Gastrin-induced miR-222 promotes gastric tumor development by suppressing p27kip1

Background and aims Elevated circulating concentrations of the hormone gastrin contribute to the development of gastric adenocarcinoma and types-1 and 2 gastric neuroendocrine tumors (NETs). MicroRNAs (miRNAs) are small non-coding RNAs that post-transcriptionally regulate proteins which in turn influence various biological processes. We hypothesised that gastrin induces the expression of specific gastric miRNAs within CCK2 receptor (CCK2R) expressing cells and that these mediate functionally important actions of gastrin.Results Gastrin increased miR-222 expression in AGSGR cells, with maximum changes observed at 10 nM G17 for 24 h. Signalling occurred via CCK2R and the PKC and PI3K pathways. miR-222 expression was increased in the serum and gastric corpus mucosa of hypergastrinemic INS-GAS mice and hypergastrinemic patients with autoimmune atrophic gastritis and type 1 gastric NETs; it decreased in patients following treatment with the CCK2R antagonist netazepide (YF476). Gastrin-induced miR-222 overexpression resulted in reduced expression and cytoplasmic mislocalisation of p27kip1, which in turn caused actin remodelling and increased migration in AGSGR cells. Materials and methods miRNA PCR arrays were used to identify changes in miRNA expression following G17 treatment of human gastric adenocarcinoma cells stably transfected with CCK2R (AGSGR). miR-222 was further investigated using primer assays and samples from hypergastrinemic mice and humans. Chemically synthesised mimics and inhibitors were used to assess cellular phenotypical changes associated with miR-222 dysregulation.Conclusions These data indicate a novel mechanism contributing to gastrin-associated gastric tumor development. miR-222 may also be a promising biomarker for monitoring gastrin induced premalignant changes in the stomach

Analysis of Population Structure: A Unifying Framework and Novel Methods Based on Sparse Factor Analysis

We consider the statistical analysis of population structure using genetic data. We show how the two most widely used approaches to modeling population structure, admixture-based models and principal components analysis (PCA), can be viewed within a single unifying framework of matrix factorization. Specifically, they can both be interpreted as approximating an observed genotype matrix by a product of two lower-rank matrices, but with different constraints or prior distributions on these lower-rank matrices. This opens the door to a large range of possible approaches to analyzing population structure, by considering other constraints or priors. In this paper, we introduce one such novel approach, based on sparse factor analysis (SFA). We investigate the effects of the different types of constraint in several real and simulated data sets. We find that SFA produces similar results to admixture-based models when the samples are descended from a few well-differentiated ancestral populations and can recapitulate the results of PCA when the population structure is more “continuous,” as in isolation-by-distance models

Potential climatic transitions with profound impact on Europe

We discuss potential transitions of six climatic subsystems with large-scale impact on Europe, sometimes denoted as tipping elements. These are the ice sheets on Greenland and West Antarctica, the Atlantic thermohaline circulation, Arctic sea ice, Alpine glaciers and northern hemisphere stratospheric ozone. Each system is represented by co-authors actively publishing in the corresponding field. For each subsystem we summarize the mechanism of a potential transition in a warmer climate along with its impact on Europe and assess the likelihood for such a transition based on published scientific literature. As a summary, the ‘tipping’ potential for each system is provided as a function of global mean temperature increase which required some subjective interpretation of scientific facts by the authors and should be considered as a snapshot of our current understanding. <br/

Reshaping of Bulbar Odor Response by Nasal Flow Rate in the Rat

The impact of respiratory dynamics on odor response has been poorly studied at the olfactory bulb level. However, it has been shown that sniffing in the behaving rodent is highly dynamic and varies both in frequency and flow rate. Bulbar odor response could vary with these sniffing parameter variations. Consequently, it is necessary to understand how nasal airflow can modify and shape odor response at the olfactory bulb level.To assess this question, we used a double cannulation and simulated nasal airflow protocol on anesthetized rats to uncouple nasal airflow from animal respiration. Both mitral/tufted cell extracellular unit activity and local field potentials (LFPs) were recorded. We found that airflow changes in the normal range were sufficient to substantially reorganize the response of the olfactory bulb. In particular, cellular odor-evoked activities, LFP oscillations and spike phase-locking to LFPs were strongly modified by nasal flow rate.Our results indicate the importance of reconsidering the notion of odor coding as odor response at the bulbar level is ceaselessly modified by respiratory dynamics

Prisoners in Their Habitat? Generalist Dispersal by Habitat Specialists: A Case Study in Southern Water Vole (Arvicola sapidus)

Habitat specialists inhabiting scarce and scattered habitat patches pose interesting questions related to dispersal such as how specialized terrestrial mammals do to colonize distant patches crossing hostile matrices. We assess dispersal patterns of the southern water vole (Arvicola sapidus), a habitat specialist whose habitat patches are distributed through less than 2% of the study area (overall 600 km2) and whose populations form a dynamic metapopulational network. We predict that individuals will require a high ability to move through the inhospitable matrix in order to avoid genetic and demographic isolations. Genotypes (N = 142) for 10 microsatellites and sequences of the whole mitochondrial Control Region (N = 47) from seven localities revealed a weak but significant genetic structure partially explained by geographic distance. None of the landscape models had a significant effect on genetic structure over that of the Euclidean distance alone and no evidence for efficient barriers to dispersal was found. Contemporary gene flow was not severely limited for A. sapidus as shown by high migration rates estimates (>10%) between non-neighbouring areas. Sex-biased dispersal tests did not support differences in dispersal rates, as shown by similar average axial parent-offspring distances, in close agreement with capture-mark-recapture estimates. As predicted, our results do not support any preferences of the species for specific landscape attributes on their dispersal pathways. Here, we combine field and molecular data to illustrate how a habitat specialist mammal might disperse like a habitat generalist, acquiring specific long-distance dispersal strategies as an adaptation to patchy, naturally fragmented, heterogeneous and unstable habitats

Power-Law Scaling in the Brain Surface Electric Potential

Recent studies have identified broadband phenomena in the electric potentials produced by the brain. We report the finding of power-law scaling in these signals using subdural electrocorticographic recordings from the surface of human cortex. The power spectral density (PSD) of the electric potential has the power-law form from 80 to 500 Hz. This scaling index, , is conserved across subjects, area in the cortex, and local neural activity levels. The shape of the PSD does not change with increases in local cortical activity, but the amplitude, , increases. We observe a “knee” in the spectra at , implying the existence of a characteristic time scale . Below , we explore two-power-law forms of the PSD, and demonstrate that there are activity-related fluctuations in the amplitude of a power-law process lying beneath the rhythms. Finally, we illustrate through simulation how, small-scale, simplified neuronal models could lead to these power-law observations. This suggests a new paradigm of non-oscillatory “asynchronous,” scale-free, changes in cortical potentials, corresponding to changes in mean population-averaged firing rate, to complement the prevalent “synchronous” rhythm-based paradigm

Enhanced Statistical Tests for GWAS in Admixed Populations: Assessment using African Americans from CARe and a Breast Cancer Consortium

While genome-wide association studies (GWAS) have primarily examined populations of European ancestry, more recent studies often involve additional populations, including admixed populations such as African Americans and Latinos. In admixed populations, linkage disequilibrium (LD) exists both at a fine scale in ancestral populations and at a coarse scale (admixture-LD) due to chromosomal segments of distinct ancestry. Disease association statistics in admixed populations have previously considered SNP association (LD mapping) or admixture association (mapping by admixture-LD), but not both. Here, we introduce a new statistical framework for combining SNP and admixture association in case-control studies, as well as methods for local ancestry-aware imputation. We illustrate the gain in statistical power achieved by these methods by analyzing data of 6,209 unrelated African Americans from the CARe project genotyped on the Affymetrix 6.0 chip, in conjunction with both simulated and real phenotypes, as well as by analyzing the FGFR2 locus using breast cancer GWAS data from 5,761 African-American women. We show that, at typed SNPs, our method yields an 8% increase in statistical power for finding disease risk loci compared to the power achieved by standard methods in case-control studies. At imputed SNPs, we observe an 11% increase in statistical power for mapping disease loci when our local ancestry-aware imputation framework and the new scoring statistic are jointly employed. Finally, we show that our method increases statistical power in regions harboring the causal SNP in the case when the causal SNP is untyped and cannot be imputed. Our methods and our publicly available software are broadly applicable to GWAS in admixed populations

Somatosensory System Deficits in Schizophrenia Revealed by MEG during a Median-Nerve Oddball Task

Although impairments related to somatosensory perception are common in schizophrenia, they have rarely been examined in functional imaging studies. In the present study, magnetoencephalography (MEG) was used to identify neural networks that support attention to somatosensory stimuli in healthy adults and abnormalities in these networks in patient with schizophrenia. A median-nerve oddball task was used to probe attention to somatosensory stimuli, and an advanced, high-resolution MEG source-imaging method was applied to assess activity throughout the brain. In nineteen healthy subjects, attention-related activation was seen in a sensorimotor network involving primary somatosensory (S1), secondary somatosensory (S2), primary motor (M1), pre-motor (PMA), and paracentral lobule (PCL) areas. A frontal–parietal–temporal “attention network”, containing dorsal- and ventral–lateral prefrontal cortex (DLPFC and VLPFC), orbitofrontal cortex (OFC), anterior cingulate cortex (ACC), superior parietal lobule (SPL), inferior parietal lobule (IPL)/supramarginal gyrus (SMG), and temporal lobe areas, was also activated. Seventeen individuals with schizophrenia showed early attention-related hyperactivations in S1 and M1 but hypo-activation in S1, S2, M1, and PMA at later latency in the sensorimotor network. Within this attention network, hypoactivation was found in SPL, DLPFC, orbitofrontal cortex, and the dorsal aspect of ACC. Hyperactivation was seen in SMG/IPL, frontal pole, and the ventral aspect of ACC in patients. These findings link attention-related somatosensory deficits to dysfunction in both sensorimotor and frontal–parietal–temporal networks in schizophrenia

Pan-cancer analysis of whole genomes

Cancer is driven by genetic change, and the advent of massively parallel sequencing has enabled systematic documentation of this variation at the whole-genome scale(1-3). Here we report the integrative analysis of 2,658 whole-cancer genomes and their matching normal tissues across 38 tumour types from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA). We describe the generation of the PCAWG resource, facilitated by international data sharing using compute clouds. On average, cancer genomes contained 4-5 driver mutations when combining coding and non-coding genomic elements; however, in around 5% of cases no drivers were identified, suggesting that cancer driver discovery is not yet complete. Chromothripsis, in which many clustered structural variants arise in a single catastrophic event, is frequently an early event in tumour evolution; in acral melanoma, for example, these events precede most somatic point mutations and affect several cancer-associated genes simultaneously. Cancers with abnormal telomere maintenance often originate from tissues with low replicative activity and show several mechanisms of preventing telomere attrition to critical levels. Common and rare germline variants affect patterns of somatic mutation, including point mutations, structural variants and somatic retrotransposition. A collection of papers from the PCAWG Consortium describes non-coding mutations that drive cancer beyond those in the TERT promoter(4); identifies new signatures of mutational processes that cause base substitutions, small insertions and deletions and structural variation(5,6); analyses timings and patterns of tumour evolution(7); describes the diverse transcriptional consequences of somatic mutation on splicing, expression levels, fusion genes and promoter activity(8,9); and evaluates a range of more-specialized features of cancer genomes(8,10-18).Peer reviewe