Excess mesangial extracellular matrix (ECM) and mesangial cell proliferation is the major pathologic feature of diabetic nephropathy (DN). Fenofibrate, a PPARα agonist, has been shown to attenuate extracellular matrix formation in diabetic nephropathy. However, the mechanisms underlying this effect remain to be elucidated. In this study, the effect of fenofibrate on high-glucose induced cell proliferation and extracellular matrix exertion and its mechanisms were investigated in cultured rat mesangial cells by the methylthiazoletetrazolium (MTT) assay, flow cytometry and western blot. The results showed that treatment of mesangial cells (MCs) with fenofibrate repressed high-glucose induced up-regulation of extracellular matrix Collagen-IV, and inhibited entry of cell cycle into the S phase. This G1 arrest and ECM inhibition was caused by the reduction of phosphorylation and activation of extracellular signal-regulated kinase 1/2 (ERK1/2) and AKT. On the contrary, PPARα siRNA accelerated high glucose-induced cell cycle progression by ERK1/2 and AKT activation. Taken together, fenofibrate ameliorated glucose-induced mesangial cell proliferation and matrix production via its inhibition of PI3K/AKT and ERK1/2 signaling pathways. Such mechanisms may contribute to the favorable effects of treatment using fenofibrate in diabetic nephropathy.
Ischemia-reperfusion (I/R) injury is associated with intestinal microbial dysbiosis. The “gut-liver axis” closely links gut function and liver function in health and disease. Ischemic preconditioning (IPC) has been proven to reduce I/R injury in the surgery. This study aims to explore the effect of IPC on intestinal microbiota and to analyze characteristics of microbial structure shift following liver transplantation (LT).
The LT animal models of liver and gut IPC were established. Hepatic graft function was assessed by histology and serum ALT/AST. Intestinal barrier function was evaluated by mucosal ultrastructure, serum endotoxin, bacterial translocation, fecal sIgA content and serum TNF-α. Intestinal bacterial populations were determined by quantitative PCR. Microbial composition was characterized by DGGE and specific bacterial species were determined by sequence analysis.
Liver IPC improved hepatic graft function expressed as ameliorated graft structure and reduced ALT/AST levels. After administration of liver IPC, intestinal mucosal ultrastructure improved, serum endotoxin and bacterial translocation mildly decreased, fecal sIgA content increased, and serum TNF-α decreased. Moreover, liver IPC promoted microbial restorations mainly through restoring Bifidobacterium spp., Clostridium clusters XI and Clostridium cluster XIVab on bacterial genus level. DGGE profiles indicated that liver IPC increased microbial diversity and species richness, and cluster analysis demonstrated that microbial structures were similar and clustered together between the NC group and Liver-IPC group. Furthermore, the phylogenetic tree of band sequences showed key bacteria corresponding to 10 key band classes of microbial structure shift induced by liver IPC, most of which were assigned to Bacteroidetes phylum.
Liver IPC cannot only improve hepatic graft function and intestinal barrier function, but also promote restorations of intestinal microbiota following LT, which may further benefit hepatic graft by positive feedback of the “gut-liver axis”.
The crystal structures of both native manganese SOD2 and iron-substituted SOD2 from S. cerevisiae were solved. The surface-potential properties showed a similar pattern to those of Cu/Zn-SODs.
The manganese-specific superoxide dismutase SOD2 from the yeast Saccharomyces cerevisiae is a protein that resides in the mitochondrion and protects it against attack by superoxide radicals. However, a high iron concentration in the mitochondria results in iron misincorporation at the active site, with subsequent inactivation of SOD2. Here, the crystal structures of SOD2 bound with the native metal manganese and with the ‘wrong’ metal iron are presented at 2.05 and 1.79 Å resolution, respectively. Structural comparison of the two structures shows no significant conformational alteration in the overall structure or in the active site upon binding the non-native metal iron. Moreover, residues Asp163 and Lys80 are proposed to potentially be responsible for the metal specificity of the Mn-specific SOD. Additionally, the surface-potential distribution of SOD2 revealed a conserved positively charged electrostatic zone in the proximity of the active site that probably functions in the same way as in Cu/Zn-SODs by facilitating the diffusion of the superoxide anion to the metal ion.
superoxide dismutases; Saccharomyces cerevisiae; SOD2
Exposure to early life trauma (ELT) is known to have a profound impact on mental development, leading to a higher risk for depression and anxiety. Our aim was to use multiple structural imaging methods to systematically investigate how traumatic stressors early in life impact the emotional brain circuits, typically found impaired with clinical diagnosis of depression and anxiety, across the lifespan in an otherwise healthy cohort. MRI data and self-reported histories of ELT from 352 healthy individuals screened for no psychiatric disorders were analyzed in this study. The volume and cortical thickness of the limbic and cingulate regions were assessed for all participants. A large subset of the cohort also had diffusion tensor imaging data, which was used to quantify white matter structural integrity of these regions. We found a significantly smaller amygdala volume and cortical thickness in the rostral anterior cingulate cortex associated with higher ELT exposure only for the adolescence group. White matter integrity of these regions was not affected. These findings demonstrate that exposure to early life trauma is associated with alterations in the gray matter of cingulate-limbic regions during adolescence in an otherwise healthy sample. These findings are interesting in the context that the affected regions are central neuroanatomical components in the psychopathology of depression, and adolescence is a peak period for risk and onset of the disorder.
Individuals differ in their cognitive resilience. Less resilient people demonstrate a greater tendency to vigilance decrements within sustained attention tasks. We hypothesized that a period of sustained attention is followed by prolonged changes in the organization of “resting state” brain networks and that individual differences in cognitive resilience are related to differences in post-task network reorganization. We compared the topological and spatial properties of brain networks as derived from functional MRI data (N = 20) recorded for 6 mins before and 12 mins after the performance of an attentional task. Furthermore we analysed changes in brain topology during task performance and during the switches between rest and task conditions. The cognitive resilience of each individual was quantified as the rate of increase in response latencies over the 32-minute time course of the attentional paradigm. On average, functional networks measured immediately post-task demonstrated significant and prolonged changes in network organization compared to pre-task networks with higher connectivity strength, more clustering, less efficiency, and shorter distance connections. Individual differences in cognitive resilience were significantly correlated with differences in the degree of recovery of some network parameters. Changes in network measures were still present in less resilient individuals in the second half of the post-task period (i.e. 6–12 mins after task completion), while resilient individuals already demonstrated significant reductions of functional connectivity and clustering towards pre-task levels. During task performance brain topology became more integrated with less clustering and higher global efficiency, but linearly decreased with ongoing time-on-task. We conclude that sustained attentional task performance has prolonged, “hang-over” effects on the organization of post-task resting-state brain networks; and that more cognitively resilient individuals demonstrate faster rates of network recovery following a period of attentional effort.
Recent research has demonstrated the feasibility of combining functional near-infrared spectroscopy (fNIRS) and graph theory approaches to explore the topological attributes of human brain networks. However, the test-retest (TRT) reliability of the application of graph metrics to these networks remains to be elucidated. Here, we used resting-state fNIRS and a graph-theoretical approach to systematically address TRT reliability as it applies to various features of human brain networks, including functional connectivity, global network metrics and regional nodal centrality metrics. Eighteen subjects participated in two resting-state fNIRS scan sessions held ∼20 min apart. Functional brain networks were constructed for each subject by computing temporal correlations on three types of hemoglobin concentration information (HbO, HbR, and HbT). This was followed by a graph-theoretical analysis, and then an intraclass correlation coefficient (ICC) was further applied to quantify the TRT reliability of each network metric. We observed that a large proportion of resting-state functional connections (∼90%) exhibited good reliability (0.6< ICC <0.74). For global and nodal measures, reliability was generally threshold-sensitive and varied among both network metrics and hemoglobin concentration signals. Specifically, the majority of global metrics exhibited fair to excellent reliability, with notably higher ICC values for the clustering coefficient (HbO: 0.76; HbR: 0.78; HbT: 0.53) and global efficiency (HbO: 0.76; HbR: 0.70; HbT: 0.78). Similarly, both nodal degree and efficiency measures also showed fair to excellent reliability across nodes (degree: 0.52∼0.84; efficiency: 0.50∼0.84); reliability was concordant across HbO, HbR and HbT and was significantly higher than that of nodal betweenness (0.28∼0.68). Together, our results suggest that most graph-theoretical network metrics derived from fNIRS are TRT reliable and can be used effectively for brain network research. This study also provides important guidance on the choice of network metrics of interest for future applied research in developmental and clinical neuroscience.
The preclinical Alzheimer's disease (AD) - amnestic mild cognitive impairment (MCI) - is manifested by phenotypes classified into exclusively memory (single-domain) MCI (sMCI) and multiple-domain MCI (mMCI). We suggest that typical MCI-to-AD progression occurs through the sMCI-to-mMCI sequence as a result of the extension of initial pathological processes. To support this hypothesis, we assess myelin content with a Magnetization Transfer Ratio (MTR) in 21 sMCI and 21 mMCI patients and in 42 age-, sex-, and education-matched controls. A conjunction analysis revealed MTR reduction shared by sMCI and mMCI groups in the medial temporal lobe and posterior structures including white matter (WM: splenium, posterior corona radiata) and gray matter (GM: hippocampus; parahippocampal and lingual gyri). A disjunction analysis showed the spread of demyelination to prefrontal WM and insula GM in executive mMCI. Our findings suggest that demyelination starts in the structures affected by neurofibrillary pathology; its presence correlates with the clinical picture and indicates the method of MCI-to-AD progression. In vivo staging of preclinical AD can be developed in terms of WM/GM demyelination.
Functional connectivity between brain regions during swallowing tasks is still not well understood. Understanding these complex interactions is of great interest from both a scientific and a clinical perspective. In this study, functional magnetic resonance imaging (fMRI) was utilized to study brain functional networks during voluntary saliva swallowing in twenty-two adult healthy subjects (all females, years of age). To construct these functional connections, we computed mean partial correlation matrices over ninety brain regions for each participant. Two regions were determined to be functionally connected if their correlation was above a certain threshold. These correlation matrices were then analyzed using graph-theoretical approaches. In particular, we considered several network measures for the whole brain and for swallowing-related brain regions. The results have shown that significant pairwise functional connections were, mostly, either local and intra-hemispheric or symmetrically inter-hemispheric. Furthermore, we showed that all human brain functional network, although varying in some degree, had typical small-world properties as compared to regular networks and random networks. These properties allow information transfer within the network at a relatively high efficiency. Swallowing-related brain regions also had higher values for some of the network measures in comparison to when these measures were calculated for the whole brain. The current results warrant further investigation of graph-theoretical approaches as a potential tool for understanding the neural basis of dysphagia.
Safe and effective lipid nanoemulsion (LNE) formulations for the antitumor delivery of doxorubicin is designed.
LNEs composed of medium-chain triglyceride, soybean oil, lecithin, and doxorubicin are prepared by a solvent-diffusion method in an aqueous system. The effects of lipid material composition and polyethylene glycol (PEG)ylation on the size, drug encapsulation efficiency, and stability of LNEs are investigated. Based on in-vitro cytotoxicity and cellular uptake tests of A549 (human lung carcinoma) cells, in-vivo biodistribution, antitumor activity, and cardiac toxicity are further examined using nude mouse bearing A549 tumor.
The LNE size decreases from 126.4 ± 8.7 nm to 44.5 ± 9.3 nm with increased weight ratio of medium-chain triglyceride to soybean oil from 1:4 to 3:2, whereas the encapsulation efficiency of doxorubicin is slightly reduced from 79.2% ± 2.1% to 71.2% ± 2.9%. The PEGylation of LNE by 1,2-distearoyl-sn-glycero-3-phosphoethanolamine-N-[carboxy(PEG)2000] (DSPE-PEG 2000) does not significantly change the size and drug encapsulation efficiency. Three-month storage at room temperature and lyophilization process does not affect the drug encapsulation efficiency, whereas the size slightly increases to almost 100 nm. The in-vitro drug-release profiles of LNEs suggest that the present formulation can prolong drug release for 48 hours. LNEs can be internalized into tumor cells in vitro and efficiently accumulate in tumor tissues in vivo by passive targeting. Analysis results of in-vitro and in-vivo antitumor activities reveal that doxorubicin-loaded LNE exerts a therapeutic effect similar to that of the commercial Adriamycin. Moreover, the toxicity of doxorubicin, particularly its cardiac toxicity, is reduced.
The present LNE formulation of doxorubicin can effectively suppress tumor growth and improve the safety of Adriamycin.
PEGylation; stability; antitumor activity
Lateralized brain regions subserve functions such as language and visuospatial processing. It has been conjectured that individuals may be left-brain dominant or right-brain dominant based on personality and cognitive style, but neuroimaging data has not provided clear evidence whether such phenotypic differences in the strength of left-dominant or right-dominant networks exist. We evaluated whether strongly lateralized connections covaried within the same individuals. Data were analyzed from publicly available resting state scans for 1011 individuals between the ages of 7 and 29. For each subject, functional lateralization was measured for each pair of 7266 regions covering the gray matter at 5-mm resolution as a difference in correlation before and after inverting images across the midsagittal plane. The difference in gray matter density between homotopic coordinates was used as a regressor to reduce the effect of structural asymmetries on functional lateralization. Nine left- and 11 right-lateralized hubs were identified as peaks in the degree map from the graph of significantly lateralized connections. The left-lateralized hubs included regions from the default mode network (medial prefrontal cortex, posterior cingulate cortex, and temporoparietal junction) and language regions (e.g., Broca Area and Wernicke Area), whereas the right-lateralized hubs included regions from the attention control network (e.g., lateral intraparietal sulcus, anterior insula, area MT, and frontal eye fields). Left- and right-lateralized hubs formed two separable networks of mutually lateralized regions. Connections involving only left- or only right-lateralized hubs showed positive correlation across subjects, but only for connections sharing a node. Lateralization of brain connections appears to be a local rather than global property of brain networks, and our data are not consistent with a whole-brain phenotype of greater “left-brained” or greater “right-brained” network strength across individuals. Small increases in lateralization with age were seen, but no differences in gender were observed.
Diffusion-weighted MRI (DW-MRI), the only non-invasive technique for probing human brain white matter structures in vivo, has been widely used in both fundamental studies and clinical applications. Many studies have utilized diffusion tensor imaging (DTI) and tractography approaches to explore the topological properties of human brain anatomical networks by using the single tensor model, the basic model to quantify DTI indices and tractography. However, the conventional DTI technique does not take into account contamination by the cerebrospinal fluid (CSF), which has been known to affect the estimated DTI measures and tractography in the single tensor model. Previous studies have shown that the Fluid-Attenuated Inversion Recovery (FLAIR) technique can suppress the contribution of the CSF to the DW-MRI signal. We acquired DTI datasets from twenty-two subjects using both FLAIR-DTI and conventional DTI (non-FLAIR-DTI) techniques, constructed brain anatomical networks using deterministic tractography, and compared the topological properties of the anatomical networks derived from the two types of DTI techniques. Although the brain anatomical networks derived from both types of DTI datasets showed small-world properties, we found that the brain anatomical networks derived from the FLAIR-DTI showed significantly increased global and local network efficiency compared with those derived from the conventional DTI. The increases in the network regional topological properties derived from the FLAIR-DTI technique were observed in CSF-filled regions, including the postcentral gyrus, periventricular regions, inferior frontal and temporal gyri, and regions in the visual cortex. Because brain anatomical networks derived from conventional DTI datasets with tractography have been widely used in many studies, our findings may have important implications for studying human brain anatomical networks derived from DW-MRI data and tractography.
The objective of this research was to design an effective gene delivery system composed of cationic solid lipid nanoparticles (SLNs), protamine, and Deoxyribonucleic acid DNA.
Cationic SLNs were prepared using an aqueous solvent diffusion method with octadecylamine as the cationic lipid material. First, protamine was combined with DNA to form binary protamine/DNA nanoparticles, and the ternary nanoparticle gene delivery system was then obtained by combining binary protamine/DNA nanoparticles with cationic SLNs. The size, zeta potential, and ability of the binary and ternary nanoparticles to compact and protect DNA were characterized. The effect of octadecylamine content in SLNs and the SLNS/DNA ratios on transfection efficiency, cellular uptake and cytotoxicity of the ternary nanoparticles were also assessed using HEK293 cells.
When the weight ratio of protamine to DNA reached 1.5:1, the plasmid DNA could be effectively compacted and protected. The average hydrodynamic diameter of the ternary nanoparticles when combined with protamine increased from 188.50 ± 0.26 nm to 259.33 ± 3.44 nm, and the zeta potential increased from 25.50 ± 3.30 mV to 33.40 ± 2.80 mV when the weight ratio of SLNs to DNA increased from 16/3 to 80/3. The ternary nanoparticles showed high gene transfection efficiency compared with Lipofectamine™ 2000/DNA nanoparticles. Several factors that might affect gene transfection efficiency, such as content and composition of SLNs, post-transfection time, and serum were examined. The ternary nanoparticles composed of SLNs with 15 wt% octadecylamine (50/3 weight ratio of SLNs to DNA) showed the best transfection efficiency (26.13% ± 5.22%) in the presence of serum. It was also found that cellular uptake of the ternary nanoparticles was better than that of the SLN/DNA and binary protamine/DNA nanoparticle systems, and DNA could be transported to the nucleus.
SLNs enhanced entry of binary protamine/DNA nanoparticles into the cell, and protamine protected DNA from enzyme degradation and transported DNA into the nucleus. Compared with Lipofectamine 2000/DNA nanoparticles, these cationic ternary nanoparticles showed relatively durable and stable gene transfection in the presence of serum.
solid lipid nanoparticles; protamine; plasmid DNA; gene transfection; ternary nanoparticles
The neurobiological basis of inattentiveness, a core feature of attention-deficit/hyperactivity disorder (ADHD), is not yet well understood. Structural abnormalities in thalamus, especially the pulvinar nuclei, have recently been reported in ADHD. Pulvinar nuclei maintain reciprocal connections with cortical/subcortical areas, and play a central coordinating role during visual attention processing. The objective of this study was to test the hypothesis that children and young adolescents with ADHD would show atypical pulvinar–cortical functional pathways during sustained attention performance, and that these functional abnormalities would be associated with the inattentive symptoms of the disorder.
Visual attention task-based functional magnetic resonance imaging (fMRI) data from 22 children and young adolescents with ADHD and 22 demographically matched, normal control subjects were analyzed. Cortical activation maps and temporal correlations of activity patterns between pulvinar nuclei and the remainder of brain were constructed for each participant. Correlations between activation magnitude of pulvinar and diagnostic measures were calculated in subjects with ADHD.
Compared to controls, subjects with ADHD showed significantly reduced pulvinar activations bilaterally, significantly decreased functional connectivity between bilateral pulvinar and right prefrontal regions, and significantly increased connectivity between the right pulvinar and bilateral occipital regions. In addition, the activation magnitude in the left pulvinar was negatively correlated with the DSM-IV inattentive index in ADHD group.
Allied with previous evidence of structural abnormalities in pulvinar, the current data suggest that inappropriate development of pulvinar may lead to disrupted functional circuits for visual attention processing, and that these disruptions contribute significantly to the pathophysiological mechanisms of the inattentiveness symptoms in ADHD.
ADHD; functional MRI; pulvinar; thalamo-cortical connectivity; attention
A Pichia pastoris (P. pastoris) cell surface display system of Bombyx mori acetylcholinesterase (BmAChE) was constructed and its bioactivity was studied. The modified Bombyx mori acetylcholinesterase gene (bmace) was fused with the anchor protein (AGα1) from Saccharomyces cerevisiae and transformed into P. pastoris strain GS115. The recombinant strain harboring the fusion gene bmace-AGα1 was induced to display BmAChE on the P. pastoris cell surface. Fluorescence microscopy and flow cytometry assays revealed that the BmAChE was successfully displayed on the cell surface of P. pastoris GS115. The enzyme activity of the displayed BmAChE was detected by the Ellman method at 787.7 U/g (wet cell weight). In addition, bioactivity of the displayed BmAChE was verified by inhibition tests conducted with eserine, and with carbamate and organophosphorus pesticides. The displayed BmAChE had an IC50 of 4.17×10−8 M and was highly sensitive to eserine and five carbamate pesticides, as well as seven organophosphorus pesticides. Results suggest that the displayed BmAChE had good bioactivity.
It is not clear whether specific brain areas act as hubs in the eyes-closed (EC) resting state, which is an unconstrained state free from any passive or active tasks. Here, we used electrophysiological magnetoencephalography (MEG) signals to study functional cortical hubs in 88 participants. We identified several multispectral cortical hubs. Although cortical hubs vary slightly with different applied measures and frequency bands, the most consistent hubs were observed in the medial and posterior cingulate cortex, the left dorsolateral superior frontal cortex, and the left pole of the middle temporal cortex. Hubs were characterized as connector nodes integrating EC resting state functional networks. Hubs in the gamma band were more likely to include midline structures. Our results confirm the existence of multispectral cortical cores in EC resting state functional networks based on MEG and imply the existence of optimized functional networks in the resting brain.
Mounting evidence has indicated that the cardiovascular protective effects of dietary alpha-linolenic acid (ALA), but whether ALA exerts an endothelial protective effect against high glucose injury and the underlying mechanisms remain largely unknown. Streptozocin-induced diabetic rats were randomized treated orally for 4 weeks with vehicle (0.01% alcohol) or ALA (500 µg/kg per day by gavage). Human umbilical vein endothelial cells (HUVECs) were exposed to high glucose (28 mmol/L) stimulation for 48 hours. ALA significantly improved concentration-dependent vasorelaxation to ACh in diabetic aortic segments and inhibited endothelial inflammation as evidenced by decreased soluble P-selectin and intercellular adhesion molecule-1 (ICAM-1) in diabetic rats. Furthermore, both P-selectin and ICAM-1 expression were increased significantly in high glucose-induced HUVECs, resulting in enhanced neutrophils adhesion to HUVECs compared with normal glucose group. Treatment with ALA (50 µmol/L) increased Akt phosphorylation, attenuated P-selectin and ICAM-1 expressions and thus inhibited neutrophils adhesion in HUVECs exposed to high glucose, all of which was blocked by the PI3K inhibitors LY294002 and wortmannin. These data indicates that ALA inhibits endothelial inflammation and improved endothelial function in STZ-induced diabetic rats. The anti-adhesive effect of ALA against high glucose injury may partially be mediated by the PI3K/Akt pathway.
The human brain is a complex system whose topological organization can be represented using connectomics. Recent studies have shown that human connectomes can be constructed using various neuroimaging technologies and further characterized using sophisticated analytic strategies, such as graph theory. These methods reveal the intriguing topological architectures of human brain networks in healthy populations and explore the changes throughout normal development and aging and under various pathological conditions. However, given the huge complexity of this methodology, toolboxes for graph-based network visualization are still lacking. Here, using MATLAB with a graphical user interface (GUI), we developed a graph-theoretical network visualization toolbox, called BrainNet Viewer, to illustrate human connectomes as ball-and-stick models. Within this toolbox, several combinations of defined files with connectome information can be loaded to display different combinations of brain surface, nodes and edges. In addition, display properties, such as the color and size of network elements or the layout of the figure, can be adjusted within a comprehensive but easy-to-use settings panel. Moreover, BrainNet Viewer draws the brain surface, nodes and edges in sequence and displays brain networks in multiple views, as required by the user. The figure can be manipulated with certain interaction functions to display more detailed information. Furthermore, the figures can be exported as commonly used image file formats or demonstration video for further use. BrainNet Viewer helps researchers to visualize brain networks in an easy, flexible and quick manner, and this software is freely available on the NITRC website (www.nitrc.org/projects/bnv/).
A near-infrared (NIR) hyperspectral imaging system was developed in this study. NIR hyperspectral imaging combined with multivariate data analysis was applied to identify rice seed cultivars. Spectral data was exacted from hyperspectral images. Along with Partial Least Squares Discriminant Analysis (PLS-DA), Soft Independent Modeling of Class Analogy (SIMCA), K-Nearest Neighbor Algorithm (KNN) and Support Vector Machine (SVM), a novel machine learning algorithm called Random Forest (RF) was applied in this study. Spectra from 1,039 nm to 1,612 nm were used as full spectra to build classification models. PLS-DA and KNN models obtained over 80% classification accuracy, and SIMCA, SVM and RF models obtained 100% classification accuracy in both the calibration and prediction set. Twelve optimal wavelengths were selected by weighted regression coefficients of the PLS-DA model. Based on optimal wavelengths, PLS-DA, KNN, SVM and RF models were built. All optimal wavelengths-based models (except PLS-DA) produced classification rates over 80%. The performances of full spectra-based models were better than optimal wavelengths-based models. The overall results indicated that hyperspectral imaging could be used for rice seed cultivar identification, and RF is an effective classification technique.
rice seed cultivar; hyperspectral imaging; random forest (RF); weighted regression coefficients (BW)
Artistic training is a complex learning that requires the meticulous orchestration of sophisticated polysensory, motor, cognitive, and emotional elements of mental capacity to harvest an aesthetic creation. In this study, we investigated the architecture of the resting-state functional connectivity networks from professional painters, dancers and pianists. Using a graph-based network analysis, we focused on the art-related changes of modular organization and functional hubs in the resting-state functional connectivity network. We report that the brain architecture of artists consists of a hierarchical modular organization where art-unique and artistic form-specific brain states collectively mirror the mind states of virtuosos. We show that even in the resting state, this type of extraordinary and long-lasting training can macroscopically imprint a neural network system of spontaneous activity in which the related brain regions become functionally and topologically modularized in both domain-general and domain-specific manners. The attuned modularity reflects a resilient plasticity nurtured by long-term experience.
Recently, a combination of non-invasive neuroimaging techniques and graph theoretical approaches has provided a unique opportunity for understanding the patterns of the structural and functional connectivity of the human brain (referred to as the human brain connectome). Currently, there is a very large amount of brain imaging data that have been collected, and there are very high requirements for the computational capabilities that are used in high-resolution connectome research. In this paper, we propose a hybrid CPU-GPU framework to accelerate the computation of the human brain connectome. We applied this framework to a publicly available resting-state functional MRI dataset from 197 participants. For each subject, we first computed Pearson’s Correlation coefficient between any pairs of the time series of gray-matter voxels, and then we constructed unweighted undirected brain networks with 58 k nodes and a sparsity range from 0.02% to 0.17%. Next, graphic properties of the functional brain networks were quantified, analyzed and compared with those of 15 corresponding random networks. With our proposed accelerating framework, the above process for each network cost 80∼150 minutes, depending on the network sparsity. Further analyses revealed that high-resolution functional brain networks have efficient small-world properties, significant modular structure, a power law degree distribution and highly connected nodes in the medial frontal and parietal cortical regions. These results are largely compatible with previous human brain network studies. Taken together, our proposed framework can substantially enhance the applicability and efficacy of high-resolution (voxel-based) brain network analysis, and have the potential to accelerate the mapping of the human brain connectome in normal and disease states.
The logopenic variant of primary progressive aphasia is an atypical clinical variant of Alzheimer’s disease which is typically characterized by left temporoparietal atrophy on magnetic resonance imaging and hypometabolism on F-18 fluorodeoxyglucose positron emission tomography. We aimed to characterize and compare patterns of atrophy and hypometabolism in logopenic primary progressive aphasia, and determine which brain regions and imaging modality best differentiates logopenic primary progressive aphasia from typical dementia of the Alzheimer’s type.
A total of 27 logopenic primary progressive aphasia subjects underwent fluorodeoxyglucose positron emission tomography and volumetric magnetic resonance imaging. These subjects were matched to 27 controls and 27 subjects with dementia of the Alzheimer’s type. Patterns of atrophy and hypometabolism were assessed at the voxel and region-level using Statistical Parametric Mapping. Penalized logistic regression analysis was used to determine what combinations of regions best discriminate between groups.
Atrophy and hypometabolism was observed in lateral temporoparietal and medial parietal lobes, left greater than right, and left frontal lobe in the logopenic group. The logopenic group showed greater left inferior, middle and superior lateral temporal atrophy (inferior p = 0.02; middle p = 0.007, superior p = 0.002) and hypometabolism (inferior p = 0.006, middle p = 0.002, superior p = 0.001), and less right medial temporal atrophy (p = 0.02) and hypometabolism (p<0.001), and right posterior cingulate hypometabolism (p<0.001) than dementia of the Alzheimer’s type. An age-adjusted penalized logistic model incorporating atrophy and hypometabolism achieved excellent discrimination (area under the receiver operator characteristic curve = 0.89) between logopenic and dementia of the Alzheimer’s type subjects, with optimal discrimination achieved using right medial temporal and posterior cingulate hypometabolism, left inferior, middle and superior temporal hypometabolism, and left superior temporal volume.
Patterns of atrophy and hypometabolism both differ between logopenic primary progressive aphasia and dementia of the Alzheimer’s type and both modalities provide excellent discrimination between groups.
To investigate the efficacy of leflunomide in experimental autoimmune uveitis (EAU) in rats.
Lewis rats were immunized with interphotoreceptor retinoid-binding peptide (IRBP) in order to generate EAU. Rats received three dose of leflunomide through intragastric administration (prevention or treatment protocols) after immunization at three separate doses (3 mg/kg/d; 6 mg/kg/d; 12 mg/kg/d). Cyclosporin A was administered as a positive) control. Rats were euthanized during peak disease activity (day 14 or 15). Treatment effectiveness was evaluated in vivo using clinical EAU scoring (d14) and histopathological evaluation of enucleated eyes after experimental termination. The expression levels of inflammatory cytokines in the serum were quantified by ELISA. Eyeball of rats were harvested and mRNA expression of interleukin 17 (IL17) and IFN-γ were quantified through RT-PCR. Intracellular expression of interleukin (IL)-17 in the activated CD4(+) T cells was assessed by flow cytometry. The effects of leflunomide inhibition on immune responses in rats were investigated in isolated lymphocytes.
Histopathological and clinical data revealed severe intraocular inflammation in the immunized rat. Inflammation reached its peak on day 14 in this EAU model. Treatment with leflunomide significantly prevented and treated EAU-induced ocular inflammation and decreased clinical and pathological scores compared to vehicle-treated eyes. Gene expression of IL17 and IFN-γwas markedly reduced in leflunomide-treated eyes. Leflunomide significantly decreased the serum levels of IL17 and IFN-γ. The study of IL17+ T cells in peripheral blood and spleen by flow cytometry showed a decreased number of Th17 cell in rats of leflunomide prevented group. Lymphocytes from animals treated with leflunomide had decreased antigen-specific proliferation in vitro compared with lymphocytes from untreated animals.
Oral administration of leflunomide effectively suppressed IRBP-induced uveitis in rats. These results suggest that leflunomide may be potentially clinical application in uveitis.
Longitudinal brain image analysis is critical for revealing subtle but complex structural and functional changes of brain during aging or in neurodevelopmental disease. However, even with the rapid increase of clinical research and trials, a software toolbox dedicated for longitudinal image analysis is still lacking publicly. To cater for this increasing need, we have developed a dedicated 4D Adult Brain Extraction and Analysis Toolbox (aBEAT) to provide robust and accurate analysis of the longitudinal adult brain MR images. Specially, a group of image processing tools were integrated into aBEAT, including 4D brain extraction, 4D tissue segmentation, and 4D brain labeling. First, a 4D deformable-surface-based brain extraction algorithm, which can deform serial brain surfaces simultaneously under temporal smoothness constraint, was developed for consistent brain extraction. Second, a level-sets-based 4D tissue segmentation algorithm that incorporates local intensity distribution, spatial cortical-thickness constraint, and temporal cortical-thickness consistency was also included in aBEAT for consistent brain tissue segmentation. Third, a longitudinal groupwise image registration framework was further integrated into aBEAT for consistent ROI labeling by simultaneously warping a pre-labeled brain atlas to the longitudinal brain images. The performance of aBEAT has been extensively evaluated on a large number of longitudinal MR T1 images which include normal and dementia subjects, achieving very promising results. A Linux-based standalone package of aBEAT is now freely available at http://www.nitrc.org/projects/abeat.