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Background: Stroke still has a high incidence with a tremendous public health burden and it is a leading cause of mortality and disability. However, biomarkers for early diagnosis are absent and the metabolic alterations associated with ischemic stroke are not clearly understood. The objectives of this case-control study are to identify serum biomarkers and explore the metabolic alterations of ischemic stroke. Methods: Metabonomic analysis was performed using ultra-performance liquid chromatography quadrupole time-of-flight tandem mass spectrometry and multivariate statistical analysis was employed to study 60 patients with or without ischemic stroke (30 cases and 30 controls). Results: Serum metabolic profiling identified a series of 12 metabolites with significant alterations, and the related metabolic pathways involved glycerophospholipid, sphingolipid, phospholipid, fat acid, acylcarnitine, heme, and purine metabolism. Subsequently, multiple logistic regression analyses of these metabolites showed uric acid, sphinganine and adrenoyl ethanolamide were potential biomarkers of ischemic stroke with an area under the receiver operating characteristic curve of 0.941. Conclusions: These findings provide insights into the early diagnosis and potential pathophysiology of ischemic stroke. [ABSTRACT FROM AUTHOR]

In this study we aim to examine how the implicit learning of statistical regularities of successive stimuli affects the ability to exert cognitive control. In three experiments, sequences of flanker stimuli were segregated into pairs, with the second stimulus contingent on the first. Response times were reliably faster for the second stimulus if its congruence tended to match the congruence of the preceding stimulus, even though most participants were not explicitly aware of the statistical regularities (Experiment 1). In contrast, performance was not enhanced if the congruence of the second stimuli tended to mismatch the congruence of the first stimulus (Experiment 2). The lack of improvement appears to result from a failure of learning mismatch contingencies (Experiment 3). The results suggest that implicit learning of inter-stimulus relationships can facilitate cognitive control. [ABSTRACT FROM AUTHOR]

Most real-world judgments and decisions require the consideration of multiple types of evidence. For example, judging the severity of environmental damage, medical illness, or negative economic trends often involves tracking and integrating evidence from multiple sources (i.e. different natural disasters, physical symptoms, or financial indicators). We hypothesized that the requirement to track and integrate across distinct types of evidence would affect severity judgments of multifaceted problems, compared to simpler problems. To test this, we used scenarios depicting crop damage. Each scenario involved either two event types (i.e. mold damage and insect damage), or one event type. Participants judged the quality of the crop following each scenario. In Experiments 1 and 2, subjective judgments were attenuated if the scenario depicted multiple event types, relative to scenarios depicting single event types. This was evident as a shallower slope of subjective severity ratings, as a function of objectively quantifiable severity, for scenarios with multiple event types. In Experiment 3, we asked whether alternation between event types might contribute to this attenuation. Each scenario contained two event types, and the sequence of events either alternated frequently between types or was organized into two sequential groups. Subjective judgments were attenuated for scenarios with frequently alternating sequences. The results demonstrate that alternation between distinct event types attenuates subjective judgments of severity. This suggests that a requirement to integrate evidence across multiple sources places extra demands on the cognitive system, which reduces the perceived evidence strength. [ABSTRACT FROM AUTHOR]

Conservation of biodiversity is determined in part by human preferences. Preferences relevant to conservation have been examined largely via explicit measures (e.g., a self-reported degree of liking), with implicit measures (e.g., preconscious, automatic evaluations) receiving relatively less attention. This is the case despite psychological evidence from other contexts that implicit preferences are more informative of behavior. Thus, the type of measure that predicts conservation intentions for biodiversity is unknown. We conducted three studies to examine conservation intentions in light of people’s explicit and implicit preferences toward four endangered species (sea otter, American badger, caribou, yellow-breasted chat) and four biomes (forest, ocean, grassland, tundra). In Study 1 (n = 55), we found that people implicitly preferred caribou most, but explicitly preferred sea otter most, with a significant multiple regression where participants’ explicit preferences dictated their stated intended donations for conservation of each species. In Study 2 (n = 57) we found that people implicitly and explicitly preferred forest and ocean over grassland and tundra. Explicit rather than implicit preferences predicted the intended donation for conservation of the ocean biome. Study 3 involved a broader online sample of participants (n = 463) and also found that explicit preferences dictated the intended donations for conservation of biomes and species. Our findings reveal discrepancies between implicit and explicit preferences toward species, but not toward biomes. Importantly, the results demonstrate that explicit rather than implicit preferences predict conservation intentions for biodiversity. The current findings have several implications for conservation and the communication of biodiversity initiatives. [ABSTRACT FROM AUTHOR]