Failure of adaptive self-organized criticality during epileptic seizure attacks

Critical dynamics are assumed to be an attractive mode for normal brain functioning as information processing and computational capabilities are found to be optimized there. Recent experimental observations of neuronal activity patterns following power-law distributions, a hallmark of systems at a critical state, have led to the hypothesis that human brain dynamics could be poised at a phase transition between ordered and disordered activity. A so far unresolved question concerns the medical significance of critical brain activity and how it relates to pathological conditions. Using data from invasive electroencephalogram recordings from humans we show that during epileptic seizure attacks neuronal activity patterns deviate from the normally observed power-law distribution characterizing critical dynamics. The comparison of these observations to results from a computational model exhibiting self-organized criticality (SOC) based on adaptive networks allows further insights into the underlying dynamics. Together these results suggest that brain dynamics deviates from criticality during seizures caused by the failure of adaptive SOC.Comment: 7 pages, 5 figure

31st Annual Meeting and Associated Programs of the Society for Immunotherapy of Cancer (SITC 2016) : part two

Background The immunological escape of tumors represents one of the main ob- stacles to the treatment of malignancies. The blockade of PD-1 or CTLA-4 receptors represented a milestone in the history of immunotherapy. However, immune checkpoint inhibitors seem to be effective in specific cohorts of patients. It has been proposed that their efficacy relies on the presence of an immunological response. Thus, we hypothesized that disruption of the PD-L1/PD-1 axis would synergize with our oncolytic vaccine platform PeptiCRAd. Methods We used murine B16OVA in vivo tumor models and flow cytometry analysis to investigate the immunological background. Results First, we found that high-burden B16OVA tumors were refractory to combination immunotherapy. However, with a more aggressive schedule, tumors with a lower burden were more susceptible to the combination of PeptiCRAd and PD-L1 blockade. The therapy signifi- cantly increased the median survival of mice (Fig. 7). Interestingly, the reduced growth of contralaterally injected B16F10 cells sug- gested the presence of a long lasting immunological memory also against non-targeted antigens. Concerning the functional state of tumor infiltrating lymphocytes (TILs), we found that all the immune therapies would enhance the percentage of activated (PD-1pos TIM- 3neg) T lymphocytes and reduce the amount of exhausted (PD-1pos TIM-3pos) cells compared to placebo. As expected, we found that PeptiCRAd monotherapy could increase the number of antigen spe- cific CD8+ T cells compared to other treatments. However, only the combination with PD-L1 blockade could significantly increase the ra- tio between activated and exhausted pentamer positive cells (p= 0.0058), suggesting that by disrupting the PD-1/PD-L1 axis we could decrease the amount of dysfunctional antigen specific T cells. We ob- served that the anatomical location deeply influenced the state of CD4+ and CD8+ T lymphocytes. In fact, TIM-3 expression was in- creased by 2 fold on TILs compared to splenic and lymphoid T cells. In the CD8+ compartment, the expression of PD-1 on the surface seemed to be restricted to the tumor micro-environment, while CD4 + T cells had a high expression of PD-1 also in lymphoid organs. Interestingly, we found that the levels of PD-1 were significantly higher on CD8+ T cells than on CD4+ T cells into the tumor micro- environment (p < 0.0001). Conclusions In conclusion, we demonstrated that the efficacy of immune check- point inhibitors might be strongly enhanced by their combination with cancer vaccines. PeptiCRAd was able to increase the number of antigen-specific T cells and PD-L1 blockade prevented their exhaus- tion, resulting in long-lasting immunological memory and increased median survival

Failure of adaptive self-organized criticality during epileptic seizure attacks.

Critical dynamics are assumed to be an attractive mode for normal brain functioning as information processing and computational capabilities are found to be optimal in the critical state. Recent experimental observations of neuronal activity patterns following power-law distributions, a hallmark of systems at a critical state, have led to the hypothesis that human brain dynamics could be poised at a phase transition between ordered and disordered activity. A so far unresolved question concerns the medical significance of critical brain activity and how it relates to pathological conditions. Using data from invasive electroencephalogram recordings from humans we show that during epileptic seizure attacks neuronal activity patterns deviate from the normally observed power-law distribution characterizing critical dynamics. The comparison of these observations to results from a computational model exhibiting self-organized criticality (SOC) based on adaptive networks allows further insights into the underlying dynamics. Together these results suggest that brain dynamics deviates from criticality during seizures caused by the failure of adaptive SOC

Noninvasive Assessment of the Circle of Willis in Cerebral Ischemia: The Potential of CT Angiography and Contrast-Enhanced Transcranial Color-Coded Duplexsonography

Thirty-four patients with acute hemispheric ischemic strokes underwent both CT angiography and contrast-enhanced transcranial color-coded duplexsonography (TCCD) to study the effectiveness of the combined noninvasive techniques for evaluation of the circle of Willis. In 3/34 patients, CT angiography and contrast-enhanced TCCD demonstrated middle cerebral artery (MCA) occlusion, in 5 others MCA stenosis. A severe posterior cerebral artery stenosis was missed by CT angiography. In 8 patients, contrast-enhanced TCCD failed because of poor bone windows. In these patients, CT angiography was normal. CT angiography and contrast-enhanced TCCD are complementary noninvasive diagnostic tools. Disagreements between the diagnostic findings of these methods still need further evaluation by digital subtraction angiography.Dieser Beitrag ist mit Zustimmung des Rechteinhabers aufgrund einer (DFG-geförderten) Allianz- bzw. Nationallizenz frei zugänglich

Distribution of PLI in a model exhibiting self-organized criticality.

<p>A Through an adaptive interplay of network dynamics and topology, the Bornholdt model self-organizes toward a characteristic connectivity independent of initial conditions. The plot shows the evolution to a characteristic connectivity of approximately in a network of 1024 nodes for three different initial connectivities, , and . B At this self-organized connectivity the network exhibits a phase transition between order and disorder. The plot shows the frozen component defined as the fraction of nodes that do not change their state along the attractor as a function of networks' average connectivities for a network of 1024 nodes. The data were measured along the dynamical attractor reached by the system, averaged over 100 random topologies for each value of . A transition around a value can be observed. C After a period of self-organization based on the adaptive interplay between topology and dynamics (aSO on, full black line), links were added and deleted solely with a certain probability independent of node activity (aSO off, dashed line: links were added with and deleted with , point-dashed line: links added with , deleted with ). Each iteration marks a topological update of the network, between iterations network activity was limited to 1000 time steps where topology was not changed. Phase-lock intervals between 20 randomly chosen nodes were calculated for scale 1 from 100 consecutive iterations at three time points: at the self-organized connectivity (bottom left), at a connectivity lower (bottom middle) and higher (bottom right) than the evolved connectivity. The distribution of PLI follows a power-law only at the self-organized connectivity (bottom left). All depicted distributions are cumulative distributions. The dashed line marks a power-law with exponent −1.5 to guide the eye.</p

The distribution of phase-locking intervals deviates from a power-law during epileptic seizures.

<p>Top: The electrocorticogram (ECoG) recording shows the onset of a focal epileptic seizure attack around 300 seconds time. Bottom: Cumulative distributions of phase-locking intervals (PLI) are obtained during three time intervals of 150 seconds: pre-ictal (left), ictal (middle) and post-ictal (right). Dashed lines indicate a power-law with exponent −3.1. While the distribution appears to follow a power-law during the pre-ictal period, intervals of increased phase-locking disturb this characteristic distribution with the onset of seizure activity. Data shown are from patient 1 at scale 3, corresponding to the frequency band 25–12.5 Hz.</p

Development of the deviation from a power-law.

<p>ECoG recordings from 8 patients showing a focal seizure attack are shown along with values for consecutive time windows of 150 seconds duration overlapping by 100 seconds. The power-law fit of data in the first time window was taken as the reference to calculate . Although different in extent, an increase of quantifying the deviation from the initial pre-ictal distribution can be observed during seizures for all patients and different scales (scale 2 red, scale 3 blue, scale 4 green).</p

Echo-Enhanced Transcranial Color-Coded Duplexsonography to Study Collateral Blood Flow in Patients with Symptomatic Obstructions of the Internal Carotid Artery and Limited Acoustic Bone Windows

We prospectively evaluated 30 consecutive patients with echo-enhanced transcranial color-coded duplexsonography (TCCD) and correlative transfemoral digital subtraction angiography to assess the diagnostic efficacy of echo-enhanced TCCD for evaluation of collateral pathways through the circle of Willis in patients with limited acoustic bone windows and critical symptomatic carotid disease. Echo-enhanced TCCD detected collateral blood flow through the anterior communicating artery in 16 of 18 patients (sensitivity 89%, 95% CI 65–99%) and was false positive in one out of 12 patients without collateral flow (specificity 92%, 95% CI 59–100%). For the posterior communicating artery, sensitivity was 11/14 (79%, 95% CI 49–95%) and specificity was 15/16 (94%, 95% CI 70–100%). Echo-enhanced TCCD enables to study collateral blood flow through the communicating arteries of the circle of Willis with high sensitivity and specificity in patients with obstructions of the internal carotid artery and limited acoustic bone windows.Dieser Beitrag ist mit Zustimmung des Rechteinhabers aufgrund einer (DFG-geförderten) Allianz- bzw. Nationallizenz frei zugänglich

Human Adult White Matter Progenitor Celts Are Multipotent Neuroprogenitors Similar to Adult Hippocampal Progenitors

Adult neural progenitor cells (aNPC) are a potential autologous cell source for cell replacement in neurologic diseases or for cell-based gene therapy of neurometabolic diseases. Easy accessibility, long-term expandability, and detailed characterization of neural progenitor cell (NPC) properties are important requisites for their future translational/clinical applications. aNPC can be isolated from different regions of the adult human brain, including the accessible subcortical white matter (aNPC_(WM)), but systematic studies comparing long-term expanded aNPC_(WM) with aNPC from neurogenic brain regions are not available. Freshly isolated cells from subcortical white matter and hippocampus expressed oligodendrocyte progenitor cell markers such as A2B5, neuron-glial antigen 2 (NG2), and oligodendrocyte transcription factor 2 (OLIG2) in ∼20% of cells but no neural stem cell (NSC) markers such as CD133 (Prominin1), Nestin, SOX2, or PAX6. The epidermal growth factor receptor protein was expressed in 18% of aNPC_(WM) and 7% of hippocampal aNPC (aNPC_(HIP)), but only a small fraction of cells, 1 of 694 cells from white matter and 1 of 1,331 hippocampal cells, was able to generate neurospheres. Studies comparing subcortical aNPC_(WM) with their hippocampal counterparts showed that both NPC types expressed mainly markers of glial origin such as NG2, A2B5, and OLIG2, and the NSC/NPC marker Nestin, but no pericyte markers. Both NPC types were able to produce neurons, astrocytes, and oligodendrocytes in amounts comparable to fetal NSC. Whole transcriptome analyses confirmed the strong similarity of aNPC_(WM) to aNPC_(HIP). Our data show that aNPC_(WM) are multipotent NPC with long-term expandability similar to NPC from hippocampus, making them a more easily accessible source for possible autologous NPC-based treatment strategies