Microglial forkhead box O3a deficiency attenuates LPS-induced neuro-inflammation and depressive-like behaviour through regulating the expression of peroxisome proliferator-activated receptor-γ.

BACKGROUND AND PURPOSE: Depression is closely linked with microglial activation and neuro-inflammation. Peroxisome proliferator-activated receptor-γ (PPAR-γ) plays an important role in M2 activation of microglia. Forkhead box (FOX) O3a has been implicated in the regulation of mood-relevant behaviour. However, little is known about the inflammatory mechanisms of in the microglia of the brain. Here, we have investigated the role of microglial FOXO3a/PPAR-γ in the development of depression. EXPERIMENTAL APPROACH: The effect of FOXO3a on microglia inflammation was analysed in vitro and in lipopolysaccharide (LPS)-induced depression-like behaviours in vivo. ChIP-seq and Dual-luciferase reporter assays were used to confirm the interaction between FOXO3a and PPAR-γ. Behavioural changes were measured, while inflammatory cytokines, microglial phenotype and morphological properties were determined by ELISA, qRT-PCR, western blotting and immunostaining. KEY RESULTS: Overexpression of FOXO3a significantly attenuated expression of PPAR-γ and enhanced the microglial polarization towards the M1 phenotype, while knockdown of FOXO3a had the opposite effect. FOXO3a binds to the promoters of PPAR-γ and decreases its transcription activity. Importantly, deacetylation and activation of FOXO3a regulate LPS-induced neuro-inflammation by inhibiting the expression of PPAR-γ in microglia cells, supporting the antidepressant potential of histone deacetylase inhibitors. Microglial FOXO3a deficiency in mice alleviated LPS-induced neuro-inflammation and depression-like behaviours but failed to reduce anxiety behaviour, whereas pharmacological inhibition of PPAR-γ by GW9662 restored LPS-induced microglial activation and depressive-like behaviours in microglial FOXO3a-deficient mice. CONCLUSION AND IMPLICATIONS: FOXO3a/PPAR-γ axis plays an important role in microglial activation and depression, identifying a new therapeutic avenue for the treatment of major depression.

Exploring intricate connectivity patterns for cognitive functioning and neurological disorders: incorporating frequency-domain NC method into fMRI analysis.

This study extends the application of the frequency-domain new causality method to functional magnetic resonance imaging analysis. Strong causality, weak causality, balanced causality, cyclic causality, and transitivity causality were constructed to simulate varying degrees of causal associations among multivariate functional-magnetic-resonance-imaging blood-oxygen-level-dependent signals. Data from 1,252 groups of individuals with different degrees of cognitive impairment were collected. The frequency-domain new causality method was employed to construct directed efficient connectivity networks of the brain, analyze the statistical characteristics of topological variations in brain regions related to cognitive impairment, and utilize these characteristics as features for training a deep learning model. The results demonstrated that the frequency-domain new causality method accurately detected causal associations among simulated signals of different degrees. The deep learning tests also confirmed the superior performance of new causality, surpassing the other three methods in terms of accuracy, precision, and recall rates. Furthermore, consistent significant differences were observed in the brain efficiency networks, where several subregions defined by the multimodal parcellation method of Human Connectome Project simultaneously appeared in the topological statistical results of different patient groups. This suggests a significant association between these fine-grained cortical subregions, driven by multimodal data segmentation, and human cognitive function, making them potential biomarkers for further analysis of Alzheimer's disease.

IL-4-induced decrease in both the number and CTLA-4 expression of Treg impairs suppression of Th2 type inflammation in severe atopic dermatitis.

BACKGROUND: Treg plays a pivotal role in the suppression of Th2 cell and the maintenance of immune homeostasis. The precise molecular mechanism underlying the disruption of Treg suppression of Th2 cell and the promotion of Th2 type inflammation in allergic diseases remains elusive. OBJECTIVE: This study aims to investigate the molecular mechanism underlying quantitative and functional changes of Treg in AD. METHODS: The molecular mechanism was investigated using flow cytometry, mRNA sequencing, co-culture experiments, co-immunoprecipitation, chromatin immunoprecipitation, and bisulfite sequencing in vitro or in AD mice model and patients with AD. RESULTS: Increased proportion of Treg was detected in mild and moderate AD. Conversely, characteristic decrease in both the number and CTLA-4 expression of Treg was relevant to serum IL-4 level in severe AD patients, which was verified under a high concentration of IL-4 treatment in vitro. The underlying mechanism is that IL-4/pSTAT6 pathway recruits DNMT1 and HDAC2 to inhibit transcriptional regulation of Foxp3 and CTLA-4 loci. High level of IL-4 impaired the suppression of Treg against Th2 cell differentiation mediated by CTLA-4, and blockade of IL-4Rα signaling in Treg restored Treg number and suppression of Th2 cell in AD model mice and patients with AD. CONCLUSION: The number of Treg is relevant to stratification of severity and serum IL-4 level in patients with AD. Abnormal high level of IL-4 epigenetically triggers a decrease in both the number and CTLA-4 expression of Treg. The reduced expression of CTLA-4 on Treg induced by IL-4 impairs suppression of Th2 cell differentiation.

Microglial FoxO3a deficiency ameliorates ferroptosis-induced brain injury of intracerebral haemorrhage via regulating autophagy and heme oxygenase-1.

Microglial HO-1 regulates iron metabolism in the brain. Intracerebral haemorrhage (ICH) shares features of ferroptosis and necroptosis; hemin is an oxidized product of haemoglobin from lysed red blood cells, leading to secondary injury. However, little is known about the underlying molecular mechanisms attributable to secondary injury by hemin or ICH. In this study, we first show that FoxO3a was highly co-located with neurons and microglia but not astrocytes area of ICH model mice. Hemin activated FoxO3a/ATG-mediated autophagy and HO-1 signalling resulting in ferroptosis in vitro and in a mice model of brain haemorrhage. Accordingly, autophagy inhibitor Baf-A1 or HO-1 inhibitor ZnPP protected against hemin-induced ferroptosis. Hemin promoted ferroptosis of neuronal cells via FoxO3a/ATG-mediated autophagy and HO-1 signalling pathway. Knock-down of FoxO3a inhibited autophagy and prevented hemin-induced ferroptosis dependent of HO-1 signalling. We first showed that hemin stimulated microglial FoxO3a/HO-1 expression and enhanced the microglial polarisation towards the M1 phenotype, while knockdown of microglial FoxO3a inhibited pro-inflammatory cytokine production in microglia. Furthermore, the microglia activation in the striatum showed significant along with a high expression level of FoxO3a in the ICH mice. We found that conditional knockout of FoxO3a in microglia in mice alleviated neurological deficits and microglia activation as well as ferroptosis-induced striatum injury in the autologous blood-induced ICH model. We demonstrate, for the first time, that FoxO3a/ATG-mediated autophagy and HO-1 play an important role in microglial activation and ferroptosis-induced striatum injury of ICH, identifying a new therapeutic avenue for the treatment of ICH.

Energy stress modulation of AMPK/FoxO3 signaling inhibits mitochondria-associated ferroptosis.

Cancer cells and ischemic diseases exhibit unique metabolic responses and adaptations to energy stress. Forkhead box O 3a (FoxO3a) is a transcription factor that plays an important role in cell metabolism, mitochondrial dysfunction and oxidative stress response. Although the AMP-activated protein kinase (AMPK)/FoxO3a signaling pathway plays a pivotal role in maintaining energy homeostasis under conditions of energy stress, the role of AMPK/FoxO3a signaling in mitochondria-associated ferroptosis has not yet been fully elucidated. We show that glucose starvation induced AMPK/FoxO3a activation and inhibited ferroptosis induced by erastin. Inhibition of AMPK or loss of FoxO3a in cancer cells under the glucose starvation condition can sensitize these cells to ferroptosis. Glucose deprivation inhibited mitochondria-related gene expression, reduced mitochondrial DNA(mtDNA) copy number, decreased expression of mitochondrial proteins and lowered the levels of respiratory complexes by inducing FoxO3a. Loss of FoxO3a promoted mitochondrial membrane potential hyperpolarization, oxygen consumption, lipid peroxide accumulation and abolished the protective effects of energy stress on ferroptosis in vitro. In addition, we identified a FDA-approved antipsychotic agent, the potent FoxO3a agonist trifluoperazine, which largely reduced ferroptosis-associated cerebral ischemia-reperfusion (CIR) injuries in rats through AMPK/FoxO3a/HIF-1α signaling and mitochondria-dependent mechanisms. We found that FoxO3a binds to the promoters of SLC7A11 and reduces CIR-mediated glutamate excitotoxicity through inhibiting the expression of SLC7A11. Collectively, these results suggest that energy stress modulation of AMPK/FoxO3a signaling regulates mitochondrial activity and alters the ferroptosis response. The regulation of FoxO3a by AMPK may play a crucial role in mitochondrial gene expression that controls energy balance and confers resistance to mitochondria-associated ferroptosis and CIR injuries.

A novel particle swarm optimization based on hybrid-learning model.

The convergence speed and the diversity of the population plays a critical role in the performance of particle swarm optimization (PSO). In order to balance the trade-off between exploration and exploitation, a novel particle swarm optimization based on the hybrid learning model (PSO-HLM) is proposed. In the early iteration stage, PSO-HLM updates the velocity of the particle based on the hybrid learning model, which can improve the convergence speed. At the end of the iteration, PSO-HLM employs a multi-pools fusion strategy to mutate the newly generated particles, which can expand the population diversity, thus avoid PSO-HLM falling into a local optima. In order to understand the strengths and weaknesses of PSO-HLM, several experiments are carried out on 30 benchmark functions. Experimental results show that the performance of PSO-HLM is better than other the-state-of-the-art algorithms.

Sodium thiosulfate inhibits epithelial-mesenchymal transition in melanoma via regulating the Wnt/ß-catenin signaling pathway.

BACKGROUND: Melanoma is the most common form of skin cancer. Given its high metastasis and high recurrence, its therapies are constantly updated. OBJECTIVE: The study aims to prove the efficacy of sodium thiosulfate (STS), an antidote to cyanide or nitroprusside poisoning, in melanoma treatment. METHODS: We tested the effect of STS by culturing melanoma cells (B16 and A375) in vitro and establishing melanoma mouse models in vivo. The proliferation and viability of melanoma cells were measured by the CCK-8 test, cell cycle assay, apoptosis analysis, wound healing assay, and transwell migration assay. The expression of apoptosis-related molecules, epithelial-mesenchymal transition (EMT)-associated molecules, and the Wnt/ß-catenin signaling pathway-related molecules were determined by Western blotting and immunofluorescence. RESULTS: The high metastasis of melanoma is considered to be linked to the EMT process. The scratch assay using B16 and A375 cells also showed that STS could inhibit the EMT process of melanoma. We demonstrated that STS inhibited the proliferation, viability, and EMT process of melanoma by releasing H2S. STS-mediated weakening of cell migration was related to the inhibition of the Wnt/ß-catenin signaling pathway. Mechanistically, we defined that STS inhibited the EMT process via the Wnt/ß-catenin signaling pathway. CONCLUSIONS: These results suggest that the negative effect of STS on melanoma development is mediated by the reduction of EMT via the regulation of the Wnt/ß-catenin signaling pathway, which provides a new clue to treating melanoma.

Arrhythmia Disease Diagnosis Based on ECG Time-Frequency Domain Fusion and Convolutional Neural Network.

Electrocardiogram (ECG) signals are often used to diagnose cardiac status. However, most of the existing ECG diagnostic methods only use the time-domain information, resulting in some obviously lesion information in frequency-domain of ECG signals are not being fully utilized. Therefore, we propose a method to fuse the time and frequency domain information in ECG signals by convolutional neural network (CNN). First, we adapt multi-scale wavelet decomposition to filter the ECG signal; Then, R-wave localization is used to segment each individual heartbeat cycle; And then, the frequency domain information of this heartbeat cycle is extracted via fast Fourier transform. Finally, the temporal information is spliced with the frequency domain information and input to the neural network for classification. The experimental results show that the proposed method has the highest recognition accuracy (99.43%) of ECG singles compared with state-of-the-art methods. Clinical and Translational Impact Statement- The proposed ECG classification method provides an effective solution for ECG interrogation to quickly diagnose the presence of arrhythmia in a patient from the ECG signal. It can increase the efficiency of the interrogating physician by aiding diagnosis.

Structure and histochemistry of the stem of Dracaena cambodiana Pierre ex Gagnep.

Dracaena cambodiana Pierre ex Gagnep is an important plant resource for producing dragon's blood and one of most popular ornamental trees in China. For a better understanding of the physiological function of the stem, the structural characteristics and main substance histological location of the stems of D. cambodiana were studied. The structural characteristics of the different developmental stages of stems of D. cambodiana were observed and described detailly. And then a schematic diagram of the mature stem was created. Histochemical staining showed that two kinds of polysaccharides distributed in parenchymal cells. Saponins distributed mainly in ground tissue and phenolic compounds distributed mainly in the thick cell walls. An abundant of calcium oxalate raphide bundles were identified in cortex and primary tissue. Finally, the role of the above results in the taxonomy of Dracaena species and in their strong adaptability was discussed.

A Prognostic Model Generated from an Apparent Diffusion Coefficient Ratio Reliably Predicts the Outcomes of Oral Tongue Squamous Cell Carcinoma.

This study aimed to develop an apparent diffusion coefficient (ADC) ratio-based prognostic model to predict the recurrence and disease-free survival (DFS) of oral tongue squamous cell carcinoma (OTSCC). A total of 188 patients with cT1-2 oral tongue squamous cell carcinoma were enrolled retrospectively. Clinical and laboratory data were extracted from medical records. The ADC values were measured at the regions of interest of the tumor and non-tumor tissues of the MRI images, and the ADC ratio was used for comparison between the patient with recurrence (n = 83 case, 44%) and patients without recurrence (n = 105 cases, 56%). Cox proportional hazards models were generated to analyze the risk factors of cancer recurrence. A nomogram was developed based on significant risk factors to predict 1-, 5- and 10-year DFS. The receiver operator characteristic (ROC) curves of predictors in the multivariable Cox proportional hazards prognostic model were generated to predict the recurrence and DFS. The integrated areas under the ROC curve were calculated to evaluate discrimination of the models. The ADC ratio, tumor thickness and lymph node ratio were reliable predictors in the final prognostic model. The final model had a 71.1% sensitivity and an 81.0% specificity. ADC ratio was the strongest predictor of cancer recurrence in prognostic performance. Discrimination and calibration statistics were satisfactory with C-index above 0.7 for both model development and internal validation. The calibration curve showed that the 5- and 10-year DFS predicted by the nomogram agreed with actual observations.

Prognostic Value of Different Computed Tomography Scoring Systems in Patients With Severe Traumatic Brain Injury Undergoing Decompressive Craniectomy.

OBJECTIVE: In this study, we investigate the preoperative and postoperative computed tomography (CT) scores in severe traumatic brain injury (TBI) patients undergoing decompressive craniectomy (DC) and compare their predictive accuracy. METHODS: Univariate and multivariate logistic regression analyses were used to determine the relationship between CT score (preoperative and postoperative) and mortality at 30 days after injury. The discriminatory power of preoperative and postoperative CT score was assessed by the area under the receiver operating characteristic curve (AUC). RESULTS: Multivariate logistic regression analysis adjusted for the established predictors of TBI outcomes showed that preoperative Rotterdam CT score (odds ratio [OR], 3.60; 95% confidence interval [CI], 1.13-11.50; P = 0.030), postoperative Rotterdam CT score (OR, 4.17; 95% CI, 1.63-10.66; P = 0.003), preoperative Stockholm CT score (OR, 3.41; 95% CI, 1.42-8.18; P = 0.006), postoperative Stockholm CT score (OR, 4.50; 95% CI, 1.60-12.64; P = 0.004), preoperative Helsinki CT score (OR, 1.44; 95% CI, 1.03-2.02; P = 0.031), and postoperative Helsinki CT score (OR, 2.55; 95% CI, 1.32-4.95; P = 0.005) were significantly associated with mortality. The performance of the postoperative Rotterdam CT score was superior to the preoperative Rotterdam CT score (AUC, 0.82-0.97 vs 0.71-0.91). The postoperative Stockholm CT score was superior to the preoperative Stockholm CT score (AUC, 0.76-0.94 vs 0.72-0.92). The postoperative Helsinki CT score was superior to the preoperative Helsinki CT score (AUC, 0.88-0.99 vs 0.65-0.87). CONCLUSIONS: In conclusion, assessing the CT score before and after DC may be more precise and efficient for predicting early mortality in severe TBI patients who undergo DC.

Protection-Free Strategy for the Synthesis of Boro-Depsipeptides in Aqueous Media under Microwave-Assisted Conditions.

In this report, 19 boron-containing depsipeptides were synthesized via microwave-assisted Passerini three-component reaction (P-3CR) in an aqueous environment. The linker-free DAHMI fluorescent tagging approach was used on selected boron-containing compounds to study the relationship between their structures and their level of cellular uptake of HEK293 cells. The biological data retrieved from the DAHMI experiments indicated that while the structures of tested compounds may be highly similar, their bio-distribution profile could be vastly distinctive. The reported optimized one-pot synthetic strategy along the linker-free in vitro testing protocol could provide an efficient platform to accelerate the development of boron-containing drugs.

Connectivity and variability of related cognitive subregions lead to different stages of progression toward Alzheimer's disease.

Single modality MRI data is not enough to depict and discern the cause of the underlying brain pathology of Alzheimer's disease (AD). Most existing studies do not perform well with multi-group classification. To reveal the structural, functional connectivity and functional topological relationships among different stages of mild cognitive impairment (MCI) and AD, a novel method was proposed in this paper for the analysis of regional importance with an improved deep learning model. Obvious drift of related cognitive regions can be observed in the prefrontal lobe and surrounding the cingulate area in the right hemisphere when comparing AD and healthy controls (HC) based on absolute weights in the classification mode. Alterations of these regions being responsible for cognitive impairment have been previously reported. Different parcellation atlases of the human cerebral cortex were compared, and the fine-grained multimodal parcellation HCPMMP performed the best with 180 cortical areas per hemisphere. In multi-group classification, the highest accuracy achieved was 96.86% with the utilization of structural and functional topological modalities as input to the training model. Weights in the trained model with perfect discriminating ability quantify the importance of each cortical region. This is the first time such a phenomenon is discovered and weights in cortical areas are precisely described in AD and its prodromal stages to the best of our knowledge. Our findings can establish other study models to differentiate the patterns in various diseases with cognitive impairments and help to identify the underlying pathology.

Method of wavefront phase retrieval from wavefront curvature sensing using membrane modes.

Wavefront phase retrieval is one of the most critical problems in adaptive optics. Here, phase retrieval by solving the transport of intensity equation using membrane vibration modes is proposed. Our study shows that the wavefront curvature sensing signal on the pupil can be expanded as a set of corresponding membrane vibration modes. The analytic expressions of the reconstructed phase are given. The coefficients of the functions are obtained by the integral over the pupil and boundary. Several representative Zernike circular and annular polynomials are respectively fitted by eigenfunctions and membrane modes in the absence of noise. In addition, wavefront recovery from noisy curvature data of the simulated atmospheric turbulence phase based on Zernike modes and Kolmogorov spectrum is demonstrated to verify the accuracy and robustness of the proposed method.

Canstatin represses glioma growth by inhibiting formation of VM-like structures.

Vasculogenic mimicry (VM) is different from classical tumor angiogenesis and does not depend on endothelial cells. VM is closely related to the prognosis of various cancers. Canstatin was first identified as an endogenous angiogenesis inhibitor. In the present study, the inhibitory effect of canstatin on VM formation was evaluated. Human glioblastoma cell lines U87 and U251 were letivirally transduced to overexpress canstatin gene or GFP as control. In vitro assays showed that canstatin overexpression reduced the tube formation of U87 and U251 cells in Matrigel. A xenograft glioma model was created by subcutaneous injection of lentivirally modified U87 cells into nude mice. The results of in vivo experiments showed that canstatin gene introduction inhibited the growth of glioma xenografts. In tumor xenografts overexpressing canstatin, U87-mediated formation of VM-like structures and VM-related VEGF (vascular endothelial growth factor) expression were remarkably reduced. Canstatin overexpression also decreased the phosphorylation of Akt and reduced the expression of Survivin in vitro. In addition, HIF-1α production and MMP-2 secretion were decreased by canstatin overexpression. Therefore, these results suggested a protective role of canstatin during VM-like structure formation of glioma probably via inhibiting signaling pathways inducing vasculogenic mimicry.

Identifying and characterizing different stages toward Alzheimer's disease using ordered core features and machine learning.

Based on the joint HCPMMP parcellation method we developed before, which divides the cortical brain into 360 regions, the concept of ordered core features (OCF) is first proposed to reveal the functional brain connectivity relationship among different cohorts of Alzheimer's disease (AD), late mild cognitive impairment (LMCI), early mild cognitive impairment (EMCI) and healthy controls (HC). A set of core network features that change significantly under the specifically progressive relationship were extracted and used as supervised machine learning classifiers. The network nodes in this set mainly locate in the frontal lobe and insular, forming a narrow band, which are responsible for cognitive impairment as suggested by previous finding. By using these features, the accuracy ranged from 86.0% to 95.5% in binary classification between any pair of cohorts, higher than 70.1%-91.0% when using all network features. In multi-group classification, the average accuracy was 75% or 78% for HC, EMCI, LMCI or EMCI, LMCI, AD against baseline of 33%, and 53.3% for HC, EMCI, LMCI and AD against baseline of 25%. In addition, the recognition rate was lower when combining EMCI and LMCI patients into one group of mild cognitive impairment (MCI) for classification, suggesting that there exists a big difference between early and late MCI patients. This finding supports the EMCI/LMCI inclusion criteria introduced by ADNI based on neuropsychological assessments.

A novel causality-centrality-based method for the analysis of the impacts of air pollutants on PM2.5 concentrations in China.

In this paper, we analyzed the spatial and temporal causality and graph-based centrality relationship between air pollutants and PM2.5 concentrations in China from 2013 to 2017. NO2, SO2, CO and O3 were considered the main components of pollution that affected the health of people; thus, various joint regression models were built to reveal the causal direction from these individual pollutants to PM2.5 concentrations. In this causal centrality analysis, Beijing was the most important area in the Jing-Jin-Ji region because of its developed economy and large population. Pollutants in Beijing and peripheral cities were studied. The results showed that NO2 pollutants play a vital role in the PM2.5 concentrations in Beijing and its surrounding areas. An obvious causality direction and betweenness centrality were observed in the northern cities compared with others, demonstrating the fact that the more developed cities were most seriously polluted. Superior performance with causal centrality characteristics in the recognition of PM2.5 concentrations has been achieved.

The trend of indirect anastomosis formation in a 2-vessel occlusion plus encephalo-myo-synangiosis rat model.

BACKGROUND: Basic research on the factors influencing indirect anastomosis formation in a 2-vessel occlusion plus encephalo-myo-synangiosis (2VO + EMS) rat model is conducive to improving the efficacy of indirect revascularization surgery in the clinic. However, the time point at which anastomosis between the rat temporal muscle (TM) and brain naturally has the greatest effect after encephalo-myo-synangiosis (EMS) remains unknown. Therefore, we conducted this study to explore the peak time of indirect anastomosis formation in the 2VO + EMS rat model. METHODS: Forty 2VO + EMS rats were randomly divided into five groups (n=8) according to the length of time (by week) after EMS, and 2VO rats were used as the control group (n=8). The expression of vascular endothelial growth factor (VEGF) and CD31 on the EMS side of the brain, perfusion ratio [improvement of cerebral blood perfusion (CBP) on the EMS side] and Morris water maze (MWM) results were compared between groups. Furthermore, the trends of the above variables were explored over weeks. RESULTS: Overall, the expression of VEGF and CD31, the perfusion ratio and the cognitive improvement in the 2VO + EMS rat model gradually increased over weeks after EMS. The VEGF and CD31 expression (as detected by immunofluorescence), perfusion ratio and number of times crossing the platform area peaked at 4 weeks after EMS. In addition, both the escape latency and the time spent in the target quadrant peaked in the fifth week after EMS. CONCLUSIONS: After establishing the 2VO + EMS rat model, the degree of endothelial cell (EC) proliferation and CBP improvement on the EMS side of the brain peaked at 4 weeks after EMS, whereas the cognitive improvement peaked in the fifth week.

RF Heating Analysis of Implanted lead wires under 3.0 Tesla Magnetic Resonance Imaging System.

RF heating has severely limited the application of high-field magnetic resonance imaging (MRI) in the patients with active implantable medical devices (AIMDs). Based on the finite element methods (FEMs), we study the RF heating of a lead implanted in the human body under 3.0 T MRI. The coupled simulation of electromagnetic and heat transfer is used to analyze the relationship between several factors, such as the resonance length, the implantation position, the implantation configuration, and the thermal conductivity, and RF heating. Results show that the resonance length of the lead is half of the RF wavelength, and the temperature rise exceeds the acceptable range of human body when the resonance occurs. The electromagnetic field distribution in the phantom is not uniform, so the field density around the wire may vary with different implantation positions and configurations. Temperature rise reduces with the decrease of the field density. In addition, RF heating can be reduced by increasing the thermal conductivity.

Characteristics and variability of functional brain networks.

Functional brain networks were constructed from functional magnetic resonance imaging (fMRI) data originating from 96 healthy adults. These networks possessed a total of 360 nodes, derived from the latest multi-modal brain parcellation method. A novel group network (overlay network) analysis model is proposed to study common attributes as well as differences found in the human brain by analysis of the functional brain network. Currently, the mean network is generally used to represent the group network. But mean networks have a modularity problem making them distinct from real networks. The overlay network is constructed by calculating the connections between the whole brain network regions, and then filtering the connections by limiting the threshold value. We find that the overlay network is closer to the real network condition of the group in terms of network characteristics related to modularity. Multiple network features are applied to investigate the discrepancies between the new group network and the mean network. Individual divergences between brain regions of everyone are also explored. Results show that the brain network of different people has a high consistency in the global measures, while there exist great differences for local measures in brain regions. Some brain regions show variability over other brain regions on most measures. In addition, we explored the impact of different thresholds on the overlay network and find that different thresholds have a greater impact on the clustering coefficient, maximized modularity, strength, and global efficiency.