Structural joint inversion of time-lapse crosshole ERT and GPR traveltime data

Time-lapse geophysical monitoring and inversion are valuable tools in hydrogeology for monitoring changes in the subsurface due to natural and forced (tracer) dynamics. However, the resulting models may suffer from insufficient resolution, which leads to underestimated variability and poor mass recovery. Structural joint inversion using cross-gradient constraints can provide higher-resolution models compared with individual inversions and we present the first application to time-lapse data. The results from a synthetic and field vadose zone water tracer injection experiment show that joint 3-D time-lapse inversion of crosshole electrical resistance tomography (ERT) and ground penetrating radar (GPR) traveltime data significantly improve the imaged characteristics of the point injected plume, such as lateral spreading and center of mass, as well as the overall consistency between models. The joint inversion method appears to work well for cases when one hydrological state variable (in this case moisture content) controls the time-lapse response of both geophysical methods. Citation: Doetsch, J., N. Linde, and A. Binley (2010), Structural joint inversion of time-lapse crosshole ERT and GPR traveltime data, Geophys. Res. Lett., 37, L24404, doi: 10.1029/2010GL045482.

Structural covariance of superficial white matter in mild Alzheimer's disease compared to normal aging.

INTRODUCTION: Interindividual variations in regional structural properties covary across the brain, thus forming networks that change as a result of aging and accompanying neurological conditions. The alterations of superficial white matter (SWM) in Alzheimer's disease (AD) are of special interest, since they follow the AD-specific pattern characterized by the strongest neurodegeneration of the medial temporal lobe and association cortices. METHODS: Here, we present an SWM network analysis in comparison with SWM topography based on the myelin content quantified with magnetization transfer ratio (MTR) for 39 areas in each hemisphere in 15 AD patients and 15 controls. The networks are represented by graphs, in which nodes correspond to the areas, and edges denote statistical associations between them. RESULTS: In both groups, the networks were characterized by asymmetrically distributed edges (predominantly in the left hemisphere). The AD-related differences were also leftward. The edges lost due to AD tended to connect nodes in the temporal lobe to other lobes or nodes within or between the latter lobes. The newly gained edges were mostly confined to the temporal and paralimbic regions, which manifest demyelination of SWM already in mild AD. CONCLUSION: This pattern suggests that the AD pathological process coordinates SWM demyelination in the temporal and paralimbic regions, but not elsewhere. A comparison of the MTR maps with MTR-based networks shows that although, in general, the changes in network architecture in AD recapitulate the topography of (de)myelination, some aspects of structural covariance (including the interhemispheric asymmetry of networks) have no immediate reflection in the myelination pattern.

Cis-trans interactions of cell surface receptors: biological roles and structural basis.

Cell surface receptors bind ligands expressed on other cells (in trans) in order to communicate with neighboring cells. However, an increasing number of cell surface receptors are found to also interact with ligands expressed on the same cell (in cis). These observations raise questions regarding the biological role of such cis interactions. Specifically, it is important to know whether cis and trans binding have distinct functional effects and, if so, how a single cell discriminates between interactions in cis versus trans. Further, what are the structural features that allow certain cell surface receptors to engage ligand both on the same as well as on an apposed cell membrane? Here, we summarize known examples of receptors that display cis-trans binding and discuss the emerging diversity of biological roles played by these unconventional two-way interactions, along with their structural basis.

Identification of optimal structural connectivity using functional connectivity and neural modeling.

The complex network dynamics that arise from the interaction of the brain's structural and functional architectures give rise to mental function. Theoretical models demonstrate that the structure-function relation is maximal when the global network dynamics operate at a critical point of state transition. In the present work, we used a dynamic mean-field neural model to fit empirical structural connectivity (SC) and functional connectivity (FC) data acquired in humans and macaques and developed a new iterative-fitting algorithm to optimize the SC matrix based on the FC matrix. A dramatic improvement of the fitting of the matrices was obtained with the addition of a small number of anatomical links, particularly cross-hemispheric connections, and reweighting of existing connections. We suggest that the notion of a critical working point, where the structure-function interplay is maximal, may provide a new way to link behavior and cognition, and a new perspective to understand recovery of function in clinical conditions.

Statistical learning theory for geospatial data. Case study: Aral sea

In recent years there has been an explosive growth in the development of adaptive and data driven methods. One of the efficient and data-driven approaches is based on statistical learning theory (Vapnik 1998). The theory is based on Structural Risk Minimisation (SRM) principle and has a solid statistical background. When applying SRM we are trying not only to reduce training error ? to fit the available data with a model, but also to reduce the complexity of the model and to reduce generalisation error. Many nonlinear learning procedures recently developed in neural networks and statistics can be understood and interpreted in terms of the structural risk minimisation inductive principle. A recent methodology based on SRM is called Support Vector Machines (SVM). At present SLT is still under intensive development and SVM find new areas of application (www.kernel-machines.org). SVM develop robust and non linear data models with excellent generalisation abilities that is very important both for monitoring and forecasting. SVM are extremely good when input space is high dimensional and training data set i not big enough to develop corresponding nonlinear model. Moreover, SVM use only support vectors to derive decision boundaries. It opens a way to sampling optimization, estimation of noise in data, quantification of data redundancy etc. Presentation of SVM for spatially distributed data is given in (Kanevski and Maignan 2004).

Crystal structure of yeast peroxisomal multifunctional enzyme: structural basis for substrate specificity of (3R)-hydroxyacyl-CoA dehydrogenase units.

(3R)-hydroxyacyl-CoA dehydrogenase is part of multifunctional enzyme type 2 (MFE-2) of peroxisomal fatty acid beta-oxidation. The MFE-2 protein from yeasts contains in the same polypeptide chain two dehydrogenases (A and B), which possess difference in substrate specificity. The crystal structure of Candida tropicalis (3R)-hydroxyacyl-CoA dehydrogenase AB heterodimer, consisting of dehydrogenase A and B, determined at the resolution of 2.2A, shows overall similarity with the prototypic counterpart from rat, but also important differences that explain the substrate specificity differences observed. Docking studies suggest that dehydrogenase A binds the hydrophobic fatty acyl chain of a medium-chain-length ((3R)-OH-C10) substrate as bent into the binding pocket, whereas the short-chain substrates are dislocated by two mechanisms: (i) a short-chain-length 3-hydroxyacyl group ((3R)-OH-C4) does not reach the hydrophobic contacts needed for anchoring the substrate into the active site; and (ii) Leu44 in the loop above the NAD(+) cofactor attracts short-chain-length substrates away from the active site. Dehydrogenase B, which can use a (3R)-OH-C4 substrate, has a more shallow binding pocket and the substrate is correctly placed for catalysis. Based on the current structure, and together with the structure of the 2-enoyl-CoA hydratase 2 unit of yeast MFE-2 it becomes obvious that in yeast and mammalian MFE-2s, despite basically identical functional domains, the assembly of these domains into a mature, dimeric multifunctional enzyme is very different.

Formation of aluminosilicate-bearing quartz veins in the Simano nappe (Central Alps): structural, thermobarometric and oxygen isotope constraints

We combined structural analysis, thermobarometry and oxygen isotope geochemistry to constrain the evolution of kyanite and/or andalusite-bearing quartz veins from the amphibolite facies metapelites of the Simano nappe, in the Central Alps of Switzerland. The Simano nappe records a complex polyphase tectonic evolution associated with nappe stacking during Tertiary Alpine collision (D1). The second regional deformation phase (132) is responsible for the main penetrative schistosity and mineral lineation, and formed during top-to-the-north thrusting. During the next stage of deformation (D3) the aluminosilicate-bearing veins formed by crystallization in tension gashes, in tectonic shadows of boudins, as well as along shear bands associated with top-to-the-north shearing. D2 and D3 are coeval with the Early Miocene metamorphic peak, characterised by kyanite + staurolite + garnet + biotite assemblages in metapelites. The peak pressure (P) and temperature (T) conditions recorded are constrained by multiple-equilibrium thermobarometry at 630 +/- 20 degrees C and 8.5 +/- 1 kbar (similar to 27 km depth), which is in agreement with oxygen isotope thermometry indicating isotopic equilibration of quartz-kyanite pairs at 670 +/- 50 degrees C. Quartz-kyanite pairs from the aluminosilicate-bearing quartz veins yield equilibration temperatures of 645 +/- 20 degrees C, confirming that the veins formed under conditions near metamorphic peak. Quartz and kyanite from veins and the surrounding metapelites have comparable isotopic compositions. Local intergranular diffusion in the border of the veins controls the mass-transfer and the growth of the product assemblage, inducing local mobilization of SiO2 and Al2O3. Andalusite is absent from the host rocks, but it is common in quartz veins, where it often pseudomorphs kyanite. For andalusite to be stable at T-max, the pressure in the veins must have been substantially lower than lithostatic. An alternative explanation consistent with structural observations would be inheritance by andalusite of the kyanite isotopic signature during polymorphic transformation after the metamorphic peak.

Global tractography with embedded anatomical priors for quantitative connectivity analysis.

Tractography algorithms provide us with the ability to non-invasively reconstruct fiber pathways in the white matter (WM) by exploiting the directional information described with diffusion magnetic resonance. These methods could be divided into two major classes, local and global. Local methods reconstruct each fiber tract iteratively by considering only directional information at the voxel level and its neighborhood. Global methods, on the other hand, reconstruct all the fiber tracts of the whole brain simultaneously by solving a global energy minimization problem. The latter have shown improvements compared to previous techniques but these algorithms still suffer from an important shortcoming that is crucial in the context of brain connectivity analyses. As no anatomical priors are usually considered during the reconstruction process, the recovered fiber tracts are not guaranteed to connect cortical regions and, as a matter of fact, most of them stop prematurely in the WM; this violates important properties of neural connections, which are known to originate in the gray matter (GM) and develop in the WM. Hence, this shortcoming poses serious limitations for the use of these techniques for the assessment of the structural connectivity between brain regions and, de facto, it can potentially bias any subsequent analysis. Moreover, the estimated tracts are not quantitative, every fiber contributes with the same weight toward the predicted diffusion signal. In this work, we propose a novel approach for global tractography that is specifically designed for connectivity analysis applications which: (i) explicitly enforces anatomical priors of the tracts in the optimization and (ii) considers the effective contribution of each of them, i.e., volume, to the acquired diffusion magnetic resonance imaging (MRI) image. We evaluated our approach on both a realistic diffusion MRI phantom and in vivo data, and also compared its performance to existing tractography algorithms.

Carboxyl terminus structural requirements for glycosyl-phosphatidylinositol anchor addition to cell surface proteins.

Glycosyl phosphatidylinositol (GPI)-anchored proteins contain in their COOH-terminal region a peptide segment that is thought to direct glycolipid addition. This signal has been shown to require a pair of small amino acids positioned 10-12 residues upstream of an hydrophobic C-terminal domain. We analysed the contribution of the region separating the anchor acceptor site and the C-terminal hydrophobic segment by introducing amino acid deletions and substitutions in the spacer element of the GPI-anchored Thy-1 glycoprotein. Deletions of 7 amino acids in this region, as well as the introduction of 2 charged residues, prevented the glycolipid addition to Thy-1, suggesting that the length and the primary sequence of the spacer domain are important determinants in the signal directing GPI anchor transfer onto a newly synthesized polypeptide. Furthermore, we tested these rules by creating a truncated form of the normally transmembranous Herpes simplex virus I glycoprotein D (gDI) and demonstrating that when its C-terminal region displays all the features of a GPI-anchored protein, it is able to direct glycolipid addition onto another cell surface molecule.

Novel nuclear ribonucleoprotein structural components in the dormouse adrenal cortex during hibernation.

Adrenocortical cell nuclei of the dormouse Muscardinus avellanarius were investigated by electron microscopic immunocytochemistry in hibernating, arousing and euthermic individuals. While the basic structural constituents of the cell nucleus did not significantly modify in the three groups, novel structural components were found in nuclei of hibernating dormice. Lattice-like bodies (LBs), clustered granules (CGs), fibrogranular material (FGM) and granules associated with bundles of nucleoplasmic fibrils (NF) all contained ribonucleoproteins (RNPs), as shown by labeling with anti-snRNP (small nuclear RNP), anti-m3G-capped RNA and anti-hnRNP (heterogeneous nuclear RNP) antibodies. Moreover, the FGM also showed immunoreactivity for the proliferation associated nuclear antigen (PANA) and the non-snRNP splicing factor SC-35. All these nuclear structural components disappeared early during arousal and were not found in euthermic animals. These novel RNP-containing structures, which have not been observed in other tissues investigated so far in the same animal model, could represent storage and/or processing sites for pre-mRNA during the extreme metabolic condition of hibernation, to be quickly released upon arousal. NFs, which had been sometimes found devoid of associated granules in nuclei of brown adipose tissue from hi-bernating dormice, were present in much higher amounts in adrenocortical cell nuclei; they do not contain RNPs and their role remains to be elucidated. The possible roles of these structures are discussed in the frame of current knowledge of morpho-functional relationships in the cell nucleus.