Sequence determinants of a microtubule tip localization signal (MtLS).

Microtubule plus-end-tracking proteins (+TIPs) specifically localize to the growing plus-ends of microtubules to regulate microtubule dynamics and functions. A large group of +TIPs contain a short linear motif, SXIP, which is essential for them to bind to end-binding proteins (EBs) and target microtubule ends. The SXIP sequence site thus acts as a widespread microtubule tip localization signal (MtLS). Here we have analyzed the sequence-function relationship of a canonical MtLS. Using synthetic peptide arrays on membrane supports, we identified the residue preferences at each amino acid position of the SXIP motif and its surrounding sequence with respect to EB binding. We further developed an assay based on fluorescence polarization to assess the mechanism of the EB-SXIP interaction and to correlate EB binding and microtubule tip tracking of MtLS sequences from different +TIPs. Finally, we investigated the role of phosphorylation in regulating the EB-SXIP interaction. Together, our results define the sequence determinants of a canonical MtLS and provide the experimental data for bioinformatics approaches to carry out genome-wide predictions of novel +TIPs in multiple organisms.

Spatially selective implementation of the adiabatic T2 prep sequence for magnetic resonance angiography of the coronary arteries.

In coronary magnetic resonance angiography, a magnetization-preparation scheme for T2 -weighting (T2 Prep) is widely used to enhance contrast between the coronary blood-pool and the myocardium. This prepulse is commonly applied without spatial selection to minimize flow sensitivity, but the nonselective implementation results in a reduced magnetization of the in-flowing blood and a related penalty in signal-to-noise ratio. It is hypothesized that a spatially selective T2 Prep would leave the magnetization of blood outside the T2 Prep volume unaffected and thereby lower the signal-to-noise ratio penalty. To test this hypothesis, a spatially selective T2 Prep was implemented where the user could freely adjust angulation and position of the T2 Prep slab to avoid covering the ventricular blood-pool and saturating the in-flowing spins. A time gap of 150 ms was further added between the T2 Prep and other prepulses to allow for in-flow of a larger volume of unsaturated spins. Consistent with numerical simulation, the spatially selective T2 Prep increased in vivo human coronary artery signal-to-noise ratio (42.3 ± 2.9 vs. 31.4 ± 2.2, n = 22, P < 0.0001) and contrast-to-noise-ratio (18.6 ± 1.5 vs. 13.9 ± 1.2, P = 0.009) as compared to those of the nonselective T2 Prep. Additionally, a segmental analysis demonstrated that the spatially selective T2 Prep was most beneficial in proximal and mid segments where the in-flowing blood volume was largest compared to the distal segments. Magn Reson Med, 2013. © 2012 Wiley Periodicals, Inc.

MP2RAGE, a self bias-field corrected sequence for improved segmentation and T1-mapping at high field.

The large spatial inhomogeneity in transmit B(1) field (B(1)(+)) observable in human MR images at high static magnetic fields (B(0)) severely impairs image quality. To overcome this effect in brain T(1)-weighted images, the MPRAGE sequence was modified to generate two different images at different inversion times, MP2RAGE. By combining the two images in a novel fashion, it was possible to create T(1)-weighted images where the result image was free of proton density contrast, T(2) contrast, reception bias field, and, to first order, transmit field inhomogeneity. MP2RAGE sequence parameters were optimized using Bloch equations to maximize contrast-to-noise ratio per unit of time between brain tissues and minimize the effect of B(1)(+) variations through space. Images of high anatomical quality and excellent brain tissue differentiation suitable for applications such as segmentation and voxel-based morphometry were obtained at 3 and 7 T. From such T(1)-weighted images, acquired within 12 min, high-resolution 3D T(1) maps were routinely calculated at 7 T with sub-millimeter voxel resolution (0.65-0.85 mm isotropic). T(1) maps were validated in phantom experiments. In humans, the T(1) values obtained at 7 T were 1.15+/-0.06 s for white matter (WM) and 1.92+/-0.16 s for grey matter (GM), in good agreement with literature values obtained at lower spatial resolution. At 3 T, where whole-brain acquisitions with 1 mm isotropic voxels were acquired in 8 min, the T(1) values obtained (0.81+/-0.03 s for WM and 1.35+/-0.05 for GM) were once again found to be in very good agreement with values in the literature.

Speech prognosis and need of pharyngeal flap for non syndromic vs syndromic Pierre Robin Sequence

BACKGROUND: The aim of this retrospective study was to evaluate speech outcome and need of a pharyngeal flap in children born with nonsyndromic Pierre Robin Sequence (nsPRS) vs syndromic Pierre Robin Sequence (sPRS). METHODS: Pierre Robin Sequence was diagnosed when the triad microretrognathia, glossoptosis, and cleft palate were present. Children were classified at birth in 3 categories depending on respiratory and feeding problems. The Borel-Maisonny classification was used to score the velopharyngeal insufficiency. RESULTS: The study was based on 38 children followed from 1985 to 2006. For the 25 nsPRS, 9 (36%) pharyngeal flaps were performed with improvements of the phonatory score in the 3 categories. For the 13 sPRS, 3 (23%) pharyngeal flaps were performed with an improvement of the phonatory scores in the 3 children. There was no statistical difference between the nsPRS and sPRS groups (P = .3) even if we compared the children in the 3 categories (P = .2). CONCLUSIONS: Children born with nsPRS did not have a better prognosis of speech outcome than children born with sPRS. Respiratory and feeding problems at birth did not seem to be correlated with speech outcome. This is important when informing parents on the prognosis of long-term therapy

Solving two production scheduling problems with sequence-dependent set-up times

In today’s competitive markets, the importance of goodscheduling strategies in manufacturing companies lead to theneed of developing efficient methods to solve complexscheduling problems.In this paper, we studied two production scheduling problemswith sequence-dependent setups times. The setup times areone of the most common complications in scheduling problems,and are usually associated with cleaning operations andchanging tools and shapes in machines.The first problem considered is a single-machine schedulingwith release dates, sequence-dependent setup times anddelivery times. The performance measure is the maximumlateness.The second problem is a job-shop scheduling problem withsequence-dependent setup times where the objective is tominimize the makespan.We present several priority dispatching rules for bothproblems, followed by a study of their performance. Finally,conclusions and directions of future research are presented.

Compact matrix expressions for generalized Wald tests of equality of moment vectors

Asymptotic chi-squared test statistics for testing the equality ofmoment vectors are developed. The test statistics proposed aregeneralizedWald test statistics that specialize for different settings by inserting andappropriate asymptotic variance matrix of sample moments. Scaled teststatisticsare also considered for dealing with situations of non-iid sampling. Thespecializationwill be carried out for testing the equality of multinomial populations, andtheequality of variance and correlation matrices for both normal andnon-normaldata. When testing the equality of correlation matrices, a scaled versionofthe normal theory chi-squared statistic is proven to be an asymptoticallyexactchi-squared statistic in the case of elliptical data.

Glut-1 deficiency syndrome masquerading as idiopathic generalized epilepsy.

To report the case of a child with short absences and occasional myoclonias since infancy who was first diagnosed with an idiopathic generalized epilepsy, but was documented at follow-up to have a mild phenotype of glucose transporter type 1 deficiency syndrome. Unlike other reported cases of Glut-1 DS and epilepsy, this child had a normal development as well as a normal head growth and neurological examination. Early onset of seizures and later recognized episodes of mild confusion before meals together with persistent atypical EEG features and unexpected learning difficulties led to the diagnosis. Seizure control and neuropsychological improvements were obtained with a ketogenic diet.

Improving generalized regression analysis for the spatial prediction of forest communities

Aim This study used data from temperate forest communities to assess: (1) five different stepwise selection methods with generalized additive models, (2) the effect of weighting absences to ensure a prevalence of 0.5, (3) the effect of limiting absences beyond the environmental envelope defined by presences, (4) four different methods for incorporating spatial autocorrelation, and (5) the effect of integrating an interaction factor defined by a regression tree on the residuals of an initial environmental model. Location State of Vaud, western Switzerland. Methods Generalized additive models (GAMs) were fitted using the grasp package (generalized regression analysis and spatial predictions, http://www.cscf.ch/grasp). Results Model selection based on cross-validation appeared to be the best compromise between model stability and performance (parsimony) among the five methods tested. Weighting absences returned models that perform better than models fitted with the original sample prevalence. This appeared to be mainly due to the impact of very low prevalence values on evaluation statistics. Removing zeroes beyond the range of presences on main environmental gradients changed the set of selected predictors, and potentially their response curve shape. Moreover, removing zeroes slightly improved model performance and stability when compared with the baseline model on the same data set. Incorporating a spatial trend predictor improved model performance and stability significantly. Even better models were obtained when including local spatial autocorrelation. A novel approach to include interactions proved to be an efficient way to account for interactions between all predictors at once. Main conclusions Models and spatial predictions of 18 forest communities were significantly improved by using either: (1) cross-validation as a model selection method, (2) weighted absences, (3) limited absences, (4) predictors accounting for spatial autocorrelation, or (5) a factor variable accounting for interactions between all predictors. The final choice of model strategy should depend on the nature of the available data and the specific study aims. Statistical evaluation is useful in searching for the best modelling practice. However, one should not neglect to consider the shapes and interpretability of response curves, as well as the resulting spatial predictions in the final assessment.

Evolution at Two Levels in Fire Ants: The Relationship between Patterns of Gene Expression and Protein Sequence Evolution.

Variation in protein sequence and gene expression each contribute to phenotypic diversity, and may be subject to similar selective pressures. Eusocial insects are particularly useful for investigating the evolutionary link between protein sequence and condition-dependent patterns of gene expression because gene expression plays a central role in determining differences between eusocial insect sexes and castes. We investigated the relationship between protein coding sequence evolution and gene expression patterns in the fire ants Solenopsis invicta, S. richteri, and their hybrids to gain greater insight into how selection jointly operates on gene expression and coding sequence. We found that genes with high expression variability within castes and sexes were frequently differentially expressed between castes and sexes, as well as between species and hybrids. These results indicate that genes showing high variation in expression in one context also tend to show high variation in expression in other contexts. Our analyses further revealed that variation in both intra- and interspecific gene expression was positively associated with rate of protein sequence evolution in Solenopsis. This suggests that selective constraints on a gene operate both at the level of protein sequence and at the level of gene expression regulation. Overall, our study provides one of the strongest demonstrations that selective constraints mediate both protein sequence evolution and gene expression variability across different biological contexts and timescales.

Adaptive approach heuristics for the generalized assignment problem

The Generalized Assignment Problem consists in assigning a setof tasks to a set of agents with minimum cost. Each agent hasa limited amount of a single resource and each task must beassigned to one and only one agent, requiring a certain amountof the resource of the agent. We present new metaheuristics forthe generalized assignment problem based on hybrid approaches.One metaheuristic is a MAX-MIN Ant System (MMAS), an improvedversion of the Ant System, which was recently proposed byStutzle and Hoos to combinatorial optimization problems, and itcan be seen has an adaptive sampling algorithm that takes inconsideration the experience gathered in earlier iterations ofthe algorithm. Moreover, the latter heuristic is combined withlocal search and tabu search heuristics to improve the search.A greedy randomized adaptive search heuristic (GRASP) is alsoproposed. Several neighborhoods are studied, including one basedon ejection chains that produces good moves withoutincreasing the computational effort. We present computationalresults of the comparative performance, followed by concludingremarks and ideas on future research in generalized assignmentrelated problems.

Generalized canonical correlation analysis of matrices with different row and column orders

A Method is offered that makes it possible to apply generalized canonicalcorrelations analysis (CANCOR) to two or more matrices of different row and column order. The new method optimizes the generalized canonical correlationanalysis objective by considering only the observed values. This is achieved byemploying selection matrices. We present and discuss fit measures to assessthe quality of the solutions. In a simulation study we assess the performance of our new method and compare it to an existing procedure called GENCOM,proposed by Green and Carroll. We find that our new method outperforms the GENCOM algorithm both with respect to model fit and recovery of the truestructure. Moreover, as our new method does not require any type of iteration itis easier to implement and requires less computation. We illustrate the methodby means of an example concerning the relative positions of the political parties inthe Netherlands based on provincial data.