Modulational instability in nonlocal nonlinear Kerr media

We study modulational instability (MI) of plane waves in nonlocal nonlinear Kerr media. For a focusing nonlinearity we show that, although the nonlocality tends to suppress MI, it can never remove it completely, irrespectively of the particular profile of the nonlocal response function. For a defocusing nonlinearity the stability properties depend sensitively on the response function profile: for a smooth profile (e.g., a Gaussian) plane waves are always stable, but MI may occur for a rectangular response. We also find that the reduced model for a weak nonlocality predicts MI in defocusing media for arbitrary response profiles, as long as the intensity exceeds a certain critical value. However, it appears that this regime of MI is beyond the validity of the reduced model, if it is to represent the weakly nonlocal limit of a general nonlocal nonlinearity, as in optics and the theory of Bose-Einstein condensates.Comment: 8 pages, submitted to Phys. Rev.

Modulational instability, solitons and beam propagation in spatially nonlocal nonlinear media

We present an overview of recent advances in the understanding of optical beams in nonlinear media with a spatially nonlocal nonlinear response. We discuss the impact of nonlocality on the modulational instability of plane waves, the collapse of finite-size beams, and the formation and interaction of spatial solitons.Comment: Review article, will be published in Journal of Optics B, special issue on Optical Solitons, 6 figure

Probabilistic Inference in General Graphical Models through Sampling in Stochastic Networks of Spiking Neurons

An important open problem of computational neuroscience is the generic organization of computations in networks of neurons in the brain. We show here through rigorous theoretical analysis that inherent stochastic features of spiking neurons, in combination with simple nonlinear computational operations in specific network motifs and dendritic arbors, enable networks of spiking neurons to carry out probabilistic inference through sampling in general graphical models. In particular, it enables them to carry out probabilistic inference in Bayesian networks with converging arrows (“explaining away”) and with undirected loops, that occur in many real-world tasks. Ubiquitous stochastic features of networks of spiking neurons, such as trial-to-trial variability and spontaneous activity, are necessary ingredients of the underlying computational organization. We demonstrate through computer simulations that this approach can be scaled up to neural emulations of probabilistic inference in fairly large graphical models, yielding some of the most complex computations that have been carried out so far in networks of spiking neurons

Rare variant analyses validate known ALS genes in a multi-ethnic population and identifies ANTXR2 as a candidate in PLS

BackgroundAmyotrophic lateral sclerosis (ALS) is a neurodegenerative disease affecting over 300,000 people worldwide. It is characterized by the progressive decline of the nervous system that leads to the weakening of muscles which impacts physical function. Approximately, 15% of individuals diagnosed with ALS have a known genetic variant that contributes to their disease. As therapies that slow or prevent symptoms continue to develop, such as antisense oligonucleotides, it is important to discover novel genes that could be targets for treatment. Additionally, as cohorts continue to grow, performing analyses in ALS subtypes, such as primary lateral sclerosis (PLS), becomes possible due to an increase in power. These analyses could highlight novel pathways in disease manifestation.MethodsBuilding on our previous discoveries using rare variant association analyses, we conducted rare variant burden testing on a substantially larger multi-ethnic cohort of 6,970 ALS patients, 166 PLS patients, and 22,524 controls. We used intolerant domain percentiles based on sub-region Residual Variation Intolerance Score (subRVIS) that have been described previously in conjunction with gene based collapsing approaches to conduct burden testing to identify genes that associate with ALS and PLS.ResultsA gene based collapsing model showed significant associations with SOD1, TARDBP, and TBK1 (OR = 19.18, p = 3.67 × 10–39; OR = 4.73, p = 2 × 10–10; OR = 2.3, p = 7.49 × 10–9, respectively). These genes have been previously associated with ALS. Additionally, a significant novel control enriched gene, ALKBH3 (p = 4.88 × 10–7), was protective for ALS in this model. An intolerant domain-based collapsing model showed a significant improvement in identifying regions in TARDBP that associated with ALS (OR = 10.08, p = 3.62 × 10–16). Our PLS protein truncating variant collapsing analysis demonstrated significant case enrichment in ANTXR2 (p = 8.38 × 10–6).ConclusionsIn a large multi-ethnic cohort of 6,970 ALS patients, collapsing analyses validated known ALS genes and identified a novel potentially protective gene, ALKBH3. A first-ever analysis in 166 patients with PLS found a candidate association with loss-of-function mutations in ANTXR2

Sensory Input Pathways and Mechanisms in Swallowing: A Review

Over the past 20 years, research on the physiology of swallowing has confirmed that the oropharyngeal swallowing process can be modulated, both volitionally and in response to different sensory stimuli. In this review we identify what is known regarding the sensory pathways and mechanisms that are now thought to influence swallowing motor control and evoke its response. By synthesizing the current state of research evidence and knowledge, we identify continuing gaps in our knowledge of these mechanisms and pose questions for future research

Blood pressure-lowering effects of nifedipine/candesartan combinations in high-risk individuals: Subgroup analysis of the DISTINCT randomised trial

The DISTINCT study (reDefining Intervention with Studies Testing Innovative Nifedipine GITS - Candesartan Therapy) investigated the efficacy and safety of nifedipine GITS/candesartan cilexetil combinations vs respective monotherapies and placebo in patients with hypertension. This descriptive sub-analysis examined blood pressure (BP)-lowering effects in high-risk participants, including those with renal impairment (estimated glomerular filtration rate<90 ml min-1, n=422), type 2 diabetes mellitus (n=202), hypercholesterolaemia (n=206) and cardiovascular (CV) risk factors (n=971), as well as the impact of gender, age and body mass index (BMI). Participants with grade I/II hypertension were randomised to treatment with nifedipine GITS (N) 20, 30, 60 mg and/or candesartan cilexetil (C) 4, 8, 16, 32 mg or placebo for 8 weeks. Mean systolic BP and diastolic BP reductions after treatment in high-risk participants were greater, overall, with N/C combinations vs respective monotherapies or placebo, with indicators of a dose-response effect. Highest rates of BP control (ESH/ESC 2013 guideline criteria) were also achieved with highest doses of N/C combinations in each high-risk subgroup. The benefits of combination therapy vs monotherapy were additionally observed in patient subgroups categorised by gender, age or BMI. All high-risk participants reported fewer vasodilatory adverse events in the pooled N/C combination therapy than the N monotherapy group. In conclusion, consistent with the DISTINCT main study outcomes, high-risk participants showed greater reductions in BP and higher control rates with N/C combinations compared with respective monotherapies and lesser vasodilatory side-effects compared with N monotherapy

Population Genomics of Parallel Adaptation in Threespine Stickleback using Sequenced RAD Tags

Next-generation sequencing technology provides novel opportunities for gathering genome-scale sequence data in natural populations, laying the empirical foundation for the evolving field of population genomics. Here we conducted a genome scan of nucleotide diversity and differentiation in natural populations of threespine stickleback (Gasterosteus aculeatus). We used Illumina-sequenced RAD tags to identify and type over 45,000 single nucleotide polymorphisms (SNPs) in each of 100 individuals from two oceanic and three freshwater populations. Overall estimates of genetic diversity and differentiation among populations confirm the biogeographic hypothesis that large panmictic oceanic populations have repeatedly given rise to phenotypically divergent freshwater populations. Genomic regions exhibiting signatures of both balancing and divergent selection were remarkably consistent across multiple, independently derived populations, indicating that replicate parallel phenotypic evolution in stickleback may be occurring through extensive, parallel genetic evolution at a genome-wide scale. Some of these genomic regions co-localize with previously identified QTL for stickleback phenotypic variation identified using laboratory mapping crosses. In addition, we have identified several novel regions showing parallel differentiation across independent populations. Annotation of these regions revealed numerous genes that are candidates for stickleback phenotypic evolution and will form the basis of future genetic analyses in this and other organisms. This study represents the first high-density SNP–based genome scan of genetic diversity and differentiation for populations of threespine stickleback in the wild. These data illustrate the complementary nature of laboratory crosses and population genomic scans by confirming the adaptive significance of previously identified genomic regions, elucidating the particular evolutionary and demographic history of such regions in natural populations, and identifying new genomic regions and candidate genes of evolutionary significance