Electroacupuncture modulates abnormal brain connectivity after ischemia reperfusion injury in rats: A graph theory-based approach

BACKGROUND

Electroacupuncture (EA) has been shown to facilitate brain plasticity-related functional recovery following ischemic stroke. The functional magnetic resonance imaging technique can be used to determine the range and mode of brain activation. After stroke, EA has been shown to alter brain connectivity, whereas EA's effect on brain network topology properties remains unclear. An evaluation of EA's effects on global and nodal topological properties in rats with ischemia reperfusion was conducted in this study.

METHODS AND RESULTS

There were three groups of adult male Sprague-Dawley rats: sham-operated group (sham group), middle cerebral artery occlusion/reperfusion (MCAO/R) group, and MCAO/R plus EA (MCAO/R + EA) group. The differences in global and nodal topological properties, including shortest path length, global efficiency, local efficiency, small-worldness index, betweenness centrality (BC), and degree centrality (DC) were estimated. Graphical network analyses revealed that, as compared with the sham group, the MCAO/R group demonstrated a decrease in BC value in the right ventral hippocampus and increased BC in the right substantia nigra, accompanied by increased DC in the left nucleus accumbens shell (AcbSh). The BC was increased in the right hippocampus ventral and decreased in the right substantia nigra after EA intervention, and MCAO/R + EA resulted in a decreased DC in left AcbSh compared to MCAO/R.

CONCLUSION

The results of this study provide a potential basis for EA to promote cognitive and motor function recovery after ischemic stroke.

Disrupted topological properties of structural brain networks present a glutamatergic neuropathophysiology in people with narcolepsy

STUDY OBJECTIVES

Growing evidences have documented various abnormalities of the white matter bundles in people with narcolepsy. We sought to evaluate topological properties of brain structural networks, and their association with symptoms and neuropathophysiological features in people with narcolepsy.

METHODS

Diffusion tensor imaging (DTI) was conducted for people with narcolepsy (n = 30) and matched healthy controls as well as symptoms assessment. Structural connectivity for each participant was generated to analyze global and regional topological properties and their correlations with narcoleptic features. Further human brain transcriptome was extracted and spatially registered for connectivity vulnerability. Genetic functional enrichment analysis was performed and further clarified using in vivo emission computed tomography data.

RESULTS

A wide and dramatic decrease in structural connectivities was observed in people with narcolepsy, with descending network degree and global efficiency. These metrics were not only correlated with sleep latency and awakening features, but also reflected alterations of sleep macrostructure in people with narcolepsy. Network-based statistics identified a small hyperenhanced subnetwork of cingulate gyrus that was closely related to rapid eye movement sleep behavior disorder (RBD) in narcolepsy. Further imaging genetics analysis suggested glutamatergic signatures were responsible for the preferential vulnerability of connectivity alterations in people with narcolepsy, while additional PET/SPECT data verified that structural alteration was significantly correlated with metabotropic glutamate receptor 5 (mGlutR5) and N-methyl-D-aspartate receptor (NMDA).

CONCLUSIONS

People with narcolepsy endured a remarkable decrease in the structural architecture, which was not only be closely related to narcolepsy symptoms but also glutamatergic signatures.

Topological properties of Xene tuned by perpendicular electric field and exchange field in the presence of Rashba spin-orbit coupling

Xene (X=Si, Ge, Sn) is a typical and promising two-dimensional topological insulator with many novel topological properties. Here, we investigate the topological properties of Xene tuned by a perpendicularly applied electric field, exchange field, and Rashba spin-orbit coupling (RSOC) using the tight-binding (TB) method. We show that in the presence of RSOC, the system can be converted from a quantum spin Hall (QSH) insulator into a conventional band insulator (BI) by a weak perpendicular electric field or into a quantum anomalous Hall (QAH) insulator by a weak exchange field. Additionally, a suitable combination of electric and exchange fields can give rise to a valley-polarized metallic (VPM) state. Furthermore, we explore the competition between the electric field and exchange field in tuning the topological states owing to the Rashba coupling effect. When the electric field is stronger than the exchange field, the system tends to be in a topologically trivial BI state; otherwise, it will be a QAH insulator. More intriguingly, for a fixed exchange field and RSOC, as the perpendicular electric field increase continuously from zero, the system undergoes multiphase (e.g. QSH-VPM-BI) transitions. This paves the way for designing multiphase transition devices through external single-field regulation.

Alterations of white matter tracts and topological properties of structural networks in hemifacial spasm

Hemifacial spasm (HFS) is characterized by involuntary and paroxysmal muscle contractions on the hemiface. It is generally believed that HFS is caused by neurovascular compression at the root exit zone of the facial nerve. In recent years, the structural alterations of brains with HFS have aroused growing concern. However, little attention has been directed towards the possible involvement of specific white matter (WM) tracts and the topological properties of structural networks in HFS. In the present study, diffusion magnetic resonance imaging tractography was utilized to construct structural networks and perform tractometric analysis. The diffusion tensor imaging scalar parameters along with the WM tracts, and the topological parameters of global networks and subnetworks, were assessed in 62 HFS patients and 57 demographically matched healthy controls (HCs). Moreover, we investigated the correlation of these parameters with disease-clinical-level (DCL) and disease-duration-time (DDT) of HFS patients. Compared with HCs, HFS patients had additional hub regions including the amygdala, ventromedial putamen, lateral occipital cortex, and rostral cuneus gyrus. Furthermore, HFS patients showed significant alternations with specific topological properties in some structural subnetworks, including the limbic, default mode, dorsal attention, somato-motor, and control networks, as well as diffusion properties in some WM tracts, including the superior longitudinal fasciculus, cingulum bundle, thalamo-frontal, and corpus callosum. These subnetworks and tracts were associated with the regulation of emotion, motor function, vision, and attention. Notably, we also found that the parameters with subnetworks and tracts exhibited correlations with DCL and DDT. In addition to corroborating previous findings in HFS, this study demonstrates the changed microstructures in specific locations along with the fiber tracts and changed topological properties in structural subnetworks.

Pressure-Induced Superconductivity in HgTe Single-Crystal Film

HgTe film is widely used for quantum Hall well studies and devices, as it has unique properties, like band gap inversion, carrier-type switch, and topological evolution depending on the film thickness modulation near the so-called critical thickness (63.5 Å), while its counterpart bulk materials do not hold these nontrivial properties at ambient pressure. Here, much richer transport properties emerging in bulk HgTe crystal through pressure-tuning are reported. Not only the above-mentioned abnormal properties can be realized in a 400 nm thick bulk HgTe single crystal, but superconductivity is also discovered in a series of high-pressure phases. Combining crystal structure, electrical transport, and Hall coefficient measurements, a p-n carrier type switching is observed in the first high-pressure cinnabar phase. Superconductivity emerges after the semiconductor-to-metal transition at 3.9 GPa and persists up to 54 GPa, crossing four high-pressure phases with an increased upper critical field. Density functional theory calculations confirm that a surface-dominated topologic band structure contributes these exotic properties under high pressure. This discovery presents broad and efficient tuning effects by pressure on the lattice structure and electronic modulations compared to the thickness-dependent critical properties in 2D and 3D topologic insulators and semimetals.

Systematic analysis of olfactory protein-protein interactions network of fruitfly, Drosophila melanogaster

Olfaction is one of the physiological traits of insect behavior. Insects have evolved a sophisticated olfactory system and use a combined coding strategy to process general odor. Drosophila melanogaster is a powerful model to reveal the molecular and cellular mechanisms of odor detection. Identifying new olfactory targets through complex interactions will contribute to a better understanding of the functions, interactions, and signaling pathways of olfactory proteins. However, the mechanism of D. melanogaster olfaction is still unclear, and more olfactory proteins are required to be discovered. In this study, we tried to explore essential proteins in the olfactory system of D. melanogaster and conduct protein-protein interactions (PPIs) analysis. We constructed the PPIs network of the olfactory system of D. melanogaster, consisting of 863 proteins and 18,959 interactions. Various methods were used to perform functional enrichment analysis, topological analysis and cluster analysis. Our results confirmed that Class B scavenger receptors (SR-Bs), glutathione S-transferases (GSTs), and UDP-glycosyltransferases (UGTs) play an essential role in olfaction of D. melanogaster. The proteins obtained in this study can be used for subsequent functional identification in D. melanogaster olfactory.

Age-related alterations of brain metabolic network based on [18F]FDG-PET of rats

Using animal models to study the underlying mechanisms of aging will create a critical foundation from which to develop new interventions for aging-related brain disorders. Aging-related reorganization of the brain network has been described for the human brain based on functional, metabolic and structural connectivity. However, alterations in the brain metabolic network of aging rats remain unknown. Here, we submitted young and aged rats to [18F]fluorodeoxyglucose with positron emission tomography (18F-FDG PET) and constructed brain metabolic networks. The topological properties were detected, and the network robustness against random failures and targeted attacks was analyzed for age-group comparison. Compared with young rats, aged rats showed reduced betweenness centrality (BC) in the superior colliculus and a decreased degree (D) in the parietal association cortex. With regard to network robustness, the brain metabolic networks of aged rats were more vulnerable to simulated damage, which showed significantly lower local efficiency and clustering coefficients than those of the young rats against targeted attacks and random failures. The findings support the idea that aged rats have similar aging-related changes in the brain metabolic network to the human brain and can therefore be used as a model for aging studies to provide targets for potential therapies that promote healthy aging.

Structure-Property Relationships of 2D Ga/In Chalcogenides

Two-dimensional MX (M = Ga, In; X = S, Se, Te) homo- and heterostructures are of interest in electronics and optoelectronics. Structural, electronic and optical properties of bulk and layered MX and GaX/InX heterostructures have been investigated comprehensively using density functional theory (DFT) calculations. Based on the quantum theory of atoms in molecules, topological analyses of bond degree (BD), bond length (BL) and bond angle (BA) have been detailed for interpreting interatomic interactions, hence the structure-property relationship. The X-X BD correlates linearly with the ratio of local potential and kinetic energy, and decreases as X goes from S to Te. For van der Waals (vdW) homo- and heterostructures of GaX and InX, a cubic relationship between microscopic interatomic interaction and macroscopic electromagnetic behavior has been established firstly relating to weighted absolute BD summation and static dielectric constant. A decisive role of vdW interaction in layer-dependent properties has been identified. The GaX/InX heterostructures have bandgaps in the range 0.23-1.49 eV, absorption coefficients over 10-5 cm-1 and maximum conversion efficiency over 27%. Under strain, discordant BD evolutions are responsible for the exclusively distributed electrons and holes in sublayers of GaX/InX. Meanwhile, the interlayer BA adjustment with lattice mismatch explains the constraint-free lattice of the vdW heterostructure.

Protein-protein interaction network analysis of insecticide resistance molecular mechanism in Drosophila melanogaster

The problem of resistance has not been solved fundamentally at present, because the development speed of new insecticides can not keep pace with the development speed of resistance, and the lack of understanding of molecular mechanism of resistance. Here we collected seed genes and their interacting proteins involved in insecticide resistance molecular mechanism in Drosophila melanogaster by literature mining and the String database. We identified a total of 528 proteins and 13514 protein-protein interactions. The protein interaction network was constructed by String and Pajek, and we analyzed the topological properties, such as degree centrality and eigenvector centrality. Proteasome complexes and drug metabolism-cytochrome P450 were an enrichment by Gene Ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. This is the first time to explore the insecticide resistance molecular mechanism of D. melanogaster by the methods and tools of network biology, it can provide the bioinformatic foundation for further understanding the mechanisms of insecticide resistance.

ce-Subpathway: Identification of ceRNA-mediated subpathways via joint power of ceRNAs and pathway topologies

Competing endogenous RNAs (ceRNAs) represent a novel mechanism of gene regulation that may mediate key subpathway regions and contribute to the altered activities of pathways. However, the classical methods used to identify pathways fail to specifically consider ceRNAs within the pathways and key regions impacted by them. We proposed a powerful strategy named ce-Subpathway for the identification of ceRNA-mediated functional subpathways. It provided an effective level of pathway analysis via integrating ceRNAs, differentially expressed (DE) genes and their key regions within the given pathways. We respectively analysed one pulmonary arterial hypertension (PAH) and one myocardial infarction (MI) data sets and demonstrated that ce-Subpathway could identify many subpathways whose corresponding entire pathways were ignored by those non-ceRNA-mediated pathway identification methods. And these pathways have been well reported to be associated with PAH/MI-related cardiovascular diseases. Further evidence showed reliability of ceRNA interactions and robustness/reproducibility of the ce-Subpathway strategy by several data sets of different cancers, including breast cancer, oesophageal cancer and colon cancer. Survival analysis was finally applied to illustrate the clinical application value of the ceRNA-mediated functional subpathways using another data sets of pancreatic cancer. Comprehensive analyses have shown the power of a joint ceRNAs/DE genes and subpathway strategy based on their topologies.

The Topological Properties of Stimuli Influence Fear Generalization and Extinction in Humans

Fear generalization is an etiologically significant indicator of anxiety disorders, and understanding how to inhibit it is important in their treatment. Prior studies have found that reducing fear generalization using a generalization stimulus (GS) is ineffective in removing a conditioned fear that incorporates local features, and that topological properties appear to play a comparatively more significant role in the processes of perception and categorization. Our study utilized a conditioned-fear generalization design to examine whether the topological properties of stimuli influence the generalization and return of fear. Fear was indexed using online expectancy ratings and skin conductance responses (SCRs). The study's 52 participants were divided into three groups: Group 1, conditioned danger cue (CS+) extinction; Group 2, extinction of one GS; Group 3, extinction of three GSs. We found that the three groups acquired conditioned fear at the same level. In the generalization and extinction phase, fear was transferred to the GS with the same topological properties as CS+, and gradual decreases in both shock expectancy and SCRs over non-reinforced extinction trials were observed. In the test phase, participants' online expectancy ratings indicated that fear did not return in Group 1, but did return in Groups 2 and 3. All three groups demonstrated successful GS fear extinction, but only Group 1 did not show a return of fear for CS+. Regarding SCRs results, none of the groups demonstrated a return of fear, suggesting that utilization of topological properties successfully reduced the return of conditioned fear. Our results indicate that, in clinical settings, using GS with topological equivalence to CS+ might offer a potential method with which to extinct conditioned fear.

Integration of network topological and connectivity properties for neuroimaging classification

Rapid advances in neuroimaging techniques have provided an efficient and noninvasive way for exploring the structural and functional connectivity of the human brain. Quantitative measurement of abnormality of brain connectivity in patients with neurodegenerative diseases, such as mild cognitive impairment (MCI) and Alzheimer's disease (AD), have also been widely reported, especially at a group level. Recently, machine learning techniques have been applied to the study of AD and MCI, i.e., to identify the individuals with AD/MCI from the healthy controls (HCs). However, most existing methods focus on using only a single property of a connectivity network, although multiple network properties, such as local connectivity and global topological properties, can potentially be used. In this paper, by employing multikernel based approach, we propose a novel connectivity based framework to integrate multiple properties of connectivity network for improving the classification performance. Specifically, two different types of kernels (i.e., vector-based kernel and graph kernel) are used to quantify two different yet complementary properties of the network, i.e., local connectivity and global topological properties. Then, multikernel learning (MKL) technique is adopted to fuse these heterogeneous kernels for neuroimaging classification. We test the performance of our proposed method on two different data sets. First, we test it on the functional connectivity networks of 12 MCI and 25 HC subjects. The results show that our method achieves significant performance improvement over those using only one type of network property. Specifically, our method achieves a classification accuracy of 91.9%, which is 10.8% better than those by single network-property-based methods. Then, we test our method for gender classification on a large set of functional connectivity networks with 133 infants scanned at birth, 1 year, and 2 years, also demonstrating very promising results.