Hydrogeophysical data integration at larger scales: Application of Bayesian sequential simulation for the characterization of heterogeneous alluvial aquifers

Knowledge of the spatial distribution of hydraulic conductivity (K) within an aquifer is critical for reliable predictions of solute transport and the development of effective groundwater management and/or remediation strategies. While core analyses and hydraulic logging can provide highly detailed information, such information is inherently localized around boreholes that tend to be sparsely distributed throughout the aquifer volume. Conversely, larger-scale hydraulic experiments like pumping and tracer tests provide relatively low-resolution estimates of K in the investigated subsurface region. As a result, traditional hydrogeological measurement techniques contain a gap in terms of spatial resolution and coverage, and they are often alone inadequate for characterizing heterogeneous aquifers. Geophysical methods have the potential to bridge this gap. The recent increased interest in the application of geophysical methods to hydrogeological problems is clearly evidenced by the formation and rapid growth of the domain of hydrogeophysics over the past decade (e.g., Rubin and Hubbard, 2005).

Protein interaction data curation: the International Molecular Exchange (IMEx) consortium.

The International Molecular Exchange (IMEx) consortium is an international collaboration between major public interaction data providers to share literature-curation efforts and make a nonredundant set of protein interactions available in a single search interface on a common website (http://www.imexconsortium.org/). Common curation rules have been developed, and a central registry is used to manage the selection of articles to enter into the dataset. We discuss the advantages of such a service to the user, our quality-control measures and our data-distribution practices.

Interhemispheric distribution of Alzheimer disease and vascular pathology in brain aging

BACKGROUND AND PURPOSE: Most of the neuropathological studies in brain aging were based on the assumption of a symmetrical right-left hemisphere distribution of both Alzheimer disease and vascular pathology. To explore the impact of asymmetrical lesion formation on cognition, we performed a clinicopathological analysis of 153 cases with mixed pathology except macroinfarcts. METHODS: Cognitive status was assessed prospectively using the Clinical Dementia Rating scale; neuropathological evaluation included assessment of Braak neurofibrillary tangle and Ass deposition staging, microvascular pathology, and lacunes. The right-left hemisphere differences in neuropathological scores were evaluated using the Wilcoxon signed rank test. The relationship between the interhemispheric distribution of lesions and Clinical Dementia Rating scores was assessed using ordered logistic regression. RESULTS: Unlike Braak neurofibrillary tangle and Ass deposition staging, vascular scores were significantly higher in the left hemisphere for all Clinical Dementia Rating scores. A negative relationship was found between Braak neurofibrillary tangle, but not Ass staging, and vascular scores in cases with moderate to severe dementia. In both hemispheres, Braak neurofibrillary tangle staging was the main determinant of cognitive decline followed by vascular scores and Ass deposition staging. The concomitant predominance of Alzheimer disease and vascular pathology in the right hemisphere was associated with significantly higher Clinical Dementia Rating scores. CONCLUSIONS: Our data show that the cognitive impact of Alzheimer disease and vascular lesions in mixed cases may be assessed unilaterally without major information loss. However, interhemispheric differences and, in particular, increased vascular and Alzheimer disease burden in the right hemisphere may increase the risk for dementia in this group.

Soft tissue artifact distribution on lower limbs during treadmill gait: Influence of skin markers' location on cluster design.

Segment poses and joint kinematics estimated from skin markers are highly affected by soft tissue artifact (STA) and its rigid motion component (STARM). While four marker-clusters could decrease the STA non-rigid motion during gait activity, other data, such as marker location or STARM patterns, would be crucial to compensate for STA in clinical gait analysis. The present study proposed 1) to devise a comprehensive average map illustrating the spatial distribution of STA for the lower limb during treadmill gait and 2) to analyze STARM from four marker-clusters assigned to areas extracted from spatial distribution. All experiments were realized using a stereophotogrammetric system to track the skin markers and a bi-plane fluoroscopic system to track the knee prosthesis. Computation of the spatial distribution of STA was realized on 19 subjects using 80 markers apposed on the lower limb. Three different areas were extracted from the distribution map of the thigh. The marker displacement reached a maximum of 24.9mm and 15.3mm in the proximal areas of thigh and shank, respectively. STARM was larger on thigh than the shank with RMS error in cluster orientations between 1.2° and 8.1°. The translation RMS errors were also large (3.0mm to 16.2mm). No marker-cluster correctly compensated for STARM. However, the coefficient of multiple correlations exhibited excellent scores between skin and bone kinematics, as well as for STARM between subjects. These correlations highlight dependencies between STARM and the kinematic components. This study provides new insights for modeling STARM for gait activity.