Bistability and regular spatial patterns in arid ecosystems.

A variety of patterns observed in ecosystems can be explained by resource–concentration mechanisms. A resource–concentration mechanism occurs when organisms increase the lateral flow of a resource toward them, leading to a local concentration of this resource and to its depletion from areas farther away. In resource–concentration systems, it has been proposed that certain spatial patterns could indicate proximity to discontinuous transitions where an ecosystem abruptly shifts from one stable state to another. Here, we test this hypothesis using a model of vegetation dynamics in arid ecosystems. In this model, a resource– concentration mechanism drives a positive feedback between vegetation and soil water availability. We derived the conditions leading to bistability and pattern formation. Our analysis revealed that bistability and regular pattern formation are linked in our model. This means that, when regular vegetation patterns occur, they indicate that the system is along a discontinuous transition to desertification. Yet, in real systems, only observing regular vegetation patterns without identifying the pattern-driving mechanism might not be enough to conclude that an ecosystem is along a discontinuous transition because similar patterns can emerge from different ecological mechanisms

Nutrients and Hydrology Indicate the Driving Mechanisms of Peatland Surface Patterning

Peatland surface patterning motivates studies that identify underlying structuring mechanisms. Theoretical studies so far suggest that different mechanisms may drive similar types of patterning. The long time span associated with peatland surface pattern formation, however, limits possibilities for empirically testing model predictions by field manipulations. Here, we present a model that describes spatial interactions between vegetation, nutrients, hydrology, and peat. We used this model to study pattern formation as driven by three different mechanisms: peat accumulation, water ponding, and nutrient accumulation. By on-and-off switching of each mechanism, we created a full-factorial design to see how these mechanisms affected surface patterning (pattern of vegetation and peat height) and underlying patterns in nutrients and hydrology. Results revealed that different combinations of structuring mechanisms lead to similar types of peatland surface patterning but contrasting underlying patterns in nutrients and hydrology. These contrasting underlying patterns suggest that the presence or absence of the structuring mechanisms can be identified by relatively simple short-term field measurements of nutrients and hydrology, meaning that longer-term field manipulations can be circumvented. Therefore, this study provides promising avenues for future empirical studies on peatland patternin

Brain Activation by Visual Food-Related Stimuli and Correlations with Metabolic and Hormonal Parameters: A fMRI Study

Regional brain activity in 15 healthy, normal weight males during processing of visual food stimuli in a satiated and a hungry state was examined and correlated with neuroendocrine factors known to be involved in hunger and satiated states. Two functional Magnetic Resonance Imaging (fMRI) sessions were performed with a one week interval, after overnight fasting or 1 hour after a standardized meal. Blood samples and appetite assessment were obtained after each fMRI session. Main effects of processing food versus non-food stimuli were observed in the ventral visual stream, including the fusiform gyrus and hippocampal areas bilaterally, significantly more in the fasting state. Leptin concentration correlated negatively with activity in the left hippocampal area and right insula during the satiation condition. A positive correlation between ghrelin and "thought of food" hunger scores were found. The positive correlation between ghrelin and food related activation in the insula areas and the right hippocampus during fasting did not reach significance. Conclusion: The increased activation of food vs non-food pictures in the ventral visual stream reflects increased salience of food pictures when subjects are hungry. Leptin was associated with activations in areas involved in processing of new information and emotion. © Jakobsdottir et al

Measuring decline in white matter integrity after systemic treatment for breast cancer:Omitting skeletonization enhances sensitivity

Chemotherapy for non-central nervous system cancers is associated with abnormalities in brain structure and function. Diffusion tensor imaging (DTI) allows for studying in vivo microstructural changes in brain white matter. Tract-based spatial statistics (TBSS) is a widely used processing pipeline in which DTI data are typically normalized to a generic DTI template and then ‘skeletonized’ to compensate for misregistration effects. However, this approach greatly reduces the overall white matter volume that is subjected to statistical analysis, leading to information loss. Here, we present a re-analysis of longitudinal data previously analyzed with standard TBSS (Menning et al., BIB 2018, 324–334). For our current approach, we constructed a pipeline with an optimized registration method in Advanced Normalization Tools (ANTs) where DTI data are registered to a study-specific, high-resolution T1 template and the skeletonization step is omitted. In a head to head comparison, we show that with our novel approach breast cancer survivors who had received chemotherapy plus or minus endocrine therapy (BC + SYST, n = 26) showed a global decline in overall FA that was not present in breast cancer survivors who did not receive systemic therapy (BC-SYST, n = 23) or women without a cancer diagnosis (no cancer controls, NC, n = 30). With the standard TBSS approach we did not find any group differences. Moreover, voxel-based analysis for our novel pipeline showed a widespread decline in FA in the BC + SYST compared to the NC group. Interestingly, the BC-SYST group also showed a decline in FA compared to the NC group, although in much less voxels. These results were not found with the standard TBSS approach. We demonstrate that a modified processing pipeline makes DTI data more sensitive to detecting changes in white matter integrity in non-CNS cancer patients after treatment, particularly chemotherapy

Detecting inconsistent responding on the youth psychopathic traits inventory-short form

The Youth Psychopathic Traits Inventory-Short Form (YPI-S) is a convenient measure for assessing psychopathy in settings with constraints on resources. However, the YPI-S does not contain a means of detecting careless or random response styles. The present study describes the development and evaluation of an inconsistent responding scale for the YPI-S using five archival samples that vary in language (English, German, Italian, Dutch) and other participant characteristics (juvenile offenders, adolescent students). Inconsistency scores resulting from the new scale effectively distinguished genuine participant responses from randomly generated cases (area under the ROC curve [AUC] = .85-.90) and from cases in which 50% of original responses were replaced with random data (AUC = .75-.82). The associations between the YPI-S and theoretically relevant correlates were reduced among participants exceeding proposed cutoff scores for profile validity compared with associations among more consistent respondents