Linking personality to cultural intelligence : an interactive effect of openness and agreeableness

The personality trait of openness is generally believed to influence an individual's cultural intelligence, which is an ability to deal effectively with people from different cultural backgrounds. This study examines whether a relationship between the two depends on the individual's degree of agreeableness, a personality trait important for building interpersonal relationships. Data collected from 244 international professionals shows that openness is positively related to three facets of cultural intelligence when agreeableness is high, but not when agreeableness is low. The findings suggest that research on personality and cultural intelligence would benefit from an interactive approach, and that assessment, selection and development of international talents should consider personality traits not in isolation, but in concert

Editorial for the special issue neurotrophic factors

Non peer reviewe

When do global leaders learn best to develop cultural intelligence? An investigation of the moderating role of experiential learning style

Cultural intelligence is believed to be an important quality for global leaders. To understand how this quality can be developed from international experience, our study employs experiential learning theory to analyze the learning process. We hypothesize that the extent to which the length of overseas work experience contributes to the development of cultural intelligence varies depending on the executives' learning styles. Analyses of data collected from 294 international executives and graduate business students in China and Ireland indicated that the positive relationship between the length of overseas experience and cultural intelligence is strengthened when global executives have a divergent learning style, not when they have an assimilative, convergent, or accommodative learning style

How Does Wildfire Risk Differ Across a Landscape Given Heterogeneous Development Patterns?

This study explores the variation in wildfire risk from different development patterns. The analysis tests how an assortment of variables within the fire risk framework are affected by differing lateral development types. The study area covered Bastrop and Travis counties located in Texas. Two time periods were used in the assessment, 2001 and 2012. Lateral development was categorized into five categories: infill, radial, isolated, clustered, and linear. Within the fire risk framework, fire severity, ignition probability, and burn probability were assessed for the study area. Maximum Entropy was used to spatially predict ignition probability. Burn probability and conditional flame length were simulated using the Minimum Travel Time algorithm. Ignition probability variation was assessed using a one-way ANOVA and post hoc analysis. Burn probability and conditional flame length analyses were more robust. One-way ANOVAs and post hoc analyses were used to differentiate variation among lateral development types. Generalized Methods of Moments were used to estimate changes in burn probability and conditional flame length across time. Finally, the simulation’s fire perimeters were analyzed for initiation and exposure using social network analysis techniques. Analyses found that outlying development patterns: isolated, clustered, linear, were at higher wild fire risk than infill and radial development. However, most simulated fires initiated nearest radial development. Being closer to a road increased the likelihood of ignition, but increases in road density decreased burn probability. Changes in fuel loading had a positive correlation with changes in conditional flame length and burn probability. The analysis suggests that increasing populations in the wildland-urban interface are increasing their risk. Policies that reduce the outlying development patterns will reduce risk for the community

Self-Calibrated Warping for Mass Spectra Alignment

With recent advances in mass spectrometry (MS) technologies, it is now possible to study protein profiles over a wide range of molecular weights in small biological specimens. However, MS spectra are usually not aligned or synchronized between samples. To ensure the consistency of the subsequent analysis, spectrum alignment is necessary to align the spectra such that the same biological entity would show up at the same m/z value for different samples. Although a variety of alignment algorithms have been proposed in the past, most of them are developed based on chromatographic data and do not address some of the unique characteristics of the serum or other body fluid MS data. In this work, we propose a self-calibrated warping (SCW) algorithm to address some of the challenges associated with serum MS data alignment. In addition, we compare the proposed algorithm with five existing representative alignment methods using a clinical surface enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF-MS) data set

Detailed evaluation of the upper airway in the Dp(16)1Yey mouse model of Down syndrome

A high prevalence of obstructive sleep apnea (OSA) has been reported in Down syndrome (DS) owing to the coexistence of multiple predisposing factors related to its genetic abnormality, posing a challenge for the management of OSA. We hypothesized that DS mice recapitulate craniofacial abnormalities and upper airway obstruction of human DS and can serve as an experimental platform for OSA research. This study, thus, aimed to quantitatively characterize the upper airway as well as craniofacial abnormalities in Dp(16)1Yey (Dp16) mice. Dp16 mice demonstrated craniofacial hypoplasia, especially in the ventral part of the skull and the mandible, and rostrally positioned hyoid. These changes were accompanied with a shorter length and smaller cross-sectional area of the upper airway, resulting in a significantly reduced upper airway volume in Dp16 mice. Our non-invasive approach, a combination of computational fluid dynamics and high-resolution micro-CT imaging, revealed a higher negative pressure inside the airway of Dp16 mice compared to wild-type littermates, showing the potential risk of upper airway collapse. Our study indicated that Dp16 mice can be a useful model to examine the pathophysiology of increased upper airway collapsibility of DS and to evaluate the efficacy of therapeutic interventions for breathing and sleep anomalies

A γ-secretase inhibitor, but not a γ-secretase modulator, induced defects in BDNF axonal trafficking and signaling: evidence for a role for APP.

Clues to Alzheimer disease (AD) pathogenesis come from a variety of different sources including studies of clinical and neuropathological features, biomarkers, genomics and animal and cellular models. An important role for amyloid precursor protein (APP) and its processing has emerged and considerable interest has been directed at the hypothesis that Aβ peptides induce changes central to pathogenesis. Accordingly, molecules that reduce the levels of Aβ peptides have been discovered such as γ-secretase inhibitors (GSIs) and modulators (GSMs). GSIs and GSMs reduce Aβ levels through very different mechanisms. However, GSIs, but not GSMs, markedly increase the levels of APP CTFs that are increasingly viewed as disrupting neuronal function. Here, we evaluated the effects of GSIs and GSMs on a number of neuronal phenotypes possibly relevant to their use in treatment of AD. We report that GSI disrupted retrograde axonal trafficking of brain-derived neurotrophic factor (BDNF), suppressed BDNF-induced downstream signaling pathways and induced changes in the distribution within neuronal processes of mitochondria and synaptic vesicles. In contrast, treatment with a novel class of GSMs had no significant effect on these measures. Since knockdown of APP by specific siRNA prevented GSI-induced changes in BDNF axonal trafficking and signaling, we concluded that GSI effects on APP processing were responsible, at least in part, for BDNF trafficking and signaling deficits. Our findings argue that with respect to anti-amyloid treatments, even an APP-specific GSI may have deleterious effects and GSMs may serve as a better alternative

The down syndrome biomarker initiative (DSBI) pilot: proof of concept for deep phenotyping of Alzheimer’s disease biomarkers in down syndrome

To gain further knowledge on the preclinical phase of AD, we sought to characterize cognitive performance, volumetric MRI, amyloid PET, FDG PET, retinal amyloid, and plasma biomarkers in a cohort of non-demented adults with Down Syndrome (DS). The goal of the Down Syndrome Biomarker Initiative (DSBI) pilot is to test feasibility of this approach for future multicenter studies. We enrolled 12 non-demented participants with DS between the ages of 30-60 years old. Participants underwent extensive cognitive testing, volumetric MRI, amyloid PET 18F-florbetapir, 18F-fluorodeoxyglucose (18F-FDG) PET, and retinal amyloid imaging. In addition, plasma beta-amyloid species were measured and ApoE genotyping was performed. Consistent with previous autopsy studies, subjects demonstrated amyloid PET positivity reflecting fibrillar amyloid plaque deposition. Results from our multimodal analysis also suggest greater hippocampal atrophy with amyloid load. Additionally, we identified an inverse relationship between amyloid load and regional glucose metabolism. Cognitive and functional measures did not correlate with amyloid load in DS but did correlate with regional FDG PET measures. Retinal amyloid imaging demonstrated presence of plaques. Biomarkers of AD can be readily studied in adults with DS as in other preclinical AD populations. Importantly, all subjects in this feasibility study were able to complete all test procedures. The data indicate that a large, multicenter longitudinal study is feasible to better understand the trajectories of AD biomarkers in this enriched population. This trial is registered with ClinicalTrials.gov, number NCT02141971

Pharmacological and Toxicological Properties of the Potent Oral γ-Secretase Modulator BPN-15606.

Alzheimer's disease (AD) is characterized neuropathologically by an abundance of 1) neuritic plaques, which are primarily composed of a fibrillar 42-amino-acid amyloid-β peptide (Aβ), as well as 2) neurofibrillary tangles composed of aggregates of hyperphosporylated tau. Elevations in the concentrations of the Aβ42 peptide in the brain, as a result of either increased production or decreased clearance, are postulated to initiate and drive the AD pathologic process. We initially introduced a novel class of bridged aromatics referred tγ-secretase modulatoro as γ-secretase modulators that inhibited the production of the Aβ42 peptide and to a lesser degree the Aβ40 peptide while concomitantly increasing the production of the carboxyl-truncated Aβ38 and Aβ37 peptides. These modulators potently lower Aβ42 levels without inhibiting the γ-secretase-mediated proteolysis of Notch or causing accumulation of carboxyl-terminal fragments of APP. In this study, we report a large number of pharmacological studies and early assessment of toxicology characterizing a highly potent γ-secretase modulator (GSM), (S)-N-(1-(4-fluorophenyl)ethyl)-6-(6-methoxy-5-(4-methyl-1H-imidazol-1-yl)pyridin-2-yl)-4-methylpyridazin-3-amine (BPN-15606). BPN-15606 displayed the ability to significantly lower Aβ42 levels in the central nervous system of rats and mice at doses as low as 5-10 mg/kg, significantly reduce Aβ neuritic plaque load in an AD transgenic mouse model, and significantly reduce levels of insoluble Aβ42 and pThr181 tau in a three-dimensional human neural cell culture model. Results from repeat-dose toxicity studies in rats and dose escalation/repeat-dose toxicity studies in nonhuman primates have designated this GSM for 28-day Investigational New Drug-enabling good laboratory practice studies and positioned it as a candidate for human clinical trials