Young Adults\u27 Autistic Behaviors Predict P1 and N170 Responses to Emotion Stimuli

Autism Spectrum Disorder (ASD) is a developmental disorder characterized by core deficits in social, communication, and motor skills (CDC, 2013). Deficits in emotional processing have also been identified, especially with negative emotions and surprise. These behavioral deficits are reflected in differences in neural responses, specifically with the P1 and N170 event-related potential components. The current study explored how these neural differences in emotion processing are modified by autistic behaviors in a subclinical population using a task that varied both by facial features available and instructions intended to modify the type of processing occurring. The results supported previous findings that those with low levels of autistic behaviors have increased neural attention, as measured by P1 and N170 amplitude, to fearful stimuli, while those with high levels did not show higher amplitudes. Exploratory analyses using autistic behaviors as a continuous variable showed this same response pattern with surprise for P1 yet showed an increase in N170 amplitude in those with high levels of autistic behaviors. These findings maintained their significance when controlling for social anxiety-related behaviors. Additionally, the results demonstrated that, in those with high levels of autistic behaviors, less neural attention occurred in response to faces in which only the eye region was shown, contrasting the increase in neural attention in those with low levels of autistic behaviors when presented the eye region instead of a face. Together the findings indicate in a subclinical population that the impact of autistic behaviors on the processing of emotions varies by emotion as well as by the facial features available

LexOPS: An R package and user interface for the controlled generation of word stimuli

LexOPS is an R package and user interface designed to facilitate the generation of word stimuli for use in research. Notably, the tool permits the generation of suitably controlled word lists for any user-specified factorial design and can be adapted for use with any language. It features an intuitive graphical user interface, including the visualization of both the distributions within and relationships among variables of interest. An inbuilt database of English words is also provided, including a range of lexical variables commonly used in psycholinguistic research. This article introduces LexOPS, outlining the features of the package and detailing the sources of the inbuilt dataset. We also report a validation analysis, showing that, in comparison to stimuli of existing studies, stimuli optimized with LexOPS generally demonstrate greater constraint and consistency in variable manipulation and control. Current instructions for installing and using LexOPS are available at https://JackEdTaylor.github.io/LexOPSdocs/

Investigating Quantitative Autism Spectrum Behaviors In A Family-Based Genetics Study

Autism Spectrum Disorder (ASD) is a neurodevelopmental condition that is complex both in its behavioral presentation and in its genetic basis. The use of quantitative behavioral phenotypes instead of the binary, categorical phenotype of diagnosis (Yes ASD, No ASD) has yet to be broadly applied in some areas of ASD research, including ASD genetics. Prior to investigating quantitative ASD-related phenotypes in humans, we reviewed the literature connecting synaptic cell adhesion molecules to social affiliation (a behavior disrupted in autism) in rodent models, and we proposed a mechanistic model. Then, by recruiting autistic adults and their extended family members through the Autism Spectrum Program of Excellence and having them complete a detailed quantitative phenotypic battery, we were able to address the reliability of quantitative phenotyping measures and to start investigating them. We found nearly all of the tested quantitative phenotypes to be heritable across several ASD-relevant behavioral domains – including social communication, repetitive behaviors, and executive functioning. Additionally, we found poor agreement between self-report and informant-report of two such measures (the Social Responsiveness Scale (social communication) and the Behavior Rating Inventory for Executive Function (executive functioning)) among autistic adults. Finally, we looked at the relationships between several relevant quantitative phenotypes, namely measures of overall ASD-related traits, psychological resilience, anxiety, and depression. We found these constructs to be related in such a way that suggests that enhancing resilience may mitigate depression among those high in ASD-related traits. All together, this work points to the promise of a quantitative trait approach in ASD research and highlights the need for several, overlapping measures across multiple behavioral domains for the most thorough understanding of ASD-related behavioral phenotypes

Transgenic mice expressing mutant forms VCP/p97 recapitulate the full spectrum of IBMPFD including degeneration in muscle, brain and bone

Inclusion body myopathy associated with Paget's disease of bone and frontotemporal dementia (IBMPFD) is a dominantly inherited degenerative disorder caused by mutations in the valosin-containing protein (VCP) gene. VCP (p97 in mouse, TER94 in Drosophila melanogaster and CDC48 in Saccharomyces cerevisiae) is a highly conserved AAA+-ATPase that regulates a wide array of cellular processes. The mechanism of IBMPFD pathogenesis is unknown. Towards elucidating the pathogenic mechanism we have developed and characterized transgenic mice with ubiquitous expression of wild-type and disease-causing versions of human VCP/p97. Here, we report that mice expressing VCP/p97 harboring the mutations R155H or A232E develop pathology that is limited to muscle, brain and bone, recapitulating the spectrum of disease in humans with IBMPFD. The mice exhibit progressive muscle weakness and pathological examination of muscle shows classic characteristics of inclusion body myopathy including rimmed vacuoles and TDP-43 pathology. The mice exhibit abnormalities in behavioral testing and pathological examination of the brain shows widespread TDP-43 pathology. Furthermore, radiological examination of the skeleton reveals that mutant mice develop severe osteopenia accompanied by focal lytic and sclerotic lesions in vertebrae and femur. In vitro studies indicate that mutant VCP causes inappropriate activation of the NF-κB signaling cascade, which could contribute to the mechanism of pathogenesis in multiple tissues including muscle, bone and brai

Comparative analysis of services from soft open points using cost–benefit analysis

Soft Open Points (SOPs) are power electronic-based devices which can replace Normally Open Points (NOPs) in distribution networks. They can improve network performance by enabling controllable power transfer between adjacent feeders. This flexible meshing can provide a wide range of services, including loss reduction, reduced renewables curtailment, improved reliability, reinforcement deferral, or enabling flexibility services. This paper proposes a novel framework, based on the Cost–Benefit Analysis methodology, to quantify and compare the cost-effectiveness of SOPs for providing each of these five value streams. The framework includes the development of mathematical models that encapsulate the key variables that drive competitive SOP use cases, as well as providing detailed analysis to determine quantitative estimates for each of the parameters. Results suggest that, whilst all services could be cost-effective, that reinforcement deferral and reduced DG curtailment are most likely to find wide usage. It is also suggested that the fast response time of SOPs as compared to conventional NOPs is unlikely to be a viable value proposition for improving reliability via conventional loss of load metrics such as energy not supplied. A detailed case study demonstrates that in marginal cases, where a SOP has a similar system net benefit compared to Business-as-Usual, that all services need to be considered rather than just single value streams in isolation. It is concluded from the research that there are multiple potential competitive applications for SOPs in future distribution networks.</p

A sensitive high performance liquid chromatography assay for the quantification of doxorubicin associated with DNA in tumor and tissues

A HPLC method was validated to quantify doxorubicin associated to DNA from tissue.Successfully applied to an in vivo mouse-based pharmacokinetic study.Important tool for future studies evaluating intracellular pharmacokinetics.Doxorubicin, a widely used anticancer agent, exhibits antitumor activity against a wide variety of malignancies. The drug exerts its cytotoxic effects by binding to and intercalating within the DNA of tumor and tissue cells. However, current assays are unable to accurately determine the concentration of the intracellular active form of doxorubicin. Thus, the development of a sample processing method and a high-performance liquid chromatography (HPLC) methodology was performed in order to quantify doxorubicin that is associated with DNA in tumors and tissues, which provided an intracellular cytotoxic measure of doxorubicin exposure after administration of small molecule and nanoparticle formulations of doxorubicin. The assay uses daunorubicin as an internal standard; liquid–liquid phase extraction to isolate drug associated with DNA; a Shimadzu HPLC with fluorescence detection equipped with a Phenomenex Luna C18 (2 μm, 2.0 × 100 mm) analytical column and a gradient mobile phase of 0.1% formic acid in water or acetonitrile for separation and quantification. The assay has a lower limit of detection (LLOQ) of 10 ng/mL and is shown to be linear up to 3000 ng/mL. The intra- and inter-day precision of the assay expressed as a coefficient of variation (CV%) ranged from 4.01 to 8.81%. Furthermore, the suitability of this assay for measuring doxorubicin associated with DNA in vivo was demonstrated by using it to quantify the doxorubicin concentration within tumor samples from SKOV3 and HEC1A mice obtained 72 h after administration of PEGylated liposomal doxorubicin (Doxil®; PLD) at 6 mg/kg IV x 1. This HPLC assay allows for sensitive intracellular quantification of doxorubicin and will be an important tool for future studies evaluating intracellular pharmacokinetics of doxorubicin and various nanoparticle formulations of doxorubicin

Building-to-building energy trading under the influence of occupant comfort

Peer-to-peer energy trading is becoming an efficient methodology for trading flexibility between buildings due to the increasing utilisation of small-scale generation and storage technologies. In the buildings, however, this trading mechanism could be affected by occupant comfort and uncertainty around it, affecting the building operation and consumption. This study introduces a multi-level peer-to-peer energy trading framework for residential buildings under the influence of occupants preferences. The proposed method considers the effect of occupants comfort as an important factor on the control and energy management of buildings in local markets. The robustness of the proposed real-time control framework in face of uncertainty in a real-life building parameter (i.e. occupants comfort level) is improved through the-state-of-the-art information gap decision theory technique. This method requires very little information about uncertain parameters, making it a suitable technique for dealing with the uncertainty in parameters with unknown patterns. Finally, the operational models of energy storage and electric vehicles are adopted for full utilisation of available photovoltaic generation. The simulation results show that participating in the local energy trading can increase the robustness of the control systems in the residential microgrids in face of uncertainty in the occupant comfort level. Also, results show that 0.1% increase in the uncertainty radius of occupants comfort level requires a 6% increase in the energy bill. This shows the importance of considering the occupant comfort in the conventional building energy management strategies, and uncertainty around it on the energy bill.</p

MicroGrid Resilience-Oriented Scheduling:A Robust MISOCP Model

This article introduces a Robust Mixed-Integer Second Order Cone Programming (R-MISOCP) model for the resilience-oriented optimal scheduling of microgrids (MGs). This is developed for MGs that are islanded due to a scheduled interruption from the main grid, where minimizing both operational costs and load shedding is critical. The model introduced presents two main benefits. Firstly, an accurate second order cone power flow model (SOC-PF) is used, which ensures global optimality. Through a comparison with a piecewise linear power flow model on a modified IEEE 33 bus network, it is demonstrated that failure to accurately model power flow equations, can result in a significant underestimation of the operational cost of almost 12%. Secondly, uncertainty is modelled using a robust approach which allows trade-offs between the uncertainty that a MG operator is willing to tolerate, and performance. In this article, performance criteria considered are operational cost and load shedding. Market price, demand, renewable generation and islanding duration are considered as uncertain variables. Results show that by controlling the budget of uncertainty, the MG operator can achieve an almost 20% reduction in the operating cost, compared to a fully robust schedule, while achieving 0% probability of shedding more demand than expected

Building-to-building energy trading under the influence of occupant comfort

Peer-to-peer energy trading is becoming an efficient methodology for trading flexibility between buildings due to the increasing utilisation of small-scale generation and storage technologies. In the buildings, however, this trading mechanism could be affected by occupant comfort and uncertainty around it, affecting the building operation and consumption. This study introduces a multi-level peer-to-peer energy trading framework for residential buildings under the influence of occupants preferences. The proposed method considers the effect of occupants comfort as an important factor on the control and energy management of buildings in local markets. The robustness of the proposed real-time control framework in face of uncertainty in a real-life building parameter (i.e. occupants comfort level) is improved through the-state-of-the-art information gap decision theory technique. This method requires very little information about uncertain parameters, making it a suitable technique for dealing with the uncertainty in parameters with unknown patterns. Finally, the operational models of energy storage and electric vehicles are adopted for full utilisation of available photovoltaic generation. The simulation results show that participating in the local energy trading can increase the robustness of the control systems in the residential microgrids in face of uncertainty in the occupant comfort level. Also, results show that 0.1% increase in the uncertainty radius of occupants comfort level requires a 6% increase in the energy bill. This shows the importance of considering the occupant comfort in the conventional building energy management strategies, and uncertainty around it on the energy bill.</p