) and radiofrequency power can be determined based on the acquired B(0)- and B(1)+-maps. This method has been tested in 7 healthy adult human subjects at 3 T and improved the B(0) field homogeneity (standard deviation) from 60 Hz to 35 Hz and the average B(1)+ field from 77% to 100% of the desired B(1)+ field when compared to more commonly used preparation methods.

Navigator-gated free-breathing three-dimensional balanced fast field echo (TrueFISP) coronary magnetic resonance angiography.

RATIONALE AND OBJECTIVES: Recent developments of MR imaging equipment enabled high-quality steady state-free-precession (Balanced FFE, True-FISP) MR-imaging with a substantial 'T2 like' contrast, resulting in a high signal intensity of the blood-pool without the application of exogenous contrast agents. It is hypothesized that Balanced-FFE may be valuable for contrast enhancement in 3D free-breathing coronary MRA. MATERIALS AND METHODS: Navigator-gated free-breathing cardiac triggered coronary MRA was performed in 10 healthy adult subjects and three patients with radiograph defined coronary artery disease using a segmented k-space 3D Balanced FFE imaging sequence. RESULTS: High contrast-to-noise ratio between the blood-pool and the myocardium (29 +/- 8) and long segment visualization of both coronary arteries could be obtained in about 5 minutes during free breathing using the present navigator-gated Balanced-FFE coronary MRA approach. First patient results demonstrated successful display of coronary artery stenoses. CONCLUSION: Balanced FFE offers a potential alternative for endogenous contrast enhancement in navigator-gated free-breathing 3D coronary MRA. The obtained results together with the relatively short scanning time warrant further studies in larger patient collectives.