Formation of Hydrogenated Graphene Nanoripples by Strain Engineering and Directed Surface Self-assembly

We propose a new class of semiconducting graphene-based nanostructures: hydrogenated graphene nanoripples (HGNRs), based on continuum-mechanics analysis and first principles calculations. They are formed via a two-step combinatorial approach: first by strain engineered pattern formation of graphene nanoripples, followed by a curvature-directed self-assembly of H adsorption. It offers a high level of control of the structure and morphology of the HGNRs, and hence their band gaps which share common features with graphene nanoribbons. A cycle of H adsorption/desorption at/from the same surface locations completes a reversible metal-semiconductor-metal transition with the same band gap.Comment: 11 pages, 5 figure

DPARSF: A MATLAB Toolbox for “Pipeline” Data Analysis of Resting-State fMRI

Resting-state functional magnetic resonance imaging (fMRI) has attracted more and more attention because of its effectiveness, simplicity and non-invasiveness in exploration of the intrinsic functional architecture of the human brain. However, user-friendly toolbox for “pipeline” data analysis of resting-state fMRI is still lacking. Based on some functions in Statistical Parametric Mapping (SPM) and Resting-State fMRI Data Analysis Toolkit (REST), we have developed a MATLAB toolbox called Data Processing Assistant for Resting-State fMRI (DPARSF) for “pipeline” data analysis of resting-state fMRI. After the user arranges the Digital Imaging and Communications in Medicine (DICOM) files and click a few buttons to set parameters, DPARSF will then give all the preprocessed (slice timing, realign, normalize, smooth) data and results for functional connectivity, regional homogeneity, amplitude of low-frequency fluctuation (ALFF), and fractional ALFF. DPARSF can also create a report for excluding subjects with excessive head motion and generate a set of pictures for easily checking the effect of normalization. In addition, users can also use DPARSF to extract time courses from regions of interest

Lifespan associations of resting-state brain functional networks with ADHD symptoms

Attention-deficit/hyperactivity disorder (ADHD) is increasingly being diagnosed in both children and adults, but the neural mechanisms that underlie its distinct symptoms and whether children and adults share the same mechanism remain poorly understood. Here, we used a nested-spectral partition (NSP) approach to study the resting-state brain functional networks of ADHD patients (n=97) and healthy controls (HCs, n=97) across the lifespan (7-50 years). Compared to the linear lifespan associations of brain functional segregation and integration with age in HCs, ADHD patients have a quadratic association in the whole brain and in most functional systems, whereas the limbic system dominantly affected by ADHD has a linear association. Furthermore, the limbic system better predicts hyperactivity, and the salient attention system better predicts inattention. These predictions are shared in children and adults with ADHD. Our findings reveal a lifespan association of brain networks with ADHD symptoms and provide potential shared neural bases of distinct ADHD symptoms in children and adults.Comment: 28 pages, 4 figure

Polyethylene glycol phase change material embedded in a hierarchical porous carbon with superior thermal storage capacity and excellent stability

Hierarchical porous materials are recommended to trade off the mismatch between high loading and efficient crystallization in pore-based composite phase change materials (PCMs), coupling the functions of expanded pores (mesopores and macropores) along with maintained micropores. Hierarchical porous carbon (HPC) was successfully synthesized from metal organic framework MOF-5 with a large specific surface area (1345 m2/g) and high pore volume (2.69 cm3/g). The adsorption capacity of HPC for low temperature PCMs, polyethylene glycol (PEG) and stearic acid (SA) reaches over 90 wt%. The introduction of HPC has very little impact on the crystallinity of the PCMs, as a result, the composites possess similar high thermal storage capacity to pure PCM. The as-prepared composites efficiently perform heat store and release with reasonable reliability. Moreover, the supercooling of PCM was strongly suppressed due to the large surface area of HPC. Molecular dynamics (MD) simulation confirms that the smaller pores enable a stronger force of the carbon skeleton on the PCM, which ensures effective anchoring of the PCM. Simultaneously, those larger pores provide enough space for storage of PCM, with a reduced negative effect on its crystallization. After the compounding, the phonon vibration matching between guest and host is strengthened, which is beneficial to the transfer of energy thus receives an enhanced thermal conductivity. Our research demonstrates the great potential of using hierarchical porous skeleton to immobilize phase change materials for practical thermal storage

The Catechol-O-Methyltransferase (COMT) val158met Polymorphism Affects Brain Responses to Repeated Painful Stimuli

Despite the explosion of interest in the genetic underpinnings of individual differences in pain sensitivity, conflicting findings have emerged for most of the identified "pain genes". Perhaps the prime example of this inconsistency is represented by catechol-O-methyltransferase (COMT), as its substantial association to pain sensitivity has been reported in various studies, but rejected in several others. In line with findings from behavioral studies, we hypothesized that the effect of COMT on pain processing would become apparent only when the pain system was adequately challenged (i.e., after repeated pain stimulation). In the present study, we used functional Magnetic Resonance Imaging (fMRI) to investigate the brain response to heat pain stimuli in 54 subjects genotyped for the common COMT val158met polymorphism (val/val = n 22, val/met = n 20, met/met = n 12). Met/met subjects exhibited stronger pain-related fMRI signals than val/val in several brain structures, including the periaqueductal gray matter, lingual gyrus, cerebellum, hippocampal formation and precuneus. These effects were observed only for high intensity pain stimuli after repeated administration. In spite of our relatively small sample size, our results suggest that COMT appears to affect pain processing. Our data demonstrate that the effect of COMT on pain processing can be detected in presence of 1) a sufficiently robust challenge to the pain system to detect a genotype effect, and/or 2) the recruitment of pain-dampening compensatory mechanisms by the putatively more pain sensitive met homozygotes. These findings may help explain the inconsistencies in reported findings of the impact of COMT in pain regulation.United States. National Institutes of Health (R01AT005280)United States. National Institutes of Health (R21AT00949)United States. National Institutes of Health (KO1AT003883)United States. National Institutes of Health (R21AT004497)National Center for Complementary and Alternative Medicine (U.S.) (PO1-AT002048)United States. National Institutes of Health (M01-RR-01066)United States. National Institutes of Health (UL1 RR025758-01)United States. National Institutes of Health (P41RR14075)United States. National Institutes of Health (DE-FG03-99ER62764)Swedish Society for Medical Researc

Bipolar disorder, brain-derived neurotrophic factor (BDNF) Val66Met polymorphism and brain morphology

10.1371/journal.pone.0038469PLoS ONE77

Characterizing the Blood Oxygen Level-Dependent Fluctuations in Musculoskeletal Tumours Using Functional Magnetic Resonance Imaging

This study characterized the blood oxygen level-dependent (BOLD) fluctuations in benign and malignant musculoskeletal tumours via power spectrum analyses in pre-established low-frequency bands. BOLD MRI and T1-weighted imaging (T1WI) were collected for 52 patients with musculoskeletal tumours. Three ROIs were drawn on the T1WI image in the tumours’ central regions, peripheral regions and neighbouring tissue. The power spectrum of the BOLD within each ROI was calculated and divided into the following four frequency bands: 0.01–0.027 Hz, 0.027–0.073 Hz, 0.073–0.198 Hz, and 0.198–0.25 Hz. ANOVA was conducted for each frequency band with the following two factors: the location of the region of interest (LoR, three levels: tumour “centre”, “peripheral” and “healthy tissue”) and tumour characteristic (TC, two levels: “malignant” and “benign”). There was a significant main effect of LoR in the frequencies of 0.073–0.198 Hz and 0.198–0.25 Hz. These data were further processed with post-hoc pair-wise comparisons. BOLD fluctuations at 0.073–0.198 Hz were stronger in the peripheral than central regions of the malignant tumours; however, no such difference was observed for the benign tumours. Our findings provide evidence that the BOLD signal fluctuates with spatial heterogeneity in malignant musculoskeletal tumours at the frequency band of 0.073–0.198 Hz

REST: A Toolkit for Resting-State Functional Magnetic Resonance Imaging Data Processing

Resting-state fMRI (RS-fMRI) has been drawing more and more attention in recent years. However, a publicly available, systematically integrated and easy-to-use tool for RS-fMRI data processing is still lacking. We developed a toolkit for the analysis of RS-fMRI data, namely the RESting-state fMRI data analysis Toolkit (REST). REST was developed in MATLAB with graphical user interface (GUI). After data preprocessing with SPM or AFNI, a few analytic methods can be performed in REST, including functional connectivity analysis based on linear correlation, regional homogeneity, amplitude of low frequency fluctuation (ALFF), and fractional ALFF. A few additional functions were implemented in REST, including a DICOM sorter, linear trend removal, bandpass filtering, time course extraction, regression of covariates, image calculator, statistical analysis, and slice viewer (for result visualization, multiple comparison correction, etc.). REST is an open-source package and is freely available at http://www.restfmri.net