Pyrroloquinoline quinone increases the expression and activity of Sirt1 and -3 genes in HepG2 cells.

Sirtuin (Sirt) 1 and Sirt 3 are nicotinamide adenine dinucleotide ((+))-dependent protein deacetylases that are important to a number of mitochondrial-related functions; thus, identification of sirtuin activators is important. Herein, we hypothesize that pyrroloquinoline quinone (PQQ) can act as a Sirt1/Sirt3 activator. In HepG2 cell cultures, PQQ increased the expression of Sirt1 and Sirt3 gene, protein, and activity levels (P < .05). We also observed a significant increase in nicotinamide phosphoribosyltransferase gene expression (as early as 18 hours) and increased NAD(+) activity at 24 hours. In addition, targets of Sirt1 and Sirt3 (peroxisome proliferator-activated receptor γ coactivator 1α, nuclear respiratory factor 1 and 2, and mitochondrial transcription factor A) were increased at 48 hours. This is the first report that demonstrates PQQ as an activator of Sirt1 and Sirt3 expression and activity, making it an attractive therapeutic agent for the treatment of metabolic diseases and for healthy aging. Based on our study and the available data in vivo, PQQ has the potential to serve as a therapeutic nutraceutical, when enhancing mitochondrial function

ShapeShifter: Robust Physical Adversarial Attack on Faster R-CNN Object Detector

Given the ability to directly manipulate image pixels in the digital input space, an adversary can easily generate imperceptible perturbations to fool a Deep Neural Network (DNN) image classifier, as demonstrated in prior work. In this work, we propose ShapeShifter, an attack that tackles the more challenging problem of crafting physical adversarial perturbations to fool image-based object detectors like Faster R-CNN. Attacking an object detector is more difficult than attacking an image classifier, as it needs to mislead the classification results in multiple bounding boxes with different scales. Extending the digital attack to the physical world adds another layer of difficulty, because it requires the perturbation to be robust enough to survive real-world distortions due to different viewing distances and angles, lighting conditions, and camera limitations. We show that the Expectation over Transformation technique, which was originally proposed to enhance the robustness of adversarial perturbations in image classification, can be successfully adapted to the object detection setting. ShapeShifter can generate adversarially perturbed stop signs that are consistently mis-detected by Faster R-CNN as other objects, posing a potential threat to autonomous vehicles and other safety-critical computer vision systems

Did Uranus' regular moons form via a rocky giant impactor?

The formation of Uranus' regular moons has been suggested to be linked to the origin of its enormous spin axial tilt (~98^o). A giant impact between proto-Uranus and a 2-3 M_Earth impactor could lead to a large tilt and to the formation of an impact generated disc, where prograde and circular satellites are accreted. The most intriguing features of the current regular Uranian satellite system is that it possesses a positive trend in the mass-distance distribution and likely also in the bulk density, implying that viscous spreading of the disc after the giant impact plays a crucial role in shaping the architecture of the final system. In this paper, we investigate the formation of Uranus' satellites by combining results of SPH simulations for the giant impact, a 1D semi-analytic disc model for viscous spreading of the post-impact disc, and N-body simulations for the assembly of satellites from a disc of moonlets. Assuming the condensed rock (i.e., silicate) remains small and available to stick onto the relatively rapid growing condensed water-ice, we find that the best case in reproducing the observed mass and bulk composition of Uranus' satellite system is a pure-rocky impactor with 3 M_Earth colliding with the young Uranus with an impact parameter b = 0.75. Such an oblique collision could also naturally explain Uranus' large tilt and possibly, its low internal heat flux. The giant impact scenario can naturally explain the key features of Uranus and its regular moons. We therefore suggest that the Uranian satellite system formed as a result of an impact rather than from a circumplanetary disc.Comment: Accepted for publication in Icaru

Electroencephalographic interbrain synchronization in children with disabilities, their parents, and neurologic music therapists

: As with typically developing children, children with cerebral palsy and autism spectrum disorder develop important socio-emotional rapport with their parents and healthcare providers. However, the neural mechanisms underlying these relationships have been less studied. By simultaneously measuring the brain activity of multiple individuals, interbrain synchronization could serve as a neurophysiological marker of social-emotional responses. Music evokes emotional and physiological responses and enhances social cohesion. These characteristics of music have fostered its deployment as a therapeutic medium in clinical settings. Therefore, this study investigated two aspects of interbrain synchronization, namely, its phase and directionality, in child-parent (CP) and child-therapist (CT) dyads during music and storytelling sessions (as a comparison). A total of 17 participants (seven cerebral palsy or autism spectrum disorder children [aged 12-18 years], their parents, and three neurologic music therapists) completed this study, comprising seven CP and seven CT dyads. Each music therapist worked with two or three children. We found that session type, dyadic relationship, frequency band, and brain region were significantly related to the degree of interbrain synchronization and its directionality. Particularly, music sessions and CP dyads were associated with higher interbrain synchronization and stronger directionality. Delta (.5-4 Hz) range showed the highest phase locking value in both CP and CT dyads in frontal brain regions. It appears that synchronization is directed predominantly from parent to child, that is, parents and music therapists' brain activity tended to influence a child's. Our findings encourage further research into neural synchrony in children with disabilities, especially in musical contexts, and its implications for social and emotional development

The prevalence and correlates of sitting in European adults - a comparison of 32 Eurobarometer-participating countries

Background Prolonged sitting is an emerging health risk. However, multi-country comparative sitting data are sparse. This paper reports the prevalence and correlates of sitting time in 32 European countries. Methods Data from the Eurobarometer 64.3 study were used, which included nationally representative samples (n = 304-1,102) from 32 European countries. Face-to-face interviews were conducted during November and December 2005. Usual weekday sitting time was assessed using the International Physical Activity Questionnaire (short-version). Sitting time was compared by country, age, gender, years of education, general health status, usual activity and physical activity. Multivariable-adjusted analyses assessed the odds of belonging to the highest sitting quartile. Results Data were available for 27,637 adults aged 15–98 years. Overall, mean reported weekday sitting time was 309 min/day (SD 184 min/day). There was a broad geographical pattern and some of the lowest amounts of daily sitting were reported in southern (Malta and Portugal means 194–236 min/day) and eastern (Romania and Hungary means 191–276 min/day) European countries; and some of the highest amounts of daily sitting were reported in northern European countries (Germany, Benelux and Scandinavian countries; means 407–335 min/day). Multivariable-adjusted analyses showed adults with low physical activity levels (OR = 5.10, CI95 = 4.60-5.66), those with high sitting in their main daily activity (OR = 2.99, CI95 = 2.74-3.25), those with a bad/very bad general health state (OR = 1.87, CI95 = 1.63-2.15) and higher education levels (OR = 1.48, CI95 = 1.38-1.59) were more likely to be in the highest quartile of daily sitting time. Adults within Greece (OR = 2.91, CI95 = 2.51-3.36) and Netherlands (OR = 2.56, CI95 = 2.22-2.94) were most likely to be in the highest quartile. High-sit/low-active participants comprised 10.1% of the sample. Adults self-reporting bad/very bad general health state (OR = 4.74, CI95 = 3.97-5.65), those within high sitting in their main daily activities (OR = 2.87, CI95 = 2.52-3.26) and adults aged ≥65 years (OR = 1.53, CI95 = 1.19-1.96) and were more likely to be in the high-sit/low-active group. Conclusions Weekday sitting time and its demographic correlates varied considerably across European countries, with adults in north-western European countries sitting the most. Sitting is prevalent across Europe and merits attention by preventive interventions

Robust Principles: Architectural Design Principles for Adversarially Robust CNNs

Our research aims to unify existing works' diverging opinions on how architectural components affect the adversarial robustness of CNNs. To accomplish our goal, we synthesize a suite of three generalizable robust architectural design principles: (a) optimal range for depth and width configurations, (b) preferring convolutional over patchify stem stage, and (c) robust residual block design through adopting squeeze and excitation blocks and non-parametric smooth activation functions. Through extensive experiments across a wide spectrum of dataset scales, adversarial training methods, model parameters, and network design spaces, our principles consistently and markedly improve AutoAttack accuracy: 1-3 percentage points (pp) on CIFAR-10 and CIFAR-100, and 4-9 pp on ImageNet. The code is publicly available at https://github.com/poloclub/robust-principles.Comment: Published at BMVC'2

Rapid assessment of T-cell receptor specificity of the immune repertoire

Accurate assessment of T-cell-receptor (TCR)–antigen specificity across the whole immune repertoire lies at the heart of improved cancer immunotherapy, but predictive models capable of high-throughput assessment of TCR–peptide pairs are lacking. Recent advances in deep sequencing and crystallography have enriched the data available for studying TCR–peptide systems. Here, we introduce RACER, a pairwise energy model capable of rapid assessment of TCR–peptide affinity for entire immune repertoires. RACER applies supervised machine learning to efficiently and accurately resolve strong TCR–peptide binding pairs from weak ones. The trained parameters further enable a physical interpretation of interacting patterns encoded in each TCR–peptide system. When applied to simulate thymic selection of a major-histocompatibility-complex (MHC)-restricted T-cell repertoire, RACER accurately estimates recognition rates for tumor-associated neoantigens and foreign peptides, thus demonstrating its utility in helping address the computational challenge of reliably identifying properties of tumor antigen-specific T-cells at the level of an individual patient’s immune repertoire