A power-law distribution of phase-locking intervals does not imply critical interaction

Neural synchronisation plays a critical role in information processing, storage and transmission. Characterising the pattern of synchronisation is therefore of great interest. It has recently been suggested that the brain displays broadband criticality based on two measures of synchronisation - phase locking intervals and global lability of synchronisation - showing power law statistics at the critical threshold in a classical model of synchronisation. In this paper, we provide evidence that, within the limits of the model selection approach used to ascertain the presence of power law statistics, the pooling of pairwise phase-locking intervals from a non-critically interacting system can produce a distribution that is similarly assessed as being power law. In contrast, the global lability of synchronisation measure is shown to better discriminate critical from non critical interaction.Comment: (v3) Fixed error in Figure 1; (v2) Added references. Minor edits throughout. Clarified relationship between theoretical critical coupling for infinite size system and 'effective' critical coupling system for finite size system. Improved presentation and discussion of results; results unchanged. Revised Figure 1 to include error bars on r and N; results unchanged; (v1) 11 pages, 7 figure

Ultrafast rerouting of light via slow modes in a nanophotonic directional coupler

We demonstrate that two coupled photonic-crystal waveguides can route two subsequently arriving light pulses to different output ports even though the pulses are only 3 ps apart. This rerouting of light is due to an ultrafast shift in the transmittance spectrum triggered by the generation of electrons and holes in the Si base material by a femtosecond laser pulse. The use of slow-light modes allows for a coupler length of only 5.2 μm. Since these modes are not directly involved, the 3 ps dead time is solely determined by the duration of the input pulse rather than its transit time through the device.We acknowledge funding through the EU FP6-FET “SPLASH” project. This work is also part of the research program of FOM, which is financially supported by the NWO

Stochastic cellular automata model of neural networks

We propose a stochastic dynamical model of noisy neural networks with complex architectures and discuss activation of neural networks by a stimulus, pacemakers and spontaneous activity. This model has a complex phase diagram with self-organized active neural states, hybrid phase transitions, and a rich array of behavior. We show that if spontaneous activity (noise) reaches a threshold level then global neural oscillations emerge. Stochastic resonance is a precursor of this dynamical phase transition. These oscillations are an intrinsic property of even small groups of 50 neurons.Comment: 10 pages, 5 figure

Fourier space imaging of light localization at a photonic band-edge located below the light cone

We observe light localization in a two-dimensional geometry, induced by residual disorder at a photonic band edge located below the light cone. The combination of a spectrally selective illumination and a grating assisted k-space imaging technique allows us to image the equifrequency surfaces associated with such a photonic band, with high accuracy and without aberrations. Thanks to this approach, the impact of the nonideal nature of real planar photonic crystals on the propagation properties of the Bloch wave at the band edge is decorrelated from the contribution of the intrinsic out-of-plane losses. As a by-product, our result demonstrates an immersion free effective numerical aperture as high as 3.5 in k space

Circulating tumour DNA detects somatic variants contributing to spatial and temporal intratumural heterogeneity in head and neck squamous cell carcinoma

Background: As circulating tumour DNA (ctDNA) liquid biopsy analysis is increasingly incorporated into modern oncological practice, establishing the impact of genomic intra-tumoural heterogeneity (ITH) upon data output is paramount. Despite advances in other cancer types the evidence base in head and neck squamous cell carcinoma (HNSCC) remains poor. We sought to investigate the utility of ctDNA to detect ITH in HNSCC.Methods: In a pilot cohort of 9 treatment-naïve HNSCC patients, DNA from two intra-tumoural sites (core and margin) was whole-exome sequenced. A 9-gene panel was designed to perform targeted sequencing on pre-treatment plasma cell-free DNA and selected post-treatment samples.Results: Rates of genomic ITH among the 9 patients was high. COSMIC variants from 19 TCGA HNSCC genes demonstrated an 86.9% heterogeneity rate (present in one tumour sub-site only). Across all patients, cell-free DNA (ctDNA) identified 12.9% (range 7.5-19.8%) of tumour-specific variants, of which 55.6% were specific to a single tumour sub-site only. CtDNA identified 79.0% (range: 55.6-90.9%) of high-frequency variants (tumour VAF>5%). Analysis of ctDNA in serial post-treatment blood samples in patients who suffered recurrence demonstrated dynamic changes in both tumour-specific and acquired variants that predicted recurrence ahead of clinical detection.Conclusion: We demonstrate that a ctDNA liquid biopsy identified spatial genomic ITH in HNSCC and reliably detected high-frequency driver mutations. Serial sampling allowed post-treatment surveillance and early identification of treatment failure

Involvement of the Gut Microbiome in the Local and Systemic Immune Response to Pancreatic Ductal Adenocarcinoma

Simple Summary: One of the reasons that pancreatic cancer is such a deadly disease is that it is able to evade the body’s usual defence system (the immune system). It has been shown that the population of microorganisms in the human gut (the gut microbiome) plays a role in regulating the human immune system. This article outlines the ways in which the gut microbiome influences the immune system in pancreatic cancer both within the bloodstream (systemic) and around the pancreatic tumour itself (local). These are important mechanisms because greater understanding of these will direct the development of future treatments for pancreatic cancer. It is possible that some of these treatment options will target the gut microbiome in order to boost the immune system’s response to pancreatic cancer. Abstract: The systemic and local immunosuppression exhibited by pancreatic ductal adenocarcinoma (PDAC) contributes significantly to its aggressive nature. There is a need for a greater understanding of the mechanisms behind this profound immune evasion, which makes it one of the most challenging malignancies to treat and thus one of the leading causes of cancer death worldwide. The gut microbiome is now thought to be the largest immune organ in the body and has been shown to play an important role in multiple immune-mediated diseases. By summarizing the current literature, this review examines the mechanisms by which the gut microbiome may modulate the immune response to PDAC. Evidence suggests that the gut microbiome can alter immune cell populations both in the peripheral blood and within the tumour itself in PDAC patients. In addition, evidence suggests that the gut microbiome influences the composition of the PDAC tumour microbiome, which exerts a local effect on PDAC tumour immune infiltration. Put together, this promotes the gut microbiome as a promising route for future therapies to improve immune responses in PDAC patients

Point-occurrence self-similarity in crackling-noise systems and in other complex systems

It has been recently found that a number of systems displaying crackling noise also show a remarkable behavior regarding the temporal occurrence of successive events versus their size: a scaling law for the probability distributions of waiting times as a function of a minimum size is fulfilled, signaling the existence on those systems of self-similarity in time-size. This property is also present in some non-crackling systems. Here, the uncommon character of the scaling law is illustrated with simple marked renewal processes, built by definition with no correlations. Whereas processes with a finite mean waiting time do not fulfill a scaling law in general and tend towards a Poisson process in the limit of very high sizes, processes without a finite mean tend to another class of distributions, characterized by double power-law waiting-time densities. This is somehow reminiscent of the generalized central limit theorem. A model with short-range correlations is not able to escape from the attraction of those limit distributions. A discussion on open problems in the modeling of these properties is provided.Comment: Submitted to J. Stat. Mech. for the proceedings of UPON 2008 (Lyon), topic: crackling nois