Multilayer perceptron with local constraint as an emerging method in spatial data analysis

The use of Geographic Information Systems has revolutionalized the handling and the visualization of geo-referenced data and has underlined the critic role of spatial analysis. The usual tools for such a purpose are geostatistics which are widely used in Earth science. Geostatistics are based upon several hypothesis which are not always verified in practice. On the other hand, Artificial Neural Network (ANN) a priori can be used without special assumptions and are known to be flexible. This paper proposes to discuss the application of ANN in the case of the interpolation of a geo-referenced variable.

Local-global splitting for spatiotemporal-adaptive multiscale methods

We present a novel spatiotemporal-adaptive Multiscale Finite Volume (MsFV) method, which is based on the natural idea that the global coarse-scale problem has longer characteristic time than the local fine-scale problems. As a consequence, the global problem can be solved with larger time steps than the local problems. In contrast to the pressure-transport splitting usually employed in the standard MsFV approach, we propose to start directly with a local-global splitting that allows to locally retain the original degree of coupling. This is crucial for highly non-linear systems or in the presence of physical instabilities. To obtain an accurate and efficient algorithm, we devise new adaptive criteria for global update that are based on changes of coarse-scale quantities rather than on fine-scale quantities, as it is routinely done before in the adaptive MsFV method. By means of a complexity analysis we show that the adaptive approach gives a noticeable speed-up with respect to the standard MsFV algorithm. In particular, it is efficient in case of large upscaling factors, which is important for multiphysics problems. Based on the observation that local time stepping acts as a smoother, we devise a self-correcting algorithm which incorporates the information from previous times to improve the quality of the multiscale approximation. We present results of multiphase flow simulations both for Darcy-scale and multiphysics (hybrid) problems, in which a local pore-scale description is combined with a global Darcy-like description. The novel spatiotemporal-adaptive multiscale method based on the local-global splitting is not limited to porous media flow problems, but it can be extended to any system described by a set of conservation equations.

Exogenous selection shapes germination behaviour and seedling traits of populations at different altitudes in a Senecio hybrid zone.

BACKGROUND AND AIMS: The Senecio hybrid zone on Mt Etna, Sicily, is characterized by steep altitudinal clines in quantitative traits and genetic variation. Such clines are thought to be maintained by a combination of 'endogenous' selection arising from genetic incompatibilities and environment-dependent 'exogenous' selection leading to local adaptation. Here, the hypothesis was tested that local adaptation to the altitudinal temperature gradient contributes to maintaining divergence between the parental species, S. chrysanthemifolius and S. aethnensis. METHODS: Intra- and inter-population crosses were performed between five populations from across the hybrid zone and the germination and early seedling growth of the progeny were assessed. KEY RESULTS: Seedlings from higher-altitude populations germinated better under low temperatures (9-13 °C) than those from lower altitude populations. Seedlings from higher-altitude populations had lower survival rates under warm conditions (25/15 °C) than those from lower altitude populations, but also attained greater biomass. There was no altitudinal variation in growth or survival under cold conditions (15/5 °C). Population-level plasticity increased with altitude. Germination, growth and survival of natural hybrids and experimentally generated F(1)s generally exceeded the worse-performing parent. CONCLUSIONS: Limited evidence was found for endogenous selection against hybrids but relatively clear evidence was found for divergence in seed and seedling traits, which is probably adaptive. The combination of low-temperature germination and faster growth in warm conditions might enable high-altitude S. aethnensis to maximize its growth during a shorter growing season, while the slower growth of S. chrysanthemifolius may be an adaptation to drought stress at low altitudes. This study indicates that temperature gradients are likely to be an important environmental factor generating and maintaining adaptive divergence across the Senecio hybrid zone on Mt Etna.

Rapid profiling of intact glucosinolates in Arabidopsis leaves by UHPLC-QTOFMS using a charged surface hybrid column.

INTRODUCTION: The analysis of glucosinolates (GS) is traditionally performed by reverse-phase liquid chromatography coupled to ultraviolet detection after a time-consuming desulphation step, which is required for increased retention. Simpler and more efficient alternative methods that can shorten both sample preparation and analysis are much needed. OBJECTIVE: To evaluate the feasibility of using ultrahigh-pressure liquid chromatography coupled to quadrupole time-of-flight mass spectrometry (UHPLC-QTOFMS) for the rapid profiling of intact GS. METHODOLOGY: A simple and short extraction of GS from Arabidopsis thaliana leaves was developed. Four sub-2 µm reverse-phase columns were tested for the rapid separation of these polar compounds using formic acid as the chromatographic additive. High-resolution QTOFMS was used to detect and identify GS. RESULTS: A novel charged surface hybrid (CSH) column was found to provide excellent retention and separation of GS within a total running time of 11 min. Twenty-one GS could be identified based on their accurate mass as well as isotopic and fragmentation patterns. The method was applied to determine the changes in GS content that occur after herbivory in Arabidopsis. In addition, we evaluated its applicability to the profiling of other Brassicaceae species. CONCLUSION: The method developed can profile the full range of GS, including the most polar ones, in a shorter time than previous methods, and is highly compatible with mass spectrometric detection.

Can we continue to neglect genomic variation in introgression rates when inferring the history of speciation? A case study in a Mytilus hybrid zone.

The use of molecular data to reconstruct the history of divergence and gene flow between populations of closely related taxa represents a challenging problem. It has been proposed that the long-standing debate about the geography of speciation can be resolved by comparing the likelihoods of a model of isolation with migration and a model of secondary contact. However, data are commonly only fit to a model of isolation with migration and rarely tested against the secondary contact alternative. Furthermore, most demographic inference methods have neglected variation in introgression rates and assume that the gene flow parameter (Nm) is similar among loci. Here, we show that neglecting this source of variation can give misleading results. We analysed DNA sequences sampled from populations of the marine mussels, Mytilus edulis and M. galloprovincialis, across a well-studied mosaic hybrid zone in Europe and evaluated various scenarios of speciation, with or without variation in introgression rates, using an Approximate Bayesian Computation (ABC) approach. Models with heterogeneous gene flow across loci always outperformed models assuming equal migration rates irrespective of the history of gene flow being considered. By incorporating this heterogeneity, the best-supported scenario was a long period of allopatric isolation during the first three-quarters of the time since divergence followed by secondary contact and introgression during the last quarter. By contrast, constraining migration to be homogeneous failed to discriminate among any of the different models of gene flow tested. Our simulations thus provide statistical support for the secondary contact scenario in the European Mytilus hybrid zone that the standard coalescent approach failed to confirm. Our results demonstrate that genomic variation in introgression rates can have profound impacts on the biological conclusions drawn from inference methods and needs to be incorporated in future studies.

Kernel-based methods for change detection in remote sensing images

Nowadays, the joint exploitation of images acquired daily by remote sensing instruments and of images available from archives allows a detailed monitoring of the transitions occurring at the surface of the Earth. These modifications of the land cover generate spectral discrepancies that can be detected via the analysis of remote sensing images. Independently from the origin of the images and of type of surface change, a correct processing of such data implies the adoption of flexible, robust and possibly nonlinear method, to correctly account for the complex statistical relationships characterizing the pixels of the images. This Thesis deals with the development and the application of advanced statistical methods for multi-temporal optical remote sensing image processing tasks. Three different families of machine learning models have been explored and fundamental solutions for change detection problems are provided. In the first part, change detection with user supervision has been considered. In a first application, a nonlinear classifier has been applied with the intent of precisely delineating flooded regions from a pair of images. In a second case study, the spatial context of each pixel has been injected into another nonlinear classifier to obtain a precise mapping of new urban structures. In both cases, the user provides the classifier with examples of what he believes has changed or not. In the second part, a completely automatic and unsupervised method for precise binary detection of changes has been proposed. The technique allows a very accurate mapping without any user intervention, resulting particularly useful when readiness and reaction times of the system are a crucial constraint. In the third, the problem of statistical distributions shifting between acquisitions is studied. Two approaches to transform the couple of bi-temporal images and reduce their differences unrelated to changes in land cover are studied. The methods align the distributions of the images, so that the pixel-wise comparison could be carried out with higher accuracy. Furthermore, the second method can deal with images from different sensors, no matter the dimensionality of the data nor the spectral information content. This opens the doors to possible solutions for a crucial problem in the field: detecting changes when the images have been acquired by two different sensors.

Using a Bayesian method to assign individuals to karyotypic taxa in shrew hybrid zones.

Individuals sampled in hybrid zones are usually analysed according to their sampling locality, morphology, behaviour or karyotype. But the increasing availability of genetic information more and more favours its use for individual sorting purposes and numerous assignment methods based on the genetic composition of individuals have been developed. The shrews of the Sorex araneus group offer good opportunities to test the genetic assignment on individuals identified by their karyotype. Here we explored the potential and efficiency of a Bayesian assignment method combined or not with a reference dataset to study admixture and individual assignment in the difficult context of two hybrid zones between karyotypic species of the Sorex araneus group. As a whole, we assigned more than 80% of the individuals to their respective karyotypic categories (i.e. 'pure' species or hybrids). This assignment level is comparable to what was obtained for the same species away from hybrid zones. Additionally, we showed that the assignment result for several individuals was strongly affected by the inclusion or not of a reference dataset. This highlights the importance of such comparisons when analysing hybrid zones. Finally, differences between the admixture levels detected in both hybrid zones support the hypothesis of an impact of chromosomal rearrangements on gene flow.

Hybrid PET/MRI in the assessment of cardiac viability: added value compared to PET/CT

Purpose: We evaluated the potential for hybrid PET/MRI devices to provide integrated metabolic, functional and anatomic characterisation of patients with suspected coronary artery disease.Methods and Materials: Ten patients (5 with suspected hibernating myocardium and 5 healthy volunteers) performed an imaging study using a hybrid PET/MRI (Philips). Viability assessed by 18F-FDG was performed in diseased patients along with MRI anatomic and functional study and reassessed within 30 minutes by conventional PET/CT. Non-contrast right coronary artery (RCA) targeted and whole heart 3D coronary angio-MRI using ECG-gating and respiratory navigator was performed in healthy volunteers with reconstruction performed using MPR and volume rendering. The extent of metabolic defect (MD) using PET/MRI and PET/CT was compared in patients and coronary territories (LAD, CX, RCA). Assessability of coronary lumen was judged as good, sub-optimal or non-assessable using a 16-segments coronary model.Results: Metabolic assessment was successful in all patients with MD being 19.2% vs 18.3% using PET/MRI and PET/CT, respectively (P=ns). The MD was 10.2%, 6 %, and 3 % vs 9.3%, 6 % and 3 % for LAD, CX and RCA territories, respectively (P= ns). Coronary angio-MRI was successful in all volunteers with 66 coronary segments visualised overall. The RCA was fully visualised in 4/5 volunteers and the left coronary arteries in 4/5 volunteers. Assessability in visualised segments was good, sub-optimal and non-assessable in 88 %, 2 % and 10 %, respectively.Conclusion: Hybrid PET/MRI devices may enable metabolic evaluation comparable to PET/CT with additional value owing to accurate functional and anatomical information including coronary assessment.

Intraoperative angiography reloaded: a new hybrid operating theater for combined endovascular and surgical treatment of cerebral arteriovenous malformations: a pilot study on 25 patients.

BACKGROUND: Multimodality treatment suites for patients with cerebral arteriovenous malformations (AVM) have recently become available. This study was designed to evaluate feasibility, safety and impact on treatment of a new intraoperative flat-panel (FP) based integrated surgical and imaging suite for combined endovascular and surgical treatment of cerebral AVM. METHODS: Twenty-five patients with AVMs to treat with combined endovascular and surgical interventions were prospectively enrolled in this consecutive case series. The hybrid suite allows combined endovascular and surgical approaches with intraoperative scanner-like imaging (XperCT®) and intraoperative 3D rotational angiography (3D-RA). The impact of intraoperative multimodal imaging on feasibility, workflow of combined interventions, surgery, and unexpected imaging findings were analyzed. RESULTS: Twenty-five patients (mean age 38 ± 18.6 year) with a median Spetzler-Martin grade 2 AVM (range 1-4) underwent combined endovascular and surgical procedures. Sixteen patients presented with a ruptured AVM and nine with an unruptured AVM. In 16 % (n = 4) of cases, intraoperative imaging visualized AVM remnants ≤3 mm and allowed for completion of the resections in the same sessions. Complete resection was confirmed in all n = 16 patients who had follow-up angiography one year after surgery so far. All diagnostic and therapeutical steps, including angiographic control, were performed without having to move the patients CONCLUSION: The hybrid neurointerventional suite was shown to be a safe and useful setup which allowed for unconstrained combined microsurgical and neuroradiological workflow. It reduces the need for extraoperative angiographic controls and subsequent potential surgical revisions a second time, as small AVM remnants can be detected with high security.

Comparison of human chromosome 21 conserved nongenic sequences (CNGs) with the mouse and dog genomes shows that their selective constraint is independent of their genic environment.

The analysis of conservation between the human and mouse genomes resulted in the identification of a large number of conserved nongenic sequences (CNGs). The functional significance of this nongenic conservation remains unknown, however. The availability of the sequence of a third mammalian genome, the dog, allows for a large-scale analysis of evolutionary attributes of CNGs in mammals. We have aligned 1638 previously identified CNGs and 976 conserved exons (CODs) from human chromosome 21 (Hsa21) with their orthologous sequences in mouse and dog. Attributes of selective constraint, such as sequence conservation, clustering, and direction of substitutions were compared between CNGs and CODs, showing a clear distinction between the two classes. We subsequently performed a chromosome-wide analysis of CNGs by correlating selective constraint metrics with their position on the chromosome and relative to their distance from genes. We found that CNGs appear to be randomly arranged in intergenic regions, with no bias to be closer or farther from genes. Moreover, conservation and clustering of substitutions of CNGs appear to be completely independent of their distance from genes. These results suggest that the majority of CNGs are not typical of previously described regulatory elements in terms of their location. We propose models for a global role of CNGs in genome function and regulation, through long-distance cis or trans chromosomal interactions.

A framework for hybrid simulations of two-phase flow in porous media

Rough a global coarse problem. Although these techniques are usually employed for problems in which the fine-scale processes are described by Darcy's law, they can also be applied to pore-scale simulations and used as a mathematical framework for hybrid methods that couples a Darcy and pore scales. In this work, we consider a pore-scale description of fine-scale processes. The Navier-Stokes equations are numerically solved in the pore geometry to compute the velocity field and obtain generalized permeabilities. In the case of two-phase flow, the dynamics of the phase interface is described by the volume of fluid method with the continuum surface force model. The MsFV method is employed to construct an algorithm that couples a Darcy macro-scale description with a pore-scale description at the fine scale. The hybrid simulations results presented are in good agreement with the fine-scale reference solutions. As the reconstruction of the fine-scale details can be done adaptively, the presented method offers a flexible framework for hybrid modeling.

Estimating parameters for generalized mass action models using constraint propagation.

As modern molecular biology moves towards the analysis of biological systems as opposed to their individual components, the need for appropriate mathematical and computational techniques for understanding the dynamics and structure of such systems is becoming more pressing. For example, the modeling of biochemical systems using ordinary differential equations (ODEs) based on high-throughput, time-dense profiles is becoming more common-place, which is necessitating the development of improved techniques to estimate model parameters from such data. Due to the high dimensionality of this estimation problem, straight-forward optimization strategies rarely produce correct parameter values, and hence current methods tend to utilize genetic/evolutionary algorithms to perform non-linear parameter fitting. Here, we describe a completely deterministic approach, which is based on interval analysis. This allows us to examine entire sets of parameters, and thus to exhaust the global search within a finite number of steps. In particular, we show how our method may be applied to a generic class of ODEs used for modeling biochemical systems called Generalized Mass Action Models (GMAs). In addition, we show that for GMAs our method is amenable to the technique in interval arithmetic called constraint propagation, which allows great improvement of its efficiency. To illustrate the applicability of our method we apply it to some networks of biochemical reactions appearing in the literature, showing in particular that, in addition to estimating system parameters in the absence of noise, our method may also be used to recover the topology of these networks.

Early childhood constraint therapy for sensory/motor impairment in cerebral palsy: a randomised clinical trial protocol.

INTRODUCTION: Cerebral palsy (CP) is the most common physical disability in childhood. It is a disorder resulting from sensory and motor impairments due to perinatal brain injury, with lifetime consequences that range from poor adaptive and social function to communication and emotional disturbances. Infants with CP have a fundamental disadvantage in recovering motor function: they do not receive accurate sensory feedback from their movements, leading to developmental disregard. Constraint-induced movement therapy (CIMT) is one of the few effective neurorehabilitative strategies shown to improve upper extremity motor function in adults and older children with CP, potentially overcoming developmental disregard. METHODS AND ANALYSIS: This study is a randomised controlled trial of children 12-24 months corrected age studying the effectiveness of CIMT combined with motor and sensory-motor interventions. The study population will comprise 72 children with CP and 144 typically developing children for a total of N=216 children. All children with CP, regardless of group allocation will continue with their standard of care occupational and physical therapy throughout the study. The research material collected will be in the form of data from high-density array event-related potential scan, standardised assessment scores and motion analysis scores. ETHICS AND DISSEMINATION: The study protocol was approved by the Institutional Review Board. The findings of the trial will be disseminated through peer-reviewed journals and scientific conferences. TRIAL REGISTRATION NUMBER: NCT02567630.

Non-assisted versus neuro-navigated and XperCT-guided external ventricular catheter placement: a comparative cadaver study.

BACKGROUND AND PURPOSE: Accurate placement of an external ventricular drain (EVD) for the treatment of hydrocephalus is of paramount importance for its functionality and in order to minimize morbidity and complications. The aim of this study was to compare two different drain insertion assistance tools with the traditional free-hand anatomical landmark method, and to measure efficacy, safety and precision. METHODS: Ten cadaver heads were prepared by opening large bone windows centered on Kocher's points on both sides. Nineteen physicians, divided in two groups (trainees and board certified neurosurgeons) performed EVD insertions. The target for the ventricular drain tip was the ipsilateral foramen of Monro. Each participant inserted the external ventricular catheter in three different ways: 1) free-hand by anatomical landmarks, 2) neuronavigation-assisted (NN), and 3) XperCT-guided (XCT). The number of ventricular hits and dangerous trajectories; time to proceed; radiation exposure of patients and physicians; distance of the catheter tip to target and size of deviations projected in the orthogonal plans were measured and compared. RESULTS: Insertion using XCT increased the probability of ventricular puncture from 69.2 to 90.2 % (p = 0.02). Non-assisted placements were significantly less precise (catheter tip to target distance 14.3 ± 7.4 mm versus 9.6 ± 7.2 mm, p = 0.0003). The insertion time to proceed increased from 3.04 ± 2.06 min. to 7.3 ± 3.6 min. (p < 0.001). The X-ray exposure for XCT was 32.23 mSv, but could be reduced to 13.9 mSv if patients were initially imaged in the hybrid-operating suite. No supplementary radiation exposure is needed for NN if patients are imaged according to a navigation protocol initially. CONCLUSION: This ex vivo study demonstrates a significantly improved accuracy and safety using either NN or XCT-assisted methods. Therefore, efforts should be undertaken to implement these new technologies into daily clinical practice. However, the accuracy versus urgency of an EVD placement has to be balanced, as the image-guided insertion technique will implicate a longer preparation time due to a specific image acquisition and trajectory planning.

Rational design of an organometallic glutathione transferase inhibitor.

Double trouble: A hybrid organic-inorganic (organometallic) inhibitor was designed to target glutathione transferases. The metal center is used to direct protein binding, while the organic moiety acts as the active-site inhibitor (see picture). The mechanism of inhibition was studied using a range of biophysical and biochemical methods.