Polarization-Based Illumination Detection for Coherent Augmented Reality Scene Rendering in Dynamic Environments

A virtual object that is integrated into the real world in a perceptually coherent manner using the physical illumination information in the current environment is still under development. Several researchers investigated the problem producing a high-quality result; however, pre-computation and offline availability of resources were the essential assumption upon which the system relied. In this paper, we propose a novel and robust approach to identifying the incident light in the scene using the polarization properties of the light wave and using this information to produce a visually coherent augmented reality within a dynamic environment. This approach is part of a complete system which has three simultaneous components that run in real-time: (i) the detection of the incident light angle, (ii) the estimation of the reflected light, and (iii) the creation of the shading properties which are required to provide any virtual object with the detected lighting, reflected shadows, and adequate materials. Finally, the system performance is analyzed where our approach has reduced the overall computational cost

Photoswitchable diacylglycerols enable optical control of protein kinase C.

Increased levels of the second messenger lipid diacylglycerol (DAG) induce downstream signaling events including the translocation of C1-domain-containing proteins toward the plasma membrane. Here, we introduce three light-sensitive DAGs, termed PhoDAGs, which feature a photoswitchable acyl chain. The PhoDAGs are inactive in the dark and promote the translocation of proteins that feature C1 domains toward the plasma membrane upon a flash of UV-A light. This effect is quickly reversed after the termination of photostimulation or by irradiation with blue light, permitting the generation of oscillation patterns. Both protein kinase C and Munc13 can thus be put under optical control. PhoDAGs control vesicle release in excitable cells, such as mouse pancreatic islets and hippocampal neurons, and modulate synaptic transmission in Caenorhabditis elegans. As such, the PhoDAGs afford an unprecedented degree of spatiotemporal control and are broadly applicable tools to study DAG signaling

Virologic Failures on Initial Boosted-PI Regimen Infrequently Possess Low-Level Variants with Major PI Resistance Mutations by Ultra-Deep Sequencing

It is unknown whether HIV-positive patients experiencing virologic failure (VF) on boosted-PI (PI/r) regimens without drug resistant mutations (DRM) by standard genotyping harbor low-level PI resistant variants. CASTLE compared the efficacy of atazanavir/ritonavir (ATV/r) with lopinavir/ritonavir (LPV/r), each in combination with TVD in ARV-naïve subjects.To determine if VF on an initial PI/r-based regimen possess low-level resistant variants that may affect a subsequent PI-containing regimen.Patients experiencing VF on a Tenofovir/Emtricitabine+PI/r regimen were evaluated by ultra deep sequencing (UDS) for mutations classified/weighted by Stanford HIVdb. Samples were evaluated for variants to 0.4% levels. 36 VF subjects were evaluated by UDS; 24 had UDS for PI and RT DRMs. Of these 24, 19 (79.2%) had any DRM by UDS. The most common UDS-detected DRM were NRTI in 18 subjects: M184V/I (11), TAMs(7) & K65R(4); PI DRMs were detected in 9 subjects: M46I/V(5), F53L(2), I50V(1), D30N(1), and N88S(1). The remaining 12 subjects, all with VLs<10,000, had protease gene UDS, and 4 had low-level PI DRMs: F53L(2), L76V(1), I54S(1), G73S(1). Overall, 3/36(8.3%) subjects had DRMs identified with Stanford-HIVdb weights >12 for ATV or LPV: N88S (at 0.43% level-mutational load 1,828) in 1 subject on ATV; I50V (0.44%-mutational load 110) and L76V (0.52%-mutational load 20) in 1 subject each, both on LPV. All VF samples remained phenotypically susceptible to the treatment PI/r.Among persons experiencing VF without PI DRMs with standard genotyping on an initial PI/r regimen, low-level variants possessing major PI DRMs were present in a minority of cases, occurred in isolation, and did not result in phenotypic resistance. NRTI DRMs were detected in a high proportion of subjects. These data suggest that PIs may remain effective in subjects experiencing VF on a PI/r-based regimen when PI DRMs are not detected by standard or UDS genotyping

The Escherichia coli transcriptome mostly consists of independently regulated modules

Underlying cellular responses is a transcriptional regulatory network (TRN) that modulates gene expression. A useful description of the TRN would decompose the transcriptome into targeted effects of individual transcriptional regulators. Here, we apply unsupervised machine learning to a diverse compendium of over 250 high-quality Escherichia coli RNA-seq datasets to identify 92 statistically independent signals that modulate the expression of specific gene sets. We show that 61 of these transcriptomic signals represent the effects of currently characterized transcriptional regulators. Condition-specific activation of signals is validated by exposure of E. coli to new environmental conditions. The resulting decomposition of the transcriptome provides: a mechanistic, systems-level, network-based explanation of responses to environmental and genetic perturbations; a guide to gene and regulator function discovery; and a basis for characterizing transcriptomic differences in multiple strains. Taken together, our results show that signal summation describes the composition of a model prokaryotic transcriptome

Comparison of Insertional RNA Editing in Myxomycetes

RNA editing describes the process in which individual or short stretches of nucleotides in a messenger or structural RNA are inserted, deleted, or substituted. A high level of RNA editing has been observed in the mitochondrial genome of Physarum polycephalum. The most frequent editing type in Physarum is the insertion of individual Cs. RNA editing is extremely accurate in Physarum; however, little is known about its mechanism. Here, we demonstrate how analyzing two organisms from the Myxomycetes, namely Physarum polycephalum and Didymium iridis, allows us to test hypotheses about the editing mechanism that can not be tested from a single organism alone. First, we show that using the recently determined full transcriptome information of Physarum dramatically improves the accuracy of computational editing site prediction in Didymium. We use this approach to predict genes in the mitochondrial genome of Didymium and identify six new edited genes as well as one new gene that appears unedited. Next we investigate sequence conservation in the vicinity of editing sites between the two organisms in order to identify sites that harbor the information for the location of editing sites based on increased conservation. Our results imply that the information contained within only nine or ten nucleotides on either side of the editing site (a distance previously suggested through experiments) is not enough to locate the editing sites. Finally, we show that the codon position bias in C insertional RNA editing of these two organisms is correlated with the selection pressure on the respective genes thereby directly testing an evolutionary theory on the origin of this codon bias. Beyond revealing interesting properties of insertional RNA editing in Myxomycetes, our work suggests possible approaches to be used when finding sequence motifs for any biological process fails

Big hearts, small hands:A focus group study exploring parental food portion behaviours

© The Author(s). 2017. This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.Background: The development of healthy food portion sizes among families is deemed critical to childhood weight management; yet little is known about the interacting factors influencing parents' portion control behaviours. This study aimed to use two synergistic theoretical models of behaviour: the COM-B model (Capability, Opportunity, Motivation - Behaviour) and Theoretical Domains Framework (TDF) to identify a broad spectrum of theoretically derived influences on parents' portion control behaviours including examination of affective and habitual influences often excluded from prevailing theories of behaviour change. Methods: Six focus groups exploring family weight management comprised of one with caseworkers (n = 4), four with parents of overweight children (n = 14) and one with parents of healthy weight children (n = 8). A thematic analysis was performed across the dataset where the TDF/COM-B were used as coding frameworks. Results: To achieve the target behaviour, the behavioural analysis revealed the need for eliciting change in all three COM-B domains and nine associated TDF domains. Findings suggest parents' internal processes such as their emotional responses, habits and beliefs, along with social influences from partners and grandparents, and environmental influences relating to items such as household objects, interact to influence portion size behaviours within the home environment. Conclusion: This is the first study underpinned by COM-B/TDF frameworks applied to childhood weight management and provides new targets for intervention development and the opportunity for future research to explore the mediating and moderating effects of these variables on one another.Peer reviewedFinal Published versio

Potential health impacts of heavy metals on HIV-infected population in USA.

Noninfectious comorbidities such as cardiovascular diseases have become increasingly prevalent and occur earlier in life in persons with HIV infection. Despite the emerging body of literature linking environmental exposures to chronic disease outcomes in the general population, the impacts of environmental exposures have received little attention in HIV-infected population. The aim of this study is to investigate whether individuals living with HIV have elevated prevalence of heavy metals compared to non-HIV infected individuals in United States. We used the National Health and Nutrition Examination Survey (NHANES) 2003-2010 to compare exposures to heavy metals including cadmium, lead, and total mercury in HIV infected and non-HIV infected subjects. In this cross-sectional study, we found that HIV-infected individuals had higher concentrations of all heavy metals than the non-HIV infected group. In a multivariate linear regression model, HIV status was significantly associated with increased blood cadmium (p=0.03) after adjusting for age, sex, race, education, poverty income ratio, and smoking. However, HIV status was not statistically associated with lead or mercury levels after adjusting for the same covariates. Our findings suggest that HIV-infected patients might be significantly more exposed to cadmium compared to non-HIV infected individuals which could contribute to higher prevalence of chronic diseases among HIV-infected subjects. Further research is warranted to identify sources of exposure and to understand more about specific health outcomes