A genetic analysis of cortical thickness in 372 twins

Imaging genetics is a new field of neuroscience that blends methods from computational anatomy and quantitative genetics to identify genetic influences on brain structure and function. Here we analyzed brain MRI data from 372 young adult twins to identify cortical regions in which gray matter volume is influenced by genetic differences across subjects. Thickness maps, reconstructed from surface models of the cortical gray/white and gray/CSF interfaces, were smoothed with a 25 mm FWHM kernel and automatically parcellated into 34 regions of interest per hemisphere. In structural equation models fitted to volume values at each surface vertex, we computed components of variance due to additive genetic (A), shared (C) and unique (E) environmental factors, and tested their significance. Cortical regions in the vicinity of the perisylvian language cortex, and at the frontal and temporal poles, showed significant additive genetic variance, suggesting that volume measures from these regions may provide quantitative phenotypes to narrow the search for quantitative trait loci that influence brain structure.

Comparison of fractional and geodesic anisotropy in diffusion tensor images of 90 monozygotic and dizygotic twins

We used diffusion tensor magnetic resonance imaging (DTI) to reveal the extent of genetic effects on brain fiber microstructure, based on tensor-derived measures, in 22 pairs of monozygotic (MZ) twins and 23 pairs of dizygotic (DZ) twins (90 scans). After Log-Euclidean denoising to remove rank-deficient tensors, DTI volumes were fluidly registered by high-dimensional mapping of co-registered MP-RAGE scans to a geometrically-centered mean neuroanatomical template. After tensor reorientation using the strain of the 3D fluid transformation, we computed two widely used scalar measures of fiber integrity: fractional anisotropy (FA), and geodesic anisotropy (GA), which measures the geodesic distance between tensors in the symmetric positive-definite tensor manifold. Spatial maps of intraclass correlations (r) between MZ and DZ twins were compared to compute maps of Falconer's heritability statistics, i.e. the proportion of population variance explainable by genetic differences among individuals. Cumulative distribution plots (CDF) of effect sizes showed that the manifold measure, GA, comparably the Euclidean measure, FA, in detecting genetic correlations. While maps were relatively noisy, the CDFs showed promise for detecting genetic influences on brain fiber integrity as the current sample expands.

Best individual template selection from deformation tensor minimization

We study the influence of the choice of template in tensor-based morphometry. Using 3D brain MR images from 10 monozygotic twin pairs, we defined a tensor-based distance in the log-Euclidean framework [1] between each image pair in the study. Relative to this metric, twin pairs were found to be closer to each other on average than random pairings, consistent with evidence that brain structure is under strong genetic control. We also computed the intraclass correlation and associated permutation p-value at each voxel for the determinant of the Jacobian matrix of the transformation. The cumulative distribution function (cdf) of the p-values was found at each voxel for each of the templates and compared to the null distribution. Surprisingly, there was very little difference between CDFs of statistics computed from analyses using different templates. As the brain with least log-Euclidean deformation cost, the mean template defined here avoids the blurring caused by creating a synthetic image from a population, and when selected from a large population, avoids bias by being geometrically centered, in a metric that is sensitive enough to anatomical similarity that it can even detect genetic affinity among anatomies.

Scalar connectivity measures from fast-marching tractography reveal heritability of white matter architecture

Recent advances in diffusion-weighted MRI (DWI) have enabled studies of complex white matter tissue architecture in vivo. To date, the underlying influence of genetic and environmental factors in determining central nervous system connectivity has not been widely studied. In this work, we introduce new scalar connectivity measures based on a computationally-efficient fast-marching algorithm for quantitative tractography. We then calculate connectivity maps for a DTI dataset from 92 healthy adult twins and decompose the genetic and environmental contributions to the variance in these metrics using structural equation models. By combining these techniques, we generate the first maps to directly examine genetic and environmental contributions to brain connectivity in humans. Our approach is capable of extracting statistically significant measures of genetic and environmental contributions to neural connectivity.

Assessment of dynamic susceptibility contrast cerebral blood flow response to amphetamine challenge: A human pharmacological magnetic resonance imaging study at 1.5 and 4 T

Pharmacological MRI (phMRI) techniques can be used to monitor the neurophysiological effects of central nervous system (CNS) active drugs. In this study, we investigated whether dynamic susceptibility contrast (DSC) perfusion imaging employing the use of superparamagnetic iron oxide nanoparticles (Resovist) could be used to measure hemodynamic response to d-amphetamine challenge in human subjects at both 1.5 and 4 T. Significant changes in cerebral blood flow (CBF) were found in focal regions associated with the nigrostriatal circuit and mesolimbic and mesocortical dopaminergic pathways. More significant CBF responses were found at higher field strength, mainly within striatal structures. The results from this study indicate that DSC perfusion imaging using Resovist can be used to assess the efficacy of CNS-active drugs and may play a role in the development of novel psychiatric therapies at the preclinical level. © 2005 Wiley-Liss, Inc.

Diffusion indices on magnetic resonance imaging and neuropsychological performance in amnestic mild cognitive impairment

Background: Magnetic resonance diffusion tensor imaging (DTI) shows promise in the early detection of microstructural pathophysiological changes in the brain. Objectives: To measure microstructural differences in the brains of participants with amnestic mild cognitive impairment (MCI) compared with an age-matched control group using an optimised DTI technique with fully automated image analysis tools and to investigate the correlation between diffusivity measurements and neuropsychological performance scores across groups. Methods: 34 participants (17 participants with MCI, 17 healthy elderly adults) underwent magnetic resonance imaging (MRI)-based DTI. To control for the effects of anatomical variation, diffusion images of all participants were registered to standard anatomical space. Significant statistical differences in diffusivity measurements between the two groups were determined on a pixel-by-pixel basis using gaussian random field theory. Results: Significantly raised mean diffusivity measurements (p<0.001) were observed in the left and right entorhinal cortices (BA28), posterior occipital-parietal cortex (BA18 and BA19), right parietal supramarginal gyrus (BA40) and right frontal precentral gyri (BA4 and BA6) in participants with MCI. With respect to fractional anisotropy, participants with MCI had significantly reduced measurements (p<0.001) in the limbic parahippocampal subgyral white matter, right thalamus and left posterior cingulate. Pearson's correlation coefficients calculated across all participants showed significant correlations between neuropsychological assessment scores and regional measurements of mean diffusivity and fractional anisotropy. Conclusions: DTI-based diffusivity measures may offer a sensitive method of detecting subtle microstructural brain changes associated with preclinical Alzheimer's disease.

Magnetic nanoparticles boosting the osmotic efficiency of a polymeric FO draw agent: Effect of polymer conformation

Poly sodium acrylate (PSA)-coated Magnetic Nanoparticles (PSA-MNPs) were synthesized as smart osmotic draw agent (SMDA) for water desalination by forward osmosis (FO) process. The PSA-coated MNPs demonstrated significantly higher osmotic pressure (~ 30 fold) as well as high FO water flux (~ 2–3 fold) when compared to their polymer (polyelectrolyte) counterpart, even at a very low concentration of ~ 0.13 wt.% in the draw solution. The PSA polymer chain conformation – coiled to extended – demonstrates a significant impact on the availability of the polymer hydrophilic groups in solution which is the driving force to attain higher osmotic pressure and water flux. When an optimum concentration of the polymer was anchored to a NP surface, the polymer chains assume an extended open conformation making the functional hydrophilic groups available to attract water molecules. This in turn boosts the osmotic pressure and FO water flux of the PSA-MNP draw agents. The low concentration of the PSA-MNP osmotic agent and the associated high water flux enhances the cost-effectiveness of our proposed SMDA system. In addition, easier magnetic separation and regeneration of the SMDA also improves its usability making it efficient, cost-effective and environment-friendly.

Towards the development of a low cost airborne sensing system to monitor dust particles after blasting at open-pit mine sites

Blasting is an integral part of large-scale open cut mining that often occurs in close proximity to population centers and often results in the emission of particulate material and gases potentially hazardous to health. Current air quality monitoring methods rely on limited numbers of fixed sampling locations to validate a complex fluid environment and collect sufficient data to confirm model effectiveness. This paper describes the development of a methodology to address the need of a more precise approach that is capable of characterizing blasting plumes in near-real time. The integration of the system required the modification and integration of an opto-electrical dust sensor, SHARP GP2Y10, into a small fixed-wing and multi-rotor copter, resulting in the collection of data streamed during flight. The paper also describes the calibration of the optical sensor with an industry grade dust-monitoring device, Dusttrak 8520, demonstrating a high correlation between them, with correlation coefficients (R2) greater than 0.9. The laboratory and field tests demonstrate the feasibility of coupling the sensor with the UAVs. However, further work must be done in the areas of sensor selection and calibration as well as flight planning.

Lateralization of temporal lobe epilepsy based on resting-state functional magnetic resonance imaging and machine learning

Lateralization of temporal lobe epilepsy (TLE) is critical for successful outcome of surgery to relieve seizures. TLE affects brain regions beyond the temporal lobes and has been associated with aberrant brain networks, based on evidence from functional magnetic resonance imaging. We present here a machine learning-based method for determining the laterality of TLE, using features extracted from resting-state functional connectivity of the brain. A comprehensive feature space was constructed to include network properties within local brain regions, between brain regions, and across the whole network. Feature selection was performed based on random forest and a support vector machine was employed to train a linear model to predict the laterality of TLE on unseen patients. A leave-one-patient-out cross validation was carried out on 12 patients and a prediction accuracy of 83% was achieved. The importance of selected features was analyzed to demonstrate the contribution of resting-state connectivity attributes at voxel, region, and network levels to TLE lateralization.

Spinal inflammation in the absence of sacroiliac joint inflammation on magnetic resonance imaging in patients with active nonradiographic axial spondyloarthritis

Objective: To evaluate the presence of spinal inflammation with and without sacroiliac (SI) joint inflammation on magnetic resonance imaging (MRI) in patients with active nonradiographic axial spondyloarthritis (SpA), and to compare the disease characteristics of these subgroups. Methods: ABILITY-1 is a multicenter, randomized, controlled trial of adalimumab versus placebo in patients with nonradiographic axial SpA classified using the Assessment of SpondyloArthritis international Society axial SpA criteria. Baseline MRIs were centrally scored independently by 2 readers using the Spondyloarthritis Research Consortium of Canada (SPARCC) method for the SI joints and the SPARCC 6-discovertebral unit method for the spine. Positive evidence of inflammation on MRI was defined as a SPARCC score of >2 for either the SI joints or the spine. Results: Among patients with baseline SPARCC scores, 40% had an SI joint score of >2 and 52% had a spine score of >2. Forty-nine percent of patients with baseline SI joint scores of <2, and 58% of those with baseline SI joint scores of >2, had a spine score of >2. Comparison of baseline disease characteristics by baseline SI joint and spine scores showed that a greater proportion of patients in the subgroup with a baseline SPARCC score of >2 for both SI joints and spine were male, and patients with spine and SI joint scores of <2 were younger and had shorter symptom duration. SPARCC spine scores correlated with baseline symptom duration, and SI joint scores correlated negatively with the baseline Bath Ankylosing Spondylitis Disease Activity Index, but neither correlated with the baseline Ankylosing Spondylitis Disease Activity Score, total back pain, the patient's global assessment of disease activity, the Bath Ankylosing Spondylitis Functional Index, morning stiffness, nocturnal pain, or C-reactive protein level. Conclusion: Assessment by experienced readers showed that spinal inflammation on MRI might be observed in half of patients with nonradiographic axial SpA without SI joint inflammation.

Metrological assessment of a portable analyzer for monitoring the particle size distribution of ultrafine particles

Adverse health effects caused by worker exposure to ultrafine particles have been detected in recent years. The scientific community focuses on the assessment of ultrafine aerosols in different microenvironments in order to determine the related worker exposure/dose levels. To this end, particle size distribution measurements have to be taken along with total particle number concentrations. The latter are obtainable through hand-held monitors. A portable particle size distribution analyzer (Nanoscan SMPS 3910, TSI Inc.) was recently commercialized, but so far no metrological assessment has been performed to characterize its performance with respect to well-established laboratory- based instruments such as the scanning mobility particle sizer (SMPS) spectrometer. The present paper compares the aerosol monitoring capability of the Nanoscan SMPS to the laboratory SMPS in order to evaluate whether the Nanoscan SMPS is suitable for field experiments designed to characterize particle exposure in different microenvironments. Tests were performed both in a Marple calm air chamber, where fresh diesel particulate matter and atomized dioctyl phthalate particles were monitored, and in microenvironments, where outdoor, urban, indoor aged, and indoor fresh aerosols were measured. Results show that the Nanoscan SMPS is able to properly measure the particle size distribution for each type of aerosol investigated, but it overestimates the total particle number concentration in the case of fresh aerosols. In particular, the test performed in the Marple chamber showed total concentrations up to twice those measured by the laboratory SMPS—likely because of the inability of the Nanoscan SMPS unipolar charger to properly charge aerosols made up of aggregated particles. Based on these findings, when field test exposure studies are conducted, the Nanoscan SMPS should be used in tandem

On the interaction between radon progeny and particles generated by electronic and traditional cigarettes

During their entire lives, people are exposed to the pollutants present in indoor air. Recently, Electronic Nicotine Delivery Systems, mainly known as electronic cigarettes, have been widely commercialized: they deliver particles into the lungs of the users but a “second-hand smoke” has yet to be associated to this indoor source. On the other hand, the naturally-occurring radioactive gas, i.e. radon, represents a significant risk for lung cancer, and the cumulative action of these two agents could be worse than the agents separately would. In order to deepen the interaction between radon progeny and second-hand aerosol from different types of cigarettes, a designed experimental study was carried out by generating aerosol from e-cigarette vaping as well as from second-hand traditional smoke inside a walk-in radon chamber at the National Institute of Ionizing Radiation Metrology (INMRI) of Italy. In this chamber, the radon present in air comes naturally from the floor and ambient conditions are controlled. To characterize the sidestream smoke emitted by cigarettes, condensation particle counters and scanning mobility particle sizer were used. Radon concentration in the air was measured through an Alphaguard ionization chamber, whereas the measurement of radon decay product in the air was performed with the Tracelab BWLM Plus-2S Radon daughter Monitor. It was found an increase of the Potential Alpha-Energy Concentration (PAEC) due to the radon decay products attached to aerosol for higher particle number concentrations. This varied from 7.47 ± 0.34 MeV L−1 to 12.6 ± 0.26 MeV L−1 (69%) for the e-cigarette. In the case of traditional cigarette and at the same radon concentration, the increase was from 14.1 ± 0.43 MeV L−1 to 18.6 ± 0.19 MeV L−1 (31%). The equilibrium factor increases, varying from 23.4% ± 1.11% to 29.5% ± 0.26% and from 30.9% ± 1.0% to 38.1 ± 0.88 for the e-cigarette and traditional cigarette, respectively. These growths still continue for long time after the combustion, by increasing the exposure risk.

Preparation of magnetic porous ceramsite and its application in biological aerated filters

Ceramsite plays a significant role as a biological aerated filter (BAF) in the treatment of wastewater. In this study, a mixture of goethite, sawdust and palygorskite clay was thermally treated to form magnetic porous ceramsite (MPC). An optimization experiment was conducted to measure the compressive strength of the MPC. X-ray diffraction (XRD), scanning electron microscopy (SEM), and polarizing microscopy (PM) characterized the pore structure of the MPC. The results show that a combination of goethite, sawdust and palygorskite clay with a mass ratio of 10:2:5 is suitable for the formation of MPC. The compressive strength of MPC conforms to the Chinese national industrial standard (CJ/T 299-2008) for wastewater treatment. The SEM and PM results also show that the uniform and interconnected pores in MPC were well suited for microbial growth. The MPC produced in this study can serve as a biomedium for advanced wastewater treatment.

Single-walled carbon nanotube-based polymer monoliths for the enantioselective nano-liquid chromatographic separation of racemic pharmaceuticals

Many protocols have been used for extraction of DNA from Thraustochytrids. These generally involve the use of CTAB, phenol/chloroform and ethanol. They also feature mechanical grinding, sonication, N2 freezing or bead beating. However, the resulting chemical and physical damage to extracted DNA reduces its quality. The methods are also unsuitable for large numbers of samples. Commercially-available DNA extraction kits give better quality and yields but are expensive. Therefore, an optimized DNA extraction protocol was developed which is suitable for Thraustochytrids to both minimise expensive and time-consuming steps prior to DNA extraction and also to improve the yield. The most effective method is a combination of single bead in TissueLyser (Qiagen) and Proteinase K. Results were conclusive: both the quality and the yield of extracted DNA were higher than with any other method giving an average yield of 8.5 µg/100 mg biomass.

Pre-lithiation of onion-like carbon/MoS2 nano-urchin anodes for high-performance rechargeable lithium ion batteries

Hybrid urchin-like nanostructures composed of a spherical onion-like carbon (OLC) core and MoS2 nanoleaves were synthesized by a simple solvothermal method followed by thermal annealing treatment. Compared to commercial MoS2 powder, MoS2/OLC nanocomposites exhibit enhanced electrochemical performance as anode materials of lithium-ion batteries (LIBs) with a specific capacity of 853 mA h g−1 at a current density of 50 mA g−1 after 60 cycles, and a moderate initial coulombic efficiency of 71.1%. Furthermore, a simple pre-lithiation method based on direct contact of lithium foil with MoS2/OLC nano-urchins was used to achieve a very high coulombic efficiency of 97.6% in the first discharge/charge cycle, which is at least 26% higher compared to that of pristine MoS2/OLC nano-urchins. This pre-lithiation method can be generalized to develop other carbon-metal sulfide nanohybrids for LIB anode materials. These results may open up a new avenue for the development of the next-generation high-performance LIBs.