Extent of resection in glioblastoma - variation between molecular risk groups in rtog-0525

Whether maximal surgical resection of glioblastoma improves patient survival has been controversial, as it is difficult to perform an unbiased assessment of extent of resection (EOR) independent of other patient-specific prognostic factors. Recently, glioblastoma has been sub-classified into 4 distinct molecular risk groups (RGs), which have been validated as prognostic biomarkers in the randomized clinical trial of temozolomide dosing in glioblastoma: the Radiation Therapy Oncology Group 0525 (RTOG-0525) trial. We sought to perform exploratory analyses examining gross total resection (GTR) versus sub-total resection (STR) within these RGs in RTOG-0525 patients. Across all randomized patients, n ¼ 354 had STR and n ¼ 450 had GTR as determined by neurosurgeon operative report. GTR was not significantly associated with survival across the overall study group. A total of 725 patients had sufficient tissue for determination of molecular RG. There were no significant differences in percentage of GTR between each of the 4 RGs (P ¼ 0.64). In exploratory subgroup analyses, GTR was associated with improved survival only for patients with tumors from RG4. Hazard ratios (95% confidence intervals) were 0.52 (0.08-2.07) for RG1 (n ¼ 28, 68% GTR), 1.74 (0.75-4.05) for RG2 (n ¼ 39, 56% GTR), 1.09 (0.84-1.42) for RG3 (n ¼ 284, 56% GTR), and 1.26 (1.01-1.56) for RG4 (n ¼ 374, 55% GTR). In univariate analysis within RG4, GTR was associated with a median survival of 14.6 months vs 12.7 months for STR (P ¼ 0.0352. In a Cox model adjusting for age, KPS, and neurologic function (NF), surgery remained an independent factor within RG4: GTR (P ¼ 0.0331), age (P ¼ 0.0014), KPS (P ¼ .3289), and NF (P ¼ 0.3804). There are important cautions in the interpretation of these data, including lack of MRI confirmation of EOR, and inclusion of a range of STR (from biopsy to near-total resection). However, these exploratory results raise the possibility that upfront characterization of tumor molecular profile may allow for personalized therapeutic strategies to improve outcomes for patients with glioblastoma.

Trade, Extent of the Market, and Economic Growth 1960-1996

We find that trade and domestic market size are robust determinants of economic growth over the 1960-1996 period when trade openness is measured as the US dollar value of imports and exports relative to GDP in PPP US$ ('real openness'). When trade openness is measured as the US dollar value of imports and exports relative to GDP in exchange rate US$ ('nominal openness') however, trade and the size of domestic markets are often non-robust determinants of growth. We argue that real openness is the more appropriate measure of trade and that our empirical results should be seen as evidence in favor of the extent-of-the-market hypothesis.

Auditory motion affects visual biological motion processing.

The processing of biological motion is a critical, everyday task performed with remarkable efficiency by human sensory systems. Interest in this ability has focused to a large extent on biological motion processing in the visual modality (see, for example, Cutting, J. E., Moore, C., & Morrison, R. (1988). Masking the motions of human gait. Perception and Psychophysics, 44(4), 339-347). In naturalistic settings, however, it is often the case that biological motion is defined by input to more than one sensory modality. For this reason, here in a series of experiments we investigate behavioural correlates of multisensory, in particular audiovisual, integration in the processing of biological motion cues. More specifically, using a new psychophysical paradigm we investigate the effect of suprathreshold auditory motion on perceptions of visually defined biological motion. Unlike data from previous studies investigating audiovisual integration in linear motion processing [Meyer, G. F. & Wuerger, S. M. (2001). Cross-modal integration of auditory and visual motion signals. Neuroreport, 12(11), 2557-2560; Wuerger, S. M., Hofbauer, M., & Meyer, G. F. (2003). The integration of auditory and motion signals at threshold. Perception and Psychophysics, 65(8), 1188-1196; Alais, D. & Burr, D. (2004). No direction-specific bimodal facilitation for audiovisual motion detection. Cognitive Brain Research, 19, 185-194], we report the existence of direction-selective effects: relative to control (stationary) auditory conditions, auditory motion in the same direction as the visually defined biological motion target increased its detectability, whereas auditory motion in the opposite direction had the inverse effect. Our data suggest these effects do not arise through general shifts in visuo-spatial attention, but instead are a consequence of motion-sensitive, direction-tuned integration mechanisms that are, if not unique to biological visual motion, at least not common to all types of visual motion. Based on these data and evidence from neurophysiological and neuroimaging studies we discuss the neural mechanisms likely to underlie this effect.

Organizing principles across the senses

ABSTRACT This thesis is composed of two main parts. The first addressed the question of whether the auditory and somatosensory systems, like their visual counterpart, comprise parallel functional pathways for processing identity and spatial attributes (so-called `what' and `where' pathways, respectively). The second part examined the independence of control processes mediating task switching across 'what' and `where' pathways in the auditory and visual modalities. Concerning the first part, electrical neuroimaging of event-related potentials identified the spatio-temporal mechanisms subserving auditory (see Appendix, Study n°1) and vibrotactile (see Appendix, Study n°2) processing during two types of blocks of trials. `What' blocks varied stimuli in their frequency independently of their location.. `Where' blocks varied the same stimuli in their location independently of their frequency. Concerning the second part (see Appendix, Study n°3), a psychophysical task-switching paradigm was used to investigate the hypothesis that the efficacy of control processes depends on the extent of overlap between the neural circuitry mediating the different tasks at hand, such that more effective task preparation (and by extension smaller switch costs) is achieved when the anatomical/functional overlap of this circuitry is small. Performance costs associated with switching tasks and/or switching sensory modalities were measured. Tasks required the analysis of either the identity or spatial location of environmental objects (`what' and `where' tasks, respectively) that were presented either visually or acoustically on any given trial. Pretrial cues informed participants of the upcoming task, but not of the sensory modality. - In the audio-visual domain, the results showed that switch costs between tasks were significantly smaller when the sensory modality of the task switched versus when it repeated. In addition, switch costs between the senses were correlated only when the sensory modality of the task repeated across trials and not when it switched. The collective evidence not only supports the independence of control processes mediating task switching and modality switching, but also the hypothesis that switch costs reflect competitive interterence between neural circuits that in turn can be diminished when these neural circuits are distinct. - In the auditory and somatosensory domains, the findings show that a segregation of location vs. recognition information is observed across sensory systems and that these happen around 100ms for both sensory modalities. - Also, our results show that functionally specialized pathways for audition and somatosensation involve largely overlapping brain regions, i.e. posterior superior and middle temporal cortices and inferior parietal areas. Both these properties (synchrony of differential processing and overlapping brain regions) probably optimize the relationships across sensory modalities. - Therefore, these results may be indicative of a computationally advantageous organization for processing spatial anal identity information.

GeoKernels: Modeling of Spatial Data on GeoManifolds

This paper presents a review of methodology for semi-supervised modeling with kernel methods, when the manifold assumption is guaranteed to be satisfied. It concerns environmental data modeling on natural manifolds, such as complex topographies of the mountainous regions, where environmental processes are highly influenced by the relief. These relations, possibly regionalized and nonlinear, can be modeled from data with machine learning using the digital elevation models in semi-supervised kernel methods. The range of the tools and methodological issues discussed in the study includes feature selection and semisupervised Support Vector algorithms. The real case study devoted to data-driven modeling of meteorological fields illustrates the discussed approach.

BME-based uncertainty assessment of the Chernobyl fallout

The vast territories that have been radioactively contaminated during the 1986 Chernobyl accident provide a substantial data set of radioactive monitoring data, which can be used for the verification and testing of the different spatial estimation (prediction) methods involved in risk assessment studies. Using the Chernobyl data set for such a purpose is motivated by its heterogeneous spatial structure (the data are characterized by large-scale correlations, short-scale variability, spotty features, etc.). The present work is concerned with the application of the Bayesian Maximum Entropy (BME) method to estimate the extent and the magnitude of the radioactive soil contamination by 137Cs due to the Chernobyl fallout. The powerful BME method allows rigorous incorporation of a wide variety of knowledge bases into the spatial estimation procedure leading to informative contamination maps. Exact measurements (?hard? data) are combined with secondary information on local uncertainties (treated as ?soft? data) to generate science-based uncertainty assessment of soil contamination estimates at unsampled locations. BME describes uncertainty in terms of the posterior probability distributions generated across space, whereas no assumption about the underlying distribution is made and non-linear estimators are automatically incorporated. Traditional estimation variances based on the assumption of an underlying Gaussian distribution (analogous, e.g., to the kriging variance) can be derived as a special case of the BME uncertainty analysis. The BME estimates obtained using hard and soft data are compared with the BME estimates obtained using only hard data. The comparison involves both the accuracy of the estimation maps using the exact data and the assessment of the associated uncertainty using repeated measurements. Furthermore, a comparison of the spatial estimation accuracy obtained by the two methods was carried out using a validation data set of hard data. Finally, a separate uncertainty analysis was conducted that evaluated the ability of the posterior probabilities to reproduce the distribution of the raw repeated measurements available in certain populated sites. The analysis provides an illustration of the improvement in mapping accuracy obtained by adding soft data to the existing hard data and, in general, demonstrates that the BME method performs well both in terms of estimation accuracy as well as in terms estimation error assessment, which are both useful features for the Chernobyl fallout study.

Biotic and abiotic variables show little redundancy in explaining tree species distributions

Abiotic factors such as climate and soil determine the species fundamental niche, which is further constrained by biotic interactions such as interspecific competition. To parameterize this realized niche, species distribution models (SDMs) most often relate species occurrence data to abiotic variables, but few SDM studies include biotic predictors to help explain species distributions. Therefore, most predictions of species distributions under future climates assume implicitly that biotic interactions remain constant or exert only minor influence on large-scale spatial distributions, which is also largely expected for species with high competitive ability. We examined the extent to which variance explained by SDMs can be attributed to abiotic or biotic predictors and how this depends on species traits. We fit generalized linear models for 11 common tree species in Switzerland using three different sets of predictor variables: biotic, abiotic, and the combination of both sets. We used variance partitioning to estimate the proportion of the variance explained by biotic and abiotic predictors, jointly and independently. Inclusion of biotic predictors improved the SDMs substantially. The joint contribution of biotic and abiotic predictors to explained deviance was relatively small (similar to 9%) compared to the contribution of each predictor set individually (similar to 20% each), indicating that the additional information on the realized niche brought by adding other species as predictors was largely independent of the abiotic (topo-climatic) predictors. The influence of biotic predictors was relatively high for species preferably growing under low disturbance and low abiotic stress, species with long seed dispersal distances, species with high shade tolerance as juveniles and adults, and species that occur frequently and are dominant across the landscape. The influence of biotic variables on SDM performance indicates that community composition and other local biotic factors or abiotic processes not included in the abiotic predictors strongly influence prediction of species distributions. Improved prediction of species' potential distributions in future climates and communities may assist strategies for sustainable forest management.

Effects of pro-cholinergic treatment in patients suffering from spatial neglect.

Spatial neglect is a neurological condition characterized by a breakdown of spatial cognition contralateral to hemispheric damage. Deficits in spatial attention toward the contralesional side are considered to be central to this syndrome. Brain lesions typically involve right fronto-parietal cortices mediating attentional functions and subcortical connections in underlying white matter. Convergent findings from neuroimaging and behavioral studies in both animals and humans suggest that the cholinergic system might also be critically implicated in selective attention by modulating cortical function via widespread projections from the basal forebrain. Here we asked whether deficits in spatial attention associated with neglect could partly result from a cholinergic deafferentation of cortical areas subserving attentional functions, and whether such disturbances could be alleviated by pro-cholinergic therapy. We examined the effect of a single-dose transdermal nicotine treatment on spatial neglect in 10 stroke patients in a double-blind placebo-controlled protocol, using a standardized battery of neglect tests. Nicotine-induced systematic improvement on cancellation tasks and facilitated orienting to single visual targets, but had no significant effect on other tests. These results support a global effect of nicotine on attention and arousal, but no effect on other spatial mechanisms impaired in neglect.

Dispersal strategies, few dominating or many coexisting: the effect of environmental spatial structure and multiple sources of mortality.

Interspecific competition, life history traits, environmental heterogeneity and spatial structure as well as disturbance are known to impact the successful dispersal strategies in metacommunities. However, studies on the direction of impact of those factors on dispersal have yielded contradictory results and often considered only few competing dispersal strategies at the same time. We used a unifying modeling approach to contrast the combined effects of species traits (adult survival, specialization), environmental heterogeneity and structure (spatial autocorrelation, habitat availability) and disturbance on the selected, maintained and coexisting dispersal strategies in heterogeneous metacommunities. Using a negative exponential dispersal kernel, we allowed for variation of both species dispersal distance and dispersal rate. We showed that strong disturbance promotes species with high dispersal abilities, while low local adult survival and habitat availability select against them. Spatial autocorrelation favors species with higher dispersal ability when adult survival and disturbance rate are low, and selects against them in the opposite situation. Interestingly, several dispersal strategies coexist when disturbance and adult survival act in opposition, as for example when strong disturbance regime favors species with high dispersal abilities while low adult survival selects species with low dispersal. Our results unify apparently contradictory previous results and demonstrate that spatial structure, disturbance and adult survival determine the success and diversity of coexisting dispersal strategies in competing metacommunities.

Spatial pattern of floral morphology: a possible insight into the effects of pollinators on plant distribution

Pollination syndromes involve convergent evolution towards phenotypes composed of specific scents, colours or floral morphologies that attract or restrict pollinator access to reward. How these traits might influence the distributions of plant species in interaction with pollinators has rarely been investigated. We sampled 870 vegetation plots in the western Swiss Alps and classified the plant species into seven blossom types according to their floral morphology (wind, disk, funnel, tube, bilabiate, head or brush). We investigated the environmental features of plots with functional diversity (FD) lower than expected by chance alone to detect potential pollination filtering and related the proportions of the seven blossom types to a combination of environmental descriptors. From these results, we inferred the potential effect of the pollinator on the spatial distribution of plant species. The vegetation plots with significantly lower FD of blossom types than expected by chance were found at higher altitudes, and the proportions of blossom types were strongly patterned along the same gradient. These results support a biotic filtering effect on plant species assemblages through pollination: disk blossoms became dominant at higher altitudes, resulting in a lower FD. In harsh conditions at high altitudes, pollinators usually decrease in activity, and the openness of the disk blossom grants access to any available pollinator. Inversely, bilabiate blossoms, which are mostly pollinated by bees, were more abundant at lower elevations, which are characterised by greater abundance and diversity of bees. Generalisation through openness of the blossom could be advantageous at high elevations, while specialisation could be a successful alternative strategy at lower elevations. The approach used in this study is purely correlative, and further investigations should be conducted to infer the nature of the causal relationship between plant and pollinator distributions.

Testing Spatial Autocorrelation in Weighted Networks : the Modes Permutation Test

In a weighted spatial network, as specified by an exchange matrix, the variances of the spatial values are inversely proportional to the size of the regions. Spatial values are no more exchangeable under independence, thus weakening the rationale for ordinary permutation and bootstrap tests of spatial autocorrelation. We propose an alternative permutation test for spatial autocorrelation, based upon exchangeable spatial modes, constructed as linear orthogonal combinations of spatial values. The coefficients obtain as eigenvectors of the standardised exchange matrix appearing in spectral clustering, and generalise to the weighted case the concept of spatial filtering for connectivity matrices. Also, two proposals aimed at transforming an acessibility matrix into a exchange matrix with with a priori fixed margins are presented. Two examples (inter-regional migratory flows and binary adjacency networks) illustrate the formalism, rooted in the theory of spectral decomposition for reversible Markov chains.

Combined analysis of grey matter voxel-based morphometry and white matter tract-based spatial statistics in late-life bipolar disorder.

Background: Previous magnetic resonance imaging (MRI) studies in young patients with bipolar disorder indicated the presence of grey matter concentration changes as well as microstructural alterations in white matter in various neocortical areas and the corpus callosum. Whether these structural changes are also present in elderly patients with bipolar disorder with long-lasting clinical evolution remains unclear. Methods: We performed a prospective MRI study of consecutive elderly, euthymic patients with bipolar disorder and healthy, elderly controls. We conducted a voxel-based morphometry (VBM) analysis and a tract-based spatial statistics (TBSS) analysis to assess fractional anisotropy and longitudinal, radial and mean diffusivity derived by diffusion tensor imaging (DTI). Results: We included 19 patients with bipolar disorder and 47 controls in our study. Fractional anisotropy was the most sensitive DTI marker and decreased significantly in the ventral part of the corpus callosum in patients with bipolar disorder. Longitudinal, radial and mean diffusivity showed no significant between-group differences. Grey matter concentration was reduced in patients with bipolar disorder in the right anterior insula, head of the caudate nucleus, nucleus accumbens, ventral putamen and frontal orbital cortex. Conversely, there was no grey matter concentration or fractional anisotropy increase in any brain region in patients with bipolar disorder compared with controls. Limitations: The major limitation of our study is the small number of patients with bipolar disorder. Conclusion: Our data document the concomitant presence of grey matter concentration decreases in the anterior limbic areas and the reduced fibre tract coherence in the corpus callosum of elderly patients with long-lasting bipolar disorder.

Technology diffusion and the spatial distribution of wages in the US

What explains the spatial distribution of wages across US counties? I find that two of the most important factors are spatial technology diffusion and externalities due to the aggregate scale of production. One empirical finding supporting the importance of spatial technology diffusion is that average wages in a county decrease with the average level of schooling in neighboring counties when employment in the county and average wages in neighboring counties are held constant. All empirical results are obtained using anovel instrument for (endogenous) employment at the county-leveland take into account other factors (e.g. productivity-differencesacross states, climate) that may determine wages.