Lightweight XML-based query, integration and visualization of distributed, multimodality brain imaging data

A need of many neuroimaging researchers is to integrate multimodality brain data that may be stored in separate databases. To address this need we have developed a framework that provides a uniform XML-based query interface across multiple online data sources. The development of this framework is driven by the need to integrate neurosurgical and neuroimaging data related to language. The data sources for the language studies are 1) a web-accessible relational database of neurosurgical cortical stimulation mapping data (CSM) that includes patient-specific 3-D coordinates of each stimulation site mapped to an MRI reconstruction of the patient brain surface; and 2) an XML database of fMRI and structural MRI data and analysis results, created automatically by a batch program we have embedded in SPM. To make these sources available for querying each is wrapped as an XML view embedded in a web service. A top level web application accepts distributed XQueries over the sources, which are dispatched to the underlying web services. Returned results can be displayed as XML, HTML, CSV (Excel format), a 2-D schematic of a parcellated brain, or a 3-D brain visualization. In the latter case the CSM patient-specific coordinates returned by the query are sent to a transformation web-service for conversion to normalized space, after which they are sent to our 3-D visualization program MindSeer, which is accessed via Java WebStart through a generated link. The anatomical distribution of pooled CSM sites can then be visualized using various surfaces derived from brain atlases. As this framework is further developed and generalized we believe it will have appeal for researchers who wish to query, integrate and visualize results across their own databases as well as those of collaborators

Risk of Performance and Behavioral Health Decrements Due to Inadequate Cooperation, Coordination, Communication, and Psychosocial Adaptation within a Team

A team is defined as: "two or more individuals who interact socially and adaptively, have shared or common goals, and hold meaningful task interdependences; it is hierarchically structured and has a limited life span; in it expertise and roles are distributed; and it is embedded within an organization/environmental context that influences and is influenced by ongoing processes and performance outcomes" (Salas, Stagl, Burke, & Goodwin, 2007, p. 189). From the NASA perspective, a team is commonly understood to be a collection of individuals that is assigned to support and achieve a particular mission. Thus, depending on context, this definition can encompass both the spaceflight crew and the individuals and teams in the larger multi-team system who are assigned to support that crew during a mission. The Team Risk outcomes of interest are predominantly performance related, with a secondary emphasis on long-term health; this is somewhat unique in the NASA HRP in that most Risk areas are medically related and primarily focused on long-term health consequences. In many operational environments (e.g., aviation), performance is assessed as the avoidance of errors. However, the research on performance errors is ambiguous. It implies that actions may be dichotomized into "correct" or "incorrect" responses, where incorrect responses or errors are always undesirable. Researchers have argued that this dichotomy is a harmful oversimplification, and it would be more productive to focus on the variability of human performance and how organizations can manage that variability (Hollnagel, Woods, & Leveson, 2006) (Category III1). Two problems occur when focusing on performance errors: 1) the errors are infrequent and, therefore, difficult to observe and record; and 2) the errors do not directly correspond to failure. Research reveals that humans are fairly adept at correcting or compensating for performance errors before such errors result in recognizable or recordable failures. Astronauts are notably adept high performers. Most failures are recorded only when multiple, small errors occur and humans are unable to recognize and correct or compensate for these errors in time to prevent a failure (Dismukes, Berman, Loukopoulos, 2007) (Category III). More commonly, observers record variability in levels of performance. Some teams commit no observable errors but fail to achieve performance objectives or perform only adequately, while other teams commit some errors but perform spectacularly. Successful performance, therefore, cannot be viewed as simply the absence of errors or the avoidance of failure Johnson Space Center (JSC) Joint Leadership Team, 2008). While failure is commonly attributed to making a major error, focusing solely on the elimination of error(s) does not significantly reduce the risk of failure. Failure may also occur when performance is simply insufficient or an effort is incapable of adjusting sufficiently to a contextual change (e.g., changing levels of autonomy)

Designing hollow nano gold golf balls.

Hollow/porous nanoparticles, including nanocarriers, nanoshells, and mesoporous materials have applications in catalysis, photonics, biosensing, and delivery of theranostic agents. Using a hierarchical template synthesis scheme, we have synthesized a nanocarrier mimicking a golf ball, consisting of (i) solid silica core with a pitted gold surface and (ii) a hollow/porous gold shell without silica. The template consisted of 100 nm polystyrene beads attached to a larger silica core. Selective gold plating of the core followed by removal of the polystyrene beads produced a golf ball-like nanostructure with 100 nm pits. Dissolution of the silica core produced a hollow/porous golf ball-like nanostructure

Effects of Weight-Bearing on Tibiofemoral, Patellofemoral, and Patellar Tendon Kinematics in Older Adults

Quantification of natural knee kinematics is essential for the assessment of joint function in the diagnosis of pathologies. Combined measurements of tibiofemoral and patellofemoral joint kinematics are necessary because knee pathologies, such as progression of osteoarthritis and patellar instability, are a frequent concern in both articulations. Combined measurement of tibiofemoral and patellofemoral kinematics also enables calculation of important quantities, specifically patellar tendon angle, which partly determines the loading vector at the tibiofemoral joint and patellar tendon moment arm. The goals of this research were to measure the differences in tibiofemoral and patellofemoral kinematics, patellar tendon angle (PTA), and patellar tendon moment arm (PTMA) that occur during non-weight-bearing and weight-bearing activities in older adults. Methods: High-speed stereo radiography was used to measure the kinematics of the tibiofemoral and patellofemoral joints in subjects as they performed seated, non-weight-bearing knee extension and two weight-bearing activities: lunge and chair rise. PTA and PTMA were extracted from the subject’s patellofemoral and tibiofemoral kinematics. Kinematics and the root mean square difference (RMSD) between non-weight-bearing and weight-bearing activities were compared across subjects and activities. Results: Internal rotation increased with weight-bearing (mean RMSD from knee extension was 4.2 ± 2.4° for lunge and 3.6 ± 1.8° for chair rise), and anterior translation was also greater (mean RMSD from knee extension was 2.2 ± 1.2 mm for lunge and 2.3 ± 1.4 mm for chair rise). Patellar tilt and medial–lateral translation changed from non-weight-bearing to weight-bearing. Changes of the patellar tendon from non-weight-bearing to weight-bearing were significant only for PTMA. Conclusions: While weight-bearing elicited changes in knee kinematics, in most degrees of freedoms, these differences were exceeded by intersubject differences. These results provide comparative kinematics for the evaluation of knee pathology and treatment in older adults

An Automated Process for 2D and 3D Finite Element Overclosure and Gap Adjustment using Radial Basis Function Networks

In biomechanics, geometries representing complicated organic structures are consistently segmented from sparse volumetric data or morphed from template geometries resulting in initial overclosure between adjacent geometries. In FEA, these overclosures result in numerical instability and inaccuracy as part of contact analysis. Several techniques exist to fix overclosures, but most suffer from several drawbacks. This work introduces a novel automated algorithm in an iterative process to remove overclosure and create a desired minimum gap for 2D and 3D finite element models. The RBF Network algorithm was introduced by its four major steps to remove the initial overclosure. Additionally, the algorithm was validated using two test cases against conventional nodal adjustment. The first case compared the ability of each algorithm to remove differing levels of overclosure between two deformable muscles and the effects on mesh quality. The second case used a non-deformable femur and deformable distal femoral cartilage geometry with initial overclosure to test both algorithms and observe the effects on the resulting contact FEA. The RBF Network in the first case study was successfully able to remove all overclosures. In the second case, the nodal adjustment method failed to create a usable FEA model, while the RBF Network had no such issue. This work proposed an algorithm to remove initial overclosures prior to FEA that has improved performance over conventional nodal adjustment, especially in complicated situations and those involving 3D elements. The work can be included in existing FEA modeling workflows to improve FEA results in situations involving sparse volumetric segmentation and mesh morphing. This algorithm has been implemented in MATLAB, and the source code is publicly available to download at the following GitHub repository: https://github.com/thor-andreassen/femorsComment: 26 Pages, 5 Figures, 2 Table

Integration of Neural Architecture within a Finite Element Framework for Improved Neuromusculoskeletal Modeling

Neuromusculoskeletal (NMS) models can aid in studying the impacts of the nervous and musculoskeletal systems on one another. These computational models facilitate studies investigating mechanisms and treatment of musculoskeletal and neurodegenerative conditions. In this study, we present a predictive NMS model that uses an embedded neural architecture within a finite element (FE) framework to simulate muscle activation. A previously developed neuromuscular model of a motor neuron was embedded into a simple FE musculoskeletal model. Input stimulation profiles from literature were simulated in the FE NMS model to verify effective integration of the software platforms. Motor unit recruitment and rate coding capabilities of the model were evaluated. The integrated model reproduced previously published output muscle forces with an average error of 0.0435 N. The integrated model effectively demonstrated motor unit recruitment and rate coding in the physiological range based upon motor unit discharge rates and muscle force output. The combined capability of a predictive NMS model within a FE framework can aid in improving our understanding of how the nervous and musculoskeletal systems work together. While this study focused on a simple FE application, the framework presented here easily accommodates increased complexity in the neuromuscular model, the FE simulation, or both

Crystal Structure of \u3cem\u3eYersinia pestis\u3c/em\u3e Virulence Factor YfeA Reveals Two Polyspecific Metal-Binding Sites

Gram-negative bacteria use siderophores, outer membrane receptors, inner membrane transporters and substrate-binding proteins (SBPs) to transport transition metals through the periplasm. The SBPs share a similar protein fold that has undergone significant structural evolution to communicate with a variety of differentially regulated transporters in the cell. In Yersinia pestis, the causative agent of plague, YfeA (YPO2439, y1897), an SBP, is important for full virulence during mammalian infection. To better understand the role of YfeA in infection, crystal structures were determined under several environmental conditions with respect to transition-metal levels. Energy-dispersive X-ray spectroscopy and anomalous X-ray scattering data show that YfeA is polyspecific and can alter its substrate specificity. In minimal-media experiments, YfeA crystals grown after iron supplementation showed a threefold increase in iron fluorescence emission over the iron fluorescence emission from YfeA crystals grown from nutrient-rich conditions, and YfeA crystals grown after manganese supplementation during overexpression showed a fivefold increase in manganese fluorescence emission over the manganese fluorescence emission from YfeA crystals grown from nutrient-rich conditions. In all experiments, the YfeA crystals produced the strongest fluorescence emission from zinc and could not be manipulated otherwise. Additionally, this report documents the discovery of a novel surface metal-binding site that prefers to chelate zinc but can also bind manganese. Flexibility across YfeA crystal forms in three loops and a helix near the buried metal-binding site suggest that a structural rearrangement is required for metal loading and unloading

Who is to blame? The relationship between ingroup identification and relative deprivation is moderated by ingroup attributions

Contradictory evidence can be found in the literature about whether ingroup identification and perceived relative deprivation are positively or negatively related. Indeed, theoretical arguments can be made for both effects. It was proposed that the contradictory findings can be explained by considering a hitherto unstudied moderator: The extent to which deprivation is attributed to the ingroup. It was hypothesised that identification would only have a negative impact on deprivation, and that deprivation would only have a negative impact on identification, if ingroup attributions are high. To test this, attributions to the ingroup were experimentally manipulated among British student participants (N = 189) who were asked about their perceived deprivation vis-à-vis German students, yield ing support for the hypotheses

FDG-PET Quantification of Lung Inflammation with Image-Derived Blood Input Function in Mice

Dynamic FDG-PET imaging was used to study inflammation in lungs of mice following administration of a virulent strain of Klebsiella (K.) pneumoniae. Net whole-lung FDG influx constant (Ki) was determined in a compartment model using an image-derived blood input function. Methods. K. pneumoniae (~3 x 105 CFU) was intratracheally administered to six mice with 6 other mice serving as controls. Dynamic FDG-PET and X-Ray CT scans were acquired 24 hr after K. pneumoniae administration. The experimental lung time activity curves were fitted to a 3-compartment FDG model to obtain Ki. Following imaging, lungs were excised and immunohistochemistry analysis was done to assess the relative presence of neutrophils and macrophages. Results. Mean Ki for control and K. pneumoniae infected mice were (5.1 ± 1.2) ×10−3 versus (11.4 ± 2.0) ×10−3 min−1, respectively, revealing a 2.24 fold significant increase (P = 0.0003) in the rate of FDG uptake in the infected lung. Immunohistochemistry revealed that cellular lung infiltrate was almost exclusively neutrophils. Parametric Ki maps by Patlak analysis revealed heterogeneous inflammatory foci within infected lungs. Conclusion. The kinetics of FDG uptake in the lungs of mice can be noninvasively quantified by PET with a 3-compartment model approach based on an image-derived input function

Standard Measures are Inadequate to Monitor Pediatric Adherence in a Resource-Limited Setting

This study aims to compare the use and cost of objective and subjective measures of adherence to pediatric antiretroviral treatment in a primary care facility in South Africa. In a 1-month longitudinal study of 53 caregiver-child dyads, pharmacy refill (PR), measurement of returned syrups (RS), caregiver self-report (3DR) and Visual Analogue Scale (VAS) were compared to Medication Event Monitoring System (MEMS). Adherence was 100% for both VAS and 3DR; by PR and RS 100% and 103%, respectively. MEMS showed that 92% of prescribed doses were administered, but only 66% of these within the correct 12-hourly interval. None of the four measures correlated significantly with MEMS. MEMS data suggest that timing of doses is often more deviant from prescribed than expected and should be better addressed when monitoring adherence. Of all, MEMS was by far the most expensive measure. Alternative, cheaper electronic devices need to be more accessible in resource-limited settings