Whole-brain radiotherapy associated with structural changes resembling aging as determined by anatomic surface-based deep learning.

BACKGROUND: Brain metastases are the most common intracranial tumors in adults and are associated with significant morbidity and mortality. Whole-brain radiotherapy (WBRT) is used frequently in patients for palliation, but can result in neurocognitive deficits. While dose-dependent injury to individual areas such as the hippocampus has been demonstrated, global structural shape changes after WBRT remain to be studied. METHODS: We studied healthy controls and patients with brain metastases and examined MRI brain anatomic surface data before and after WBRT. We implemented a validated graph convolutional neural network model to estimate patient's "brain age". We further developed a mixed-effects linear model to compare the estimated age of the whole brain and substructures before and after WBRT. RESULTS: 4220 subjects were analyzed (4148 healthy controls and 72 patients). The median radiation dose was 30 Gy (range 25-37.5 Gy). The whole brain and substructures underwent structural change resembling rapid aging in radiated patients compared to healthy controls; the whole brain "aged" 9.32 times faster, the cortex 8.05 times faster, the subcortical structures 12.57 times faster, and the hippocampus 10.14 times faster. In a subset analysis, the hippocampus "aged" 8.88 times faster in patients after conventional WBRT versus after hippocampal avoidance (HA)-WBRT. CONCLUSIONS: Our findings suggest that WBRT causes the brain and its substructures to undergo structural changes at a pace up to 13x of the normal aging pace, where hippocampal avoidance offers focal structural protection. Correlating these structural imaging changes with neurocognitive outcomes following WBRT or HA-WBRT would benefit from future analysis.

A multicohort geometric deep learning study of age dependent cortical and subcortical morphologic interactions for fluid intelligence prediction.

The relationship of human brain structure to cognitive function is complex, and how this relationship differs between childhood and adulthood is poorly understood. One strong hypothesis suggests the cognitive function of Fluid Intelligence (Gf) is dependent on prefrontal cortex and parietal cortex. In this work, we developed a novel graph convolutional neural networks (gCNNs) for the analysis of localized anatomic shape and prediction of Gf. Morphologic information of the cortical ribbons and subcortical structures was extracted from T1-weighted MRIs within two independent cohorts, the Adolescent Brain Cognitive Development Study (ABCD; age: 9.93 ± 0.62 years) of children and the Human Connectome Project (HCP; age: 28.81 ± 3.70 years). Prediction combining cortical and subcortical surfaces together yielded the highest accuracy of Gf for both ABCD (R = 0.314) and HCP datasets (R = 0.454), outperforming the state-of-the-art prediction of Gf from any other brain measures in the literature. Across both datasets, the morphology of the amygdala, hippocampus, and nucleus accumbens, along with temporal, parietal and cingulate cortex consistently drove the prediction of Gf, suggesting a significant reframing of the relationship between brain morphology and Gf to include systems involved with reward/aversion processing, judgment and decision-making, motivation, and emotion.

Geometric deep learning reveals a structuro-temporal understanding of healthy and pathologic brain aging.

Background: Brain age has historically been investigated primarily at the whole brain level. The ability to deconstruct the brain into its composite parts and explore brain age at the sub-structure level offers unique advantages. These include the exploration of dynamic and interconnected relationships between different brain structures in healthy and pathologic aging. To achieve this, individual brain structures can be rendered as surface representations on which morphologic analysis is carried out. Combining the advantages of deep learning with the strengths of surface analysis, we investigate the aging process at the individual structure level with the hypothesis being that pathologic aging does not uniformly affect the aging process of individual structures. Methods: MRI data, age at scan time and diagnosis of dementia were collected from seven publicly available data repositories. The data from 17,440 unique subjects were collected, representing a total of 26,276 T1-weighted MRI accounting for longitudinal acquisitions. Surfaces were extracted for the cortex and seven subcortical structures. Deep learning networks were trained to estimate a subject's age either using several structures together or a single structure. We conducted a cross-sectional analysis to assess the difference between the predicted and actual ages for all structures between healthy subjects, individuals with mild cognitive impairment (MCI) or Alzheimer's disease dementia (ADD). We then performed a longitudinal analysis to assess the difference in the aging pace for each structure between stable healthy controls and healthy controls converting to either MCI or ADD. Findings: Using an independent cohort of healthy subjects, age was well estimated for all structures. Cross-sectional analysis identified significantly larger predicted age for all structures in patients with either MCI and ADD compared to healthy subjects. Longitudinal analysis revealed varying degrees of involvement of individual subcortical structures for both age difference across groups and aging pace across time. These findings were most notable in the whole brain, cortex, hippocampus and amygdala. Conclusion: Although similar patterns of abnormal aging were found related to MCI and ADD, the involvement of individual subcortical structures varied greatly and was consistently more pronounced in ADD patients compared to MCI patients.

Performance after training in a complex cognitive task is enhanced by high-definition transcranial random noise stimulation.

Interest for neuromodulation, and transcranial random noise stimulation (tRNS) in particular, is growing. It concerns patients rehabilitation, but also healthy people who want or need to improve their cognitive and learning abilities. However, there is no consensus yet regarding the efficacy of tRNS on learning and performing a complex task. In particular, the most effective electrode montage is yet to be determined. Here, we examined the effect of two different tRNS montages on learning rate, short- and long-term performance in a video game (Space Fortress) that engages multiple cognitive abilities. Sixty-one participants were randomly assigned to one of three groups (sham vs. simple-definition tRNS vs. high-definition tRNS) in a double-blind protocol. Their performance on the Space Fortress task was monitored during a 15-day experiment with baseline (day 1), stimulation (day 2 to 4), short- (day 5) and long-term (day 15) evaluations. Our results show that the high-definition tRNS group improved more on the long term than simple-definition tRNS group, tended to learn faster and had better performance retention compared to both simple-definition tRNS and sham groups. This study is the first to report that high-definition tRNS is more effective than conventional simple-definition tRNS to enhance performance in a complex task.

Automatic segmentation of deep grey nuclei using a high-resolution 7T magnetic resonance imaging atlas-Quantification of T1 values in healthy volunteers.

We present a new consensus atlas of deep grey nuclei obtained by shape-based averaging of manual segmentation of two experienced neuroradiologists and optimized from 7T MP2RAGE images acquired at (.6 mm)3 in 60 healthy subjects. A group-wise normalization method was used to build a high-contrast and high-resolution T1 -weighted brain template (.5 mm)3 using data from 30 out of the 60 controls. Delineation of 24 deep grey nuclei per hemisphere, including the claustrum and 12 thalamic nuclei, was then performed by two expert neuroradiologists and reviewed by a third neuroradiologist according to tissue contrast and external references based on the Morel atlas. Corresponding deep grey matter structures were also extracted from the Morel and CIT168 atlases. The data-derived, Morel and CIT168 atlases were all applied at the individual level using non-linear registration to fit the subject reference and to extract absolute mean quantitative T1 values derived from the 3D-MP2RAGE volumes, after correction for residual B1+ biases. Three metrics (the Dice and the volumetric similarity coefficients and a novel Hausdorff distance) were used to estimate the inter-rater agreement of manual MRI segmentation and inter-atlas variability, and these metrics were measured to quantify biases due to image registration, and their impact on the measurements of the quantitative T1 values was highlighted. This represents a fully automated segmentation process permitting the extraction of unbiased normative T1 values in a population of young healthy controls as a reference for characterizing subtle structural alterations of deep grey nuclei relevant to a range of neurological diseases.

Voltage-Gated Sodium Channel NaV1.5 Controls NHE-1-Dependent Invasive Properties in Colon Cancer Cells.

Colorectal cancer (CRC) is the second leading cause of death worldwide, with 0.9 million deaths per year. The metastatic stage of the disease is identified in about 20% of cases at the first diagnosis and is associated with low patient-survival rates. Voltage-gated sodium channels (NaV) are abnormally overexpressed in several carcinomas including CRC and are strongly associated with the metastatic behavior of cancer cells. Acidification of the extracellular space by Na+/H+ exchangers (NHE) contributes to extracellular matrix degradation and cell invasiveness. In this study, we assessed the expression levels of pore-forming α-subunits of NaV channels and NHE exchangers in tumor and adjacent non-malignant tissues from colorectal cancer patients, CRC cell lines and primary tumor cells. In all cases, SCN5A (gene encoding for NaV1.5) was overexpressed and positively correlated with cancer stage and poor survival prognosis for patients. In addition, we identified an anatomical differential expression of SCN5A and SLC9A1 (gene encoding for NHE-1) being particularly relevant for tumors that originated on the sigmoid colon epithelium. The functional activity of NaV1.5 channels was characterized in CRC cell lines and the primary cells of colon tumors obtained using tumor explant methodologies. Furthermore, we assessed the performance of two new small-molecule NaV1.5 inhibitors on the reduction of sodium currents, as well as showed that silencing SCN5A and SLC9A1 substantially reduced the 2D invasive capabilities of cancer cells. Thus, our findings show that both NaV1.5 and NHE-1 represent two promising targetable membrane proteins against the metastatic progression of CRC.

The Voltage-Gated Sodium Channel Beta4 Subunit Maintains Epithelial Phenotype in Mammary Cells.

The SCN4B gene, coding for the NaVß4 subunit of voltage-gated sodium channels, was recently found to be expressed in normal epithelial cells and down-regulated in several cancers. However, its function in normal epithelial cells has not been characterized. In this study, we demonstrated that reducing NaVß4 expression in MCF10A non-cancer mammary epithelial cells generated important morphological changes observed both in two-dimensional cultures and in three-dimensional cysts. Most notably, the loss of NaVß4 induced a complete loss of epithelial organisation in cysts and increased proteolytic activity towards the extracellular matrix. Loss of epithelial morphology was associated with an increased degradation of ß-catenin, reduced E-cadherin expression and induction of mesenchymal markers N-cadherin, vimentin, and α-SMA expression. Overall, our results suggest that Navß4 may participate in the maintenance of the epithelial phenotype in mammary cells and that its downregulation might be a determining step in early carcinogenesis.

Geometric deep learning on brain shape predicts sex and age.

The complex relationship between the shape and function of the human brain remains elusive despite extensive studies of cortical folding over many decades. The analysis of cortical gyrification presents an opportunity to advance our knowledge about this relationship, and better understand the etiology of a variety of pathologies involving diverse degrees of cortical folding abnormalities. Hypothesis-driven surface-based approaches have been shown to be particularly efficient in their ability to accurately describe unique features of the folded sheet topology of the cortical ribbon. However, the utility of these approaches has been blunted by their reliance on manually defined features aiming to capture the relevant geometric properties of cortical folding. In this paper, we propose an entirely novel, data-driven deep-learning based method to analyze the brain's shape that eliminates this reliance on manual feature definition. This method builds on the emerging field of geometric deep-learning and uses traditional convolutional neural network architecture uniquely adapted to the surface representation of the cortical ribbon. This method is a complete departure from prior brain MRI CNN investigations, all of which have relied on three dimensional MRI data and interpreted features of the MRI signal for prediction. MRI data from 6410 healthy subjects obtained from 11 publicly available data repositories were used for analysis. Ages ranged from 6 to 89 years. Both inner and outer cortical surfaces were extracted using Freesurfer and then registered into MNI space. For purposes of method development, both a classification and regression challenge were introduced for network learning including sex and age prediction, respectively. Two independent graph convolutional neural networks (gCNNs) were trained, the first of which to predict subject's self-identified sex, the second of which to predict subject's age. Class Activation Maps (CAM) and Regression Activation Maps (RAM) were constructed respectively to map the topographic distribution of the most influential brain regions involved in the decision process for each gCNN. Using this approach, the gCNN was able to predict a subject's sex with an average accuracy of 87.99 % and achieved a Person's coefficient of correlation of 0.93 with an average absolute error 4.58 years when predicting a subject's age. We believe this shape-based convolutional classifier offers a novel, data-driven approach to define biomedically relevant features from the brain at both the population and single subject levels and therefore lays a critical foundation for future precision medicine applications.

Pharmacological and nutritional targeting of voltage-gated sodium channels in the treatment of cancers.

Voltage-gated sodium (NaV) channels, initially characterized in excitable cells, have been shown to be aberrantly expressed in non-excitable cancer tissues and cells from epithelial origins such as in breast, lung, prostate, colon, and cervix, whereas they are not expressed in cognate non-cancer tissues. Their activity was demonstrated to promote aggressive and invasive potencies of cancer cells, both in vitro and in vivo, whereas their deregulated expression in cancer tissues has been associated with metastatic progression and cancer-related death. This review proposes NaV channels as pharmacological targets for anticancer treatments providing opportunities for repurposing existing NaV-inhibitors or developing new pharmacological and nutritional interventions.

Bioinspired imidazo[1,2-a:4,5-c']dipyridines with dual antiproliferative and anti-migrative properties in human cancer cells: The SAR investigation.

Herein, we report the design, synthesis and evaluation of novel bioinspired imidazo[1,2-a:4,5c']dipyridines. The structural optimization identified four anti-proliferative compounds. Compounds 11, 18, 19 and 20 exhibited excellent anticancer activities in vitro with IC50 of 0.4-5 µM against three human cancer cell lines (MDA-MB-468, MDA-MB-435s and MDA-MB-231). These four compounds induced apoptosis in MDA-MB-231 cells in a dose-dependent manner, targeting different apoptotic proteins expression: 11 increased the expression of pro-apoptotic Bax protein while 18-20 reduced the level of anti-apoptotic Bcl-2 protein. Compounds 18 and 19 also reduced MDA-MB-231 cells proliferation as measured by Ki-67 staining. Furthermore, compounds were also tested for the ability to inhibit cell migration in the highly aggressive human MDA-MB-435s cell line. Six compounds of this series (8, 15, 18, 22, 23, 24) inhibited cell migration by 41-50% while four compounds (20, 25, 27, 30) inhibited the migration by 53-62% in wound-healing experiments. Interestingly, compound 20 presented both antiproliferative and anti-migration activities and might be a promising anti-metastatic agent for cancer treatment.

Structural constraints of functional connectivity drive cognitive impairment in the early stages of multiple sclerosis.

BACKGROUND: The relationship between structural and functional deficits in multiple sclerosis (MS) is unclear. OBJECTIVE: This study explored structure-function relationships during the 5 years following a clinically isolated syndrome and their role in cognitive performance. METHODS: Thirty-two patients were enrolled after their first neurological episode suggestive of MS and followed for 5 years, along with 10 matched healthy controls. We assessed structural (using diffusion tensor imaging) and functional (using resting-state functional magnetic resonance imaging (fMRI)) brain network metrics, clinical and cognitive scores at each follow-up visit. Structural-functional coupling, calculated as the correlation coefficient between strengths of structural and functional networks, was used to assess structure-function relationships. RESULTS: Structural clustering coefficient was significantly increased after 5 years, whereas characteristic path length decreased. Structural connections decreased after 1 year and increased after 5 years. Functional connections and related path lengths were decreased after 5 years. Structural-functional coupling had increased significantly after 5 years. This structural-functional coupling was associated with cognitive and clinical evolution, with stronger coupling associated with a decline in both domains. CONCLUSION: Our findings provide novel biological evidence that MS leads to a more constrained anatomical-dependant functional connectivity. The collapse of this network seems to lead to both cognitive worsening and clinical disability.

Interpretation of Brain Morphology in Association to Alzheimer's Disease Dementia Classification Using Graph Convolutional Networks on Triangulated Meshes.

We propose a mesh-based technique to aid in the classification of Alzheimer's disease dementia (ADD) using mesh representations of the cortex and subcortical structures. Deep learning methods for classification tasks that utilize structural neuroimaging often require extensive learning parameters to optimize. Frequently, these approaches for automated medical diagnosis also lack visual interpretability for areas in the brain involved in making a diagnosis. This work: (a) analyzes brain shape using surface information of the cortex and subcortical structures, (b) proposes a residual learning framework for state-of-the-art graph convolutional networks which offer a significant reduction in learnable parameters, and (c) offers visual interpretability of the network via class-specific gradient information that localizes important regions of interest in our inputs. With our proposed method leveraging the use of cortical and subcortical surface information, we outperform other machine learning methods with a 96.35% testing accuracy for the ADD vs. healthy control problem. We confirm the validity of our model by observing its performance in a 25-trial Monte Carlo cross-validation. The generated visualization maps in our study show correspondences with current knowledge regarding the structural localization of pathological changes in the brain associated to dementia of the Alzheimer's type.

Effects of Multiple Sessions of Cathodal Priming and Anodal HD-tDCS on Visuo Motor Task Plateau Learning and Retention.

A single session of priming cathodal transcranial direct current stimulation (tDCS) prior to anodal tDCS (c-a-tDCS) allows cumulative effects on motor learning and retention. However, the impact of multiple sessions of c-a-tDCS priming on learning and retention remains unclear. Here, we tested whether multiple sessions of c-a-tDCS (over 3 consecutive days) applied over the left sensorimotor cortex can further enhance motor learning and retention of an already learned visuo-motor task as compared to anodal tDCS (a-tDCS) or sham. In a between group and randomized double-blind sham-controlled study design, 25 participants separated in 3 independent groups underwent 2 days of baseline training without tDCS followed by 3-days of training with both online and offline tDCS, and two retention tests (1 and 14 days later). Each training block consisted of five trials of a 60 s circular-tracing task intersected by 60 s rest, and performance was assessed in terms of speed-accuracy trade-off represented notably by an index of performance (IP). The main findings of this exploratory study were that multiple sessions of c-a-tDCS significantly further enhanced IP above baseline training levels over the 3 training days that were maintained over the 2 retention days, but these learning and retention performance changes were not significantly different from the sham group. Subtle differences in the changes in speed-accuracy trade-off (components of IP) between c-a-tDCS (maintenance of accuracy over increasing speed) and a-tDCS (increasing speed over maintenance of accuracy) provide preliminary insights to a mechanistic modulation of motor performance with priming and polarity of tDCS.

P2X7 Receptor Promotes Mouse Mammary Cancer Cell Invasiveness and Tumour Progression, and Is a Target for Anticancer Treatment.

The P2X7 receptor is an ATP-gated cation channel with a still ambiguous role in cancer progression, proposed to be either pro- or anti-cancerous, depending on the cancer or cell type in the tumour. Its role in mammary cancer progression is not yet defined. Here, we show that P2X7 receptor is functional in highly aggressive mammary cancer cells, and induces a change in cell morphology with fast F-actin reorganization and formation of filopodia, and promotes cancer cell invasiveness through both 2- and 3-dimensional extracellular matrices in vitro. Furthermore, P2X7 receptor sustains Cdc42 activity and the acquisition of a mesenchymal phenotype. In an immunocompetent mouse mammary cancer model, we reveal that the expression of P2X7 receptor in cancer cells, but not in the host mice, promotes tumour growth and metastasis development, which were reduced by treatment with specific P2X7 antagonists. Our results demonstrate that P2X7 receptor drives mammary tumour progression and represents a pertinent target for mammary cancer treatment.

Rock inhibition promotes NaV1.5 sodium channel-dependent SW620 colon cancer cell invasiveness.

The acquisition of invasive capacities by carcinoma cells, i.e. their ability to migrate through and to remodel extracellular matrices, is a determinant process leading to their dissemination and to the development of metastases. these cancer cell properties have often been associated with an increased Rho-ROCK signalling, and ROCK inhibitors have been proposed for anticancer therapies. In this study we used the selective ROCK inhibitor, Y-27632, to address the participation of the Rho-ROCK signalling pathway in the invasive properties of SW620 human colon cancer cells. Contrarily to initial assumptions, Y-27632 induced the acquisition of a pro-migratory cell phenotype and increased cancer cell invasiveness in both 3- and 2-dimensions assays. This effect was also obtained using the other ROCK inhibitor Fasudil as well as with knocking down the expression of ROCK-1 or ROCK-2, but was prevented by the inhibition of NaV1.5 voltage-gated sodium channel activity. Indeed, ROCK inhibition enhanced the activity of the pro-invasive NaV1.5 channel through a pathway that was independent of gene expression regulation. In conclusions, our evidence identifies voltage-gated sodium channels as new targets of the ROCK signalling pathway, as well as responsible for possible deleterious effects of the use of ROCK inhibitors in the treatment of cancers.

Aerobic Exercise Induces Functional and Structural Reorganization of CNS Networks in Multiple Sclerosis: A Randomized Controlled Trial.

Objectives: Evidence from animal studies suggests that aerobic exercise may promote neuroplasticity and could, therefore, provide therapeutic benefits for neurological diseases such as multiple sclerosis (MS). However, the effects of exercise in human CNS disorders on the topology of brain networks, which might serve as an outcome at the interface between biology and clinical performance, remain poorly understood. Methods: We investigated functional and structural networks in patients with relapsing-remitting MS in a clinical trial of standardized aerobic exercise. Fifty-seven patients were randomly assigned to moderate-intensity exercise for 3 months or a non-exercise control group. We reconstructed functional networks based on resting-state functional magnetic resonance imaging (MRI) and used probabilistic tractography on diffusion-weighted imaging data for structural networks. Results: At baseline, compared to 30 healthy controls, patients exhibited decreased structural connectivity that was most pronounced in hub regions of the brain. Vice versa, functional connectivity was increased in hubs. After 3 months, we observed hub independent increased functional connectivity in the exercise group while the control group presented a loss of functional hub connectivity. On a structural level, the control group remained unchanged, while the exercise group had also increased connectivity. Increased clustering of hubs indicates a better structural integration and internal connectivity at the top of the network hierarchy. Conclusion: Increased functional connectivity of hubs contrasts a loss of structural connectivity in relapsing-remitting MS. Under an exercise condition, a further hub independent increase of functional connectivity seems to translate in higher structural connectivity of the whole brain.

Longitudinal study of functional brain network reorganization in clinically isolated syndrome.

BACKGROUND: There is a lack of longitudinal studies exploring the topological organization of functional brain networks at the early stages of multiple sclerosis (MS). OBJECTIVE: This study aims to assess potential brain functional reorganization at rest in patients with CIS (PwCIS) after 1 year of evolution and to characterize the dynamics of functional brain networks at the early stage of the disease. METHODS: We prospectively included 41 PwCIS and 19 matched healthy controls (HCs). They were scanned at baseline and after 1 year. Using graph theory, topological metrics were calculated for each region. Hub disruption index was computed for each metric. RESULTS: Hub disruption indexes of degree and betweenness centrality were negative at baseline in patients (p < 0.05), suggesting brain reorganization. After 1 year, hub disruption indexes for degree and betweenness centrality were still negative (p < 0.00001), but such reorganization appeared more pronounced than at baseline. Different brain regions were driving these alterations. No global efficiency differences were observed between PwCIS and HCs either at baseline or at 1 year. CONCLUSION: Dynamic changes in functional brain networks appear at the early stages of MS and are associated with the maintenance of normal global efficiency in the brain, suggesting a compensatory effect.

Autophagy and mitophagy in cancer metabolic remodelling.

Metabolic reprogramming in tumours is now recognized as a hallmark of cancer, participating both in tumour growth and cancer progression. Cancer cells develop global metabolic adaptations allowing them to survive in the low oxygen and nutrient tumour microenvironment. Among these metabolic adaptations, cancer cells use glycolysis but also mitochondrial oxidations to produce ATP and building blocks needed for their high proliferation rate. Another particular adaptation of cancer cell metabolism is the use of autophagy and specific forms of autophagy like mitophagy to recycle intracellular components in condition of metabolic stress or during anticancer treatments. The plasticity of cancer cell metabolism is a major limitation of anticancer treatments and could participate to therapy resistances. The aim of this review is to report recent advances in the understanding of the relationship between tumour metabolism and autophagy/mitophagy in order to propose new therapeutic strategies.

Sodium Channel Nav1.5 Controls Epithelial-to-Mesenchymal Transition and Invasiveness in Breast Cancer Cells Through its Regulation by the Salt-Inducible Kinase-1.

Loss of epithelial polarity and gain in invasiveness by carcinoma cells are critical events in the aggressive progression of cancers and depend on phenotypic transition programs such as the epithelial-to-mesenchymal transition (EMT). Many studies have reported the aberrant expression of voltage-gated sodium channels (NaV) in carcinomas and specifically the NaV1.5 isoform, encoded by the SCN5A gene, in breast cancer. NaV1.5 activity, through an entry of sodium ions, in breast cancer cells is associated with increased invasiveness, but its participation to the EMT has to be clarified. In this study, we show that reducing the expression of NaV1.5 in highly aggressive human MDA-MB-231 breast cancer cells reverted the mesenchymal phenotype, reduced cancer cell invasiveness and the expression of the EMT-promoting transcription factor SNAI1. The heterologous expression of NaV1.5 in weakly invasive MCF-7 breast cancer cells induced their expression of both SNAI1 and ZEB1 and increased their invasive capacities. In MCF-7 cells the stimulation with the EMT-activator signal TGF-ß1 increased the expression of SCN5A. Moreover, the reduction of the salt-inducible kinase 1 (SIK1) expression promoted NaV1.5-dependent invasiveness and expression of EMT-associated transcription factor SNAI1. Altogether, these results indicated a prominent role of SIK1 in regulating NaV1.5-dependent EMT and invasiveness.

Connectivity strength, time lag structure and the epilepsy network in resting-state fMRI.

The relationship between the epilepsy network, intrinsic brain networks and hypersynchrony in epilepsy remains incompletely understood. To converge upon a synthesized understanding of these features, we studied two elements of functional connectivity in epilepsy: correlation and time lag structure using resting state fMRI data from both SEEG-defined epileptic brain regions and whole-brain fMRI analysis. Functional connectivity (FC) was analyzed in 15 patients with epilepsy and 36 controls. Correlation strength and time lag were selected to investigate the magnitude of and temporal interdependency across brain regions. Zone-based analysis was carried out investigating directed correlation strength and time lag between both SEEG-defined nodes of the epilepsy network and between the epileptogenic zone and all other brain regions. Findings were compared between patients and controls and against a functional atlas. FC analysis on the nodal and whole brain levels identifies consistent patterns of altered correlation strength and altered time lag architecture in epilepsy patients compared to controls. These patterns include 1) broadly distributed increased strength of correlation between the seizure onset node and the remainder of the brain, 2) decreased time lag within the seizure onset node, and 3) globally increased time lag throughout all regions of the brain not involved in seizure onset or propagation. Comparing the topographic distribution of findings against a functional atlas, all resting state networks were involved to a variable degree. These local and whole brain findings presented here lead us to propose the network steal hypothesis as a possible mechanistic explanation for the non-seizure clinical manifestations of epilepsy.