One Versus Two Handedness: Directional Preference in a Silent-Failure Scenario

This study focused on the direction drivers of a self-driving car will turn to avoid a crash at a T-intersection. We hypothesized that drivers would steer differently when they drive using both hands and when they use their dominant hand only. Specifically, we hypothesized that participants would favor the direction of their dominant hand (if they use their dominant hand only) and that there with be no directional preference if driving with both hands.. To test this hypothesis, we implemented a driving simulator study. We asked the participants to use either both their hands or only their dominant hand to avoid a crash. We are currently analyzing the data. Keywords: one-handed, two-handed, automated vehicle, silent takeover, directional preferenc

Detection of multidrug-resistant bacteria in the occupied Palestinian territory: a cross-sectional study

Background Antimicrobial resistance is a worldwide threat to public health. WHO has created several resolutions and strategies on this subject at the World Health Assembly. In May, 2015, WHO published a global action plan to mitigate antimicrobial resistance, including tracking and global surveillance focusing on improving awareness and understanding of this issue. The aim of this study was to screen for carbapenem-resistant bacteria in the occupied Palestinian Territory, to investigate the mechanisms behind the resistance, and to assess the scope of this difficulty in the area. Methods During 6 weeks in 2012, we collected all available Gram-negative isolates taken from inpatients and outpatients in hospital laboratories at Al-Shifa Hospital and five additional hospitals in the West Bank to screen for carbapenem resistance. Resistant isolates were identified with MALDI-TOF, mapped for their resistance pattern, and

Effects of Pycnogenol on endothelial function in patients with stable coronary artery disease: a double-blind, randomized, placebo-controlled, cross-over study

Aims Extracts from pine tree bark containing a variety of flavonoids have been used in traditional medicine. Pycnogenol is a proprietary bark extract of the French maritime pine tree (Pinus pinaster ssp. atlantica) that exerts antioxidative, anti-inflammatory, and anti-platelet effects. However, the effects of Pycnogenol on endothelial dysfunction, a precursor of atherosclerosis and cardiovascular events, remain still elusive. Methods and results Twenty-three patients with coronary artery disease (CAD) completed this randomized, double-blind, placebo-controlled cross-over study. Patients received Pycnogenol (200 mg/day) for 8 weeks followed by placebo or vice versa on top of standard cardiovascular therapy. Between the two treatment periods, a 2-week washout period was scheduled. At baseline and after each treatment period, endothelial function, non-invasively assessed by flow-mediated dilatation (FMD) of the brachial artery using high-resolution ultrasound, biomarkers of oxidative stress and inflammation, platelet adhesion, and 24 h blood pressure monitoring were evaluated. In CAD patients, Pycnogenol treatment was associated with an improvement of FMD from 5.3 ± 2.6 to 7.0 ± 3.1 (P < 0.0001), while no change was observed with placebo (5.4 ± 2.4 to 4.7 ± 2.0; P = 0.051). This difference between study groups was significant [estimated treatment effect 2.75; 95% confidence interval (CI): 1.75, 3.75, P < 0.0001]. 15-F2t-Isoprostane, an index of oxidative stress, significantly decreased from 0.71 ± 0.09 to 0.66 ± 0.13 after Pycnogenol treatment, while no change was observed in the placebo group (mean difference 0.06 pg/mL with an associated 95% CI (0.01, 0.11), P = 0.012]. Inflammation markers, platelet adhesion, and blood pressure did not change after treatment with Pycnogenol or placebo. Conclusion This study provides the first evidence that the antioxidant Pycnogenol improves endothelial function in patients with CAD by reducing oxidative stress. Clinical Trial Registration: ClinicalTrials.gov identifier: NCT0064175

Apolipoprotein E-dependent load of white matter hyperintensities in Alzheimer’s disease: a voxel-based lesion mapping study

Introduction: White matter (WM) magnetic resonance imaging (MRI) hyperintensities are common in Alzheimer’s disease (AD), but their pathophysiological relevance and relationship to genetic factors are unclear. In the present study, we investigated potential apolipoprotein E (APOE)-dependent effects on the extent and cognitive impact of WM hyperintensities in patients with AD. Methods: WM hyperintensity volume on fluid-attenuated inversion recovery images of 201 patients with AD (128 carriers and 73 non-carriers of the APOE ε4 risk allele) was determined globally as well as regionally with voxel-based lesion mapping. Clinical, neuropsychological and MRI data were collected from prospective multicenter trials conducted by the German Dementia Competence Network. Results: WM hyperintensity volume was significantly greater in non-carriers of the APOE ε4 allele. Lesion distribution was similar among ε4 carriers and non-carriers. Only ε4 non-carriers showed a correlation between lesion volume and cognitive performance. Conclusion: The current findings indicate an increased prevalence of WM hyperintensities in non-carriers compared with carriers of the APOE ε4 allele among patients with AD. This is consistent with a possibly more pronounced contribution of heterogeneous vascular risk factors to WM damage and cognitive impairment in patients with AD without APOE ε4-mediated risk

Memory Concerns, Memory Performance and Risk of Dementia in Patients with Mild Cognitive Impairment

Background: Concerns about worsening memory ("memory concerns"; MC) and impairment in memory performance are both predictors of Alzheimer's dementia (AD). The relationship of both in dementia prediction at the pre-dementia disease stage, however, is not well explored. Refined understanding of the contribution of both MC and memory performance in dementia prediction is crucial for defining at-risk populations. We examined the risk of incident AD by MC and memory performance in patients with mild cognitive impairment (MCI). Methods: We analyzed data of 417 MCI patients from a longitudinal multicenter observational study. Patients were classified based on presence (n=305) vs. absence (n=112) of MC. Risk of incident AD was estimated with Cox Proportional-Hazards regression models. Results: Risk of incident AD was increased by MC (HR=2.55, 95% CI: 1.33-4.89), lower memory performance (HR=0.63, 95% CI: 0.56-0.71) and ApoE4-genotype (HR=1.89, 95% CI: 1.18-3.02). An interaction effect between MC and memory performance was observed. The predictive power of MC was greatest for patients with very mild memory impairment and decreased with increasing memory impairment. Conclusions: Our data suggest that the power of MC as a predictor of future dementia at the MCI stage varies with the patients' level of cognitive impairment. While MC are predictive at early stage MCI, their predictive value at more advanced stages of MCI is reduced. This suggests that loss of insight related to AD may occur at the late stage of MCI

MIGHTEE-HI: The first MeerKAT HI mass function from an untargeted interferometric survey

We present the first measurement of the HI mass function (HIMF) using data from MeerKAT, based on 276 direct detections from the MIGHTEE Survey Early Science data covering a period of approximately a billion years ($0 \leq z \leq 0.084$). This is the first HIMF measured using interferometric data over non-group or cluster field, i.e. a deep blank field. We constrain the parameters of the Schechter function which describes the HIMF with two different methods: $1/\rm V_{\rm max}$ and Modified Maximum Likelihood (MML). We find a low-mass slope $\alpha=-1.29^{+0.37}_{-0.26}$, `knee' mass $\log_{10}(M_{*}/{\rm M_{\odot}}) = 10.07^{+0.24}_{-0.24}$ and normalisation $\log_{10}(\phi_{*}/\rm Mpc^{-3})=-2.34^{+0.32}_{-0.36}$ ($H_0 = 67.4$ kms$^{-1}$ Mpc$^{-1}$) for $1/\rm V_{\rm max}$ and $\alpha=-1.44^{+0.13}_{-0.10}$, `knee' mass $\log_{10}(M_{*}/{\rm M_{\odot}}) = 10.22^{+0.10}_{-0.13}$ and normalisation $\log_{10}(\phi_{*}/\rm Mpc^{-3})=-2.52^{+0.19}_{-0.14}$ for MML. When using $1/\rm V_{\rm max}$ we find both the low-mass slope and `knee' mass to be consistent within $1\sigma$ with previous studies based on single-dish surveys. The cosmological mass density of HI is found to be slightly larger than previously reported: $\Omega_{\rm HI}=5.46^{+0.94}_{-0.99} \times 10^{-4}h^{-1}_{67.4}$ from $1/\rm V_{\rm max}$ and $\Omega_{\rm HI}=6.31^{+0.31}_{-0.31} \times 10^{-4}h^{-1}_{67.4}$ from MML but consistent within the uncertainties. We find no evidence for evolution of the HIMF over the last billion years.Comment: 13 pages, 9 figures, accepted for publication in MNRA

Acute stress induces the rapid and transient induction of caspase-1, gasdermin D and release of constitutive IL-1 protein in dorsal hippocampus

The proinflammatory cytokine interleukin (IL)-1 plays a pivotal role in the behavioral manifestations (i.e., sickness) of the stress response. Indeed, exposure to acute and chronic stressors induces the expression of IL-1 in stress-sensitive brain regions. Thus, it is typically presumed that exposure to stressors induces the extracellular release of IL-1 in the brain parenchyma. However, this stress-evoked neuroimmune phenomenon has not been directly demonstrated nor has the cellular process of IL-1 release into the extracellular milieu been characterized in brain. This cellular process involves a form of inflammatory cell death, termed pyroptosis, which involves: 1) activation of caspase-1, 2) caspase-1 maturation of IL-1, 3) caspase-1 cleavage of gasdermin D (GSDMD), and 4) GSDMD-induced permeability of the cell membrane through which IL-1 is released into the extracellular space. Thus, the present study examined whether stress induces the extra-cellular release of IL-1 and engages the above cellular process in mediating IL-1 release in the brain. Male Sprague-Dawley rats were exposed to inescapable tailshock (IS). IL-1 extra-cellular release, caspase-1 activity and cleavage of GSDMD were measured in dorsal hippocampus. We found that exposure to IS induced a transient increase in the release of IL-1 into the extracellular space immediately after termination of the stressor. IS also induced a transient increase in caspase-1 activity prior to IL-1 release, while activation of GSDMD was observed immediately after termination of the stressor. IS also increased mRNA and protein expression of the ESCRTIII protein CHMP4B, which is involved in cellular repair. The present results suggest that exposure to an acute stressor induces the hallmarks of pyroptosis in brain, which might serve as a key cellular process involved in the release of IL-1 into the extracellular milieu of the brain parenchyma.</p

Mixture of latent trait analyzers for model-based clustering of categorical data

Model-based clustering methods for continuous data are well established and commonly used in a wide range of applications. However, model-based clustering methods for categorical data are less standard. Latent class analysis is a commonly used method for model-based clustering of binary data and/or categorical data, but due to an assumed local independence structure there may not be a correspondence between the estimated latent classes and groups in the population of interest. The mixture of latent trait analyzers model extends latent class analysis by assuming a model for the categorical response variables that depends on both a categorical latent class and a continuous latent trait variable; the discrete latent class accommodates group structure and the continuous latent trait accommodates dependence within these groups. Fitting the mixture of latent trait analyzers model is potentially difficult because the likelihood function involves an integral that cannot be evaluated analytically. We develop a variational approach for fitting the mixture of latent trait models and this provides an efficient model fitting strategy. The mixture of latent trait analyzers model is demonstrated on the analysis of data from the National Long Term Care Survey (NLTCS) and voting in the U.S. Congress. The model is shown to yield intuitive clustering results and it gives a much better fit than either latent class analysis or latent trait analysis alone