Cortical Thickness and Subcortical Gray Matter Reductions in Neuropsychiatric Systemic Lupus Erythematosus

Within systemic lupus erythematosus (SLE) patients can be divided into groups with and without central nervous system involvement, the latter being subcategorized as neuropsychiatric systemic lupus erythematosus (NPSLE). While a number of research groups have investigated NPSLE, there remains a lack of consistent application of this diagnostic criteria within neuroimaging studies. Previous neuroimaging research suggests that SLE patients have reduced subcortical and regional gray matter volumes when compared to controls, and that these group differences may be driven by SLE patients with neuropsychiatric symptoms. The current study sought to compare measures of cortical thickness and subcortical structure volume between NPSLE, SLE, and healthy controls. We hypothesized that patients with NPSLE (N = 21) would have thinner cortex and reduced subcortical gray matter volumes when compared to SLE (N = 16) and control subjects (N = 21). All subjects underwent MRI examinations on a 1.5 Tesla Siemens Sonata scanner. Anatomical reconstruction and segmentation were performed using the FreeSurfer image analysis suite. Cortical and subcortical volumes were extracted from FreeSurfer and analyzed for group differences, controlling for age. The NPSLE group exhibited decreased cortical thickness in clusters of the left frontal and parietal lobes as well as in the right parietal and occipital lobes compared to control subjects. Compared to the SLE group, the NPSLE group exhibited comparable thinning in clusters of the frontal and temporal lobes. Controlling for age, we found that between group effects for subcortical gray matter structures were significant for the thalamus (F = 3.06, p = .04), caudate nucleus (F = 3.19, p = .03), and putamen (F = 4.82, p = .005). These results clarify previous imaging work identifying cortical atrophy in a mixed SLE and NPSLE group, and suggest that neuroanatomical abnormalities are specific to SLE patients diagnosed with neuropsychiatric symptoms. Future work should help elucidate the underlying mechanisms underlying the emerging neurobiological profile seen in NPSLE, as well as clarify the apparent lack of overlap between cortical thinning and functional activation results and other findings pointing to increased functional activation during cognitive tasks

Mining the Mind Research Network: A Novel Framework for Exploring Large Scale, Heterogeneous Translational Neuroscience Research Data Sources

A neuroinformatics (NI) system is critical to brain imaging research in order to shorten the time between study conception and results. Such a NI system is required to scale well when large numbers of subjects are studied. Further, when multiple sites participate in research projects organizational issues become increasingly difficult. Optimized NI applications mitigate these problems. Additionally, NI software enables coordination across multiple studies, leveraging advantages potentially leading to exponential research discoveries. The web-based, Mind Research Network (MRN), database system has been designed and improved through our experience with 200 research studies and 250 researchers from seven different institutions. The MRN tools permit the collection, management, reporting and efficient use of large scale, heterogeneous data sources, e.g., multiple institutions, multiple principal investigators, multiple research programs and studies, and multimodal acquisitions. We have collected and analyzed data sets on thousands of research participants and have set up a framework to automatically analyze the data, thereby making efficient, practical data mining of this vast resource possible. This paper presents a comprehensive framework for capturing and analyzing heterogeneous neuroscience research data sources that has been fully optimized for end-users to perform novel data mining

A Baseline for the Multivariate Comparison of Resting-State Networks

As the size of functional and structural MRI datasets expands, it becomes increasingly important to establish a baseline from which diagnostic relevance may be determined, a processing strategy that efficiently prepares data for analysis, and a statistical approach that identifies important effects in a manner that is both robust and reproducible. In this paper, we introduce a multivariate analytic approach that optimizes sensitivity and reduces unnecessary testing. We demonstrate the utility of this mega-analytic approach by identifying the effects of age and gender on the resting-state networks (RSNs) of 603 healthy adolescents and adults (mean age: 23.4 years, range: 12–71 years). Data were collected on the same scanner, preprocessed using an automated analysis pipeline based in SPM, and studied using group independent component analysis. RSNs were identified and evaluated in terms of three primary outcome measures: time course spectral power, spatial map intensity, and functional network connectivity. Results revealed robust effects of age on all three outcome measures, largely indicating decreases in network coherence and connectivity with increasing age. Gender effects were of smaller magnitude but suggested stronger intra-network connectivity in females and more inter-network connectivity in males, particularly with regard to sensorimotor networks. These findings, along with the analysis approach and statistical framework described here, provide a useful baseline for future investigations of brain networks in health and disease

Laser-Sustained Plasma (LSP) Nitriding of Titanium: A Review

Titanium and its alloys possess several attractive properties that include a high strength-to-weight ratio, biocompatibility, and good corrosion resistance. However, due to their poor wear resistance, titanium components need to undergo surface hardening treatments before being used in applications involving high contact stresses. Laser nitriding is a thermochemical method of enhancing the surface hardness and wear resistance of titanium. This technique entails scanning the titanium substrate under a laser beam near its focal plane in the presence of nitrogen gas flow. At processing conditions characterized by low scan speeds, high laser powers, and small off-focal distances, a nitrogen plasma can be struck near the surface of the titanium substrate. When the substrate is removed, this plasma can be sustained indefinitely and away from any potentially interacting surfaces, by the laser power and a cascade ionization process. This paper presents a critical review of the literature pertaining to the laser nitriding of titanium in the presence of a laser-sustained plasma, with the ultimate objective of forming wide-area, deep, crack-free, wear-resistant nitrided cases on commercially pure titanium substrates

Perceived control in relation to socioeconomic and behavioral resources for health

Perceived control is a personality characteristic that contributes to well-being, but few studies have attempted to integrate the functions of perceived control with those of other determinants of health. This research tested two hypotheses about the functions of perceived control: (a) individual differences in perceived control would account for socioeconomic differences in self-rated health status; (b) performance of health-related behaviors would account for the health benefits of perceived control. Using data from adult, nonproxy respondents in the National Population Health Survey of Canada (1995; n=11,110), confirmatory factor analysis supported a measurement model of self-rated health status composed of two correlated factors: physical health (i.e., chronic conditions, restricted activities, self-rated general health, physical functional capacity) and mental health (i.e., distress, depression). Structural equation modeling supported the first hypothesis, but not the second, regarding perceived control as a determinant of self-rated physical and mental health. Health-related behaviors partially mediated age differences in self-rated health, but different behaviors functioned in this way for men than for women. The findings suggest that psychological process, that of perceiving control over life events, underlies social inequality in health. Health-related behaviors appear not to serve as the primary mechanism through which perceived control influences healthSocioeconomic status Perceived control Health behaviors Health status National Population Health Survey of Canada

Long-term effects of marijuana use on the brain.

The existing literature on the long-term effects of marijuana on the brain provides an inconsistent picture (i.e., presence or absence of structural changes) due to methodological differences across studies. We overcame these methodological issues by collecting multimodal measures in a large group of chronic marijuana using adults with a wide age range that allows for characterization of changes across lifespan without developmental or maturational biases as in other studies. Our findings suggest that chronic marijuana use is associated with complex neuroadaptive processes and that onset and duration of use have unique effects on these processes

Scatterplot showing individual cortical thickness values (in millimeters) obtained from the left rostrofrontal cortex for the sample.

<p>Red squares  =  NPLSE patients; Blue circles  =  SLE patients (blue circles); Black diamonds  =  control subjects, stratified by age. All three groups show decreasing trends for cortical thickness in all significant regions (light blue in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0009302#pone-0009302-g001" target="_blank">Figure 1</a>).</p

Group comparison of cortical thickness differences between SLE patients (N = 16) and NPSLE patients (N = 21).

<p>Images show clusters of lower (blue clusters) cortical thickness values controlling for age. Clusters are displayed in the range of p≤.01 to p≤.0001 (color scale shows −log (10) p-value). Clusters which survived FDR correction for multiple correction (p≤.05 are encircled). Top left  =  left lateral hemisphere; Bottom left  =  left medial hemisphere; Top right  =  right lateral hemisphere; Bottom right  =  right medial hemisphere.</p