482 research outputs found

    In vivo detection of cortical optical changes associated with seizure activity with optical coherence tomography.

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    The most common technology for seizure detection is with electroencephalography (EEG), which has low spatial resolution and minimal depth discrimination. Optical techniques using near-infrared (NIR) light have been used to improve upon EEG technology and previous research has suggested that optical changes, specifically changes in near-infrared optical scattering, may precede EEG seizure onset in in vivo models. Optical coherence tomography (OCT) is a high resolution, minimally invasive imaging technique, which can produce depth resolved cross-sectional images. In this study, OCT was used to detect changes in optical properties of cortical tissue in vivo in mice before and during the induction of generalized seizure activity. We demonstrated that a significant decrease (P < 0.001) in backscattered intensity during seizure progression can be detected before the onset of observable manifestations of generalized (stage-5) seizures. These results indicate the feasibility of minimally-invasive optical detection of seizures with OCT

    Detectors and cryostat design for the SuMIRe Prime Focus Spectrograph (PFS)

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    We describe the conceptual design of the camera cryostats, detectors, and detector readout electronics for the SuMIRe Prime Focus Spectrograph (PFS) being developed for the Subaru telescope. The SuMIRe PFS will consist of four identical spectrographs, each receiving 600 fibers from a 2400 fiber robotic positioner at the prime focus. Each spectrograph will have three channels covering wavelength ranges 3800 {\AA} - 6700 {\AA}, 6500 {\AA} - 10000 {\AA}, and 9700 {\AA} - 13000 {\AA}, with the dispersed light being imaged in each channel by a f/1.10 vacuum Schmidt camera. In the blue and red channels a pair of Hamamatsu 2K x 4K edge-buttable CCDs with 15 um pixels are used to form a 4K x 4K array. For the IR channel, the new Teledyne 4K x 4K, 15 um pixel, mercury-cadmium-telluride sensor with substrate removed for short-wavelength response and a 1.7 um cutoff will be used. Identical detector geometry and a nearly identical optical design allow for a common cryostat design with the only notable difference being the need for a cold radiation shield in the IR camera to mitigate thermal background. This paper describes the details of the cryostat design and cooling scheme, relevant thermal considerations and analysis, and discusses the detectors and detector readout electronics

    Determination of Cellular Lipids Bound to Human CD1d Molecules

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    CD1 molecules are glycoproteins that present lipid antigens at the cell surface for immunological recognition by specialized populations of T lymphocytes. Prior experimental data suggest a wide variety of lipid species can bind to CD1 molecules, but little is known about the characteristics of cellular ligands that are selected for presentation. Here we have molecularly characterized lipids bound to the human CD1d isoform. Ligands were eluted from secreted CD1d molecules and separated by normal phase HPLC, then characterized by mass spectroscopy. A total of 177 lipid species were molecularly identified, comprising glycerophospholipids and sphingolipids. The glycerophospholipids included common diacylglycerol species, reduced forms known as plasmalogens, lyso-phospholipids (monoacyl species), and cardiolipins (tetraacyl species). The sphingolipids included sphingomyelins and glycosylated forms, such as the ganglioside GM3. These results demonstrate that human CD1d molecules bind a surprising diversity of lipid structures within the secretory pathway, including compounds that have been reported to play roles in cancer, autoimmune diseases, lipid signaling, and cell death

    Apoplast proteome reveals that extracellular matrix contributes to multistress response in poplar

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    <p>Abstract</p> <p>Background</p> <p>Riverine ecosystems, highly sensitive to climate change and human activities, are characterized by rapid environmental change to fluctuating water levels and siltation, causing stress on their biological components. We have little understanding of mechanisms by which riverine plant species have developed adaptive strategies to cope with stress in dynamic environments while maintaining growth and development.</p> <p>Results</p> <p>We report that poplar (<it>Populus </it>spp.) has evolved a systems level "stress proteome" in the leaf-stem-root apoplast continuum to counter biotic and abiotic factors. To obtain apoplast proteins from <it>P. deltoides</it>, we developed pressure-chamber and water-displacement methods for leaves and stems, respectively. Analyses of 303 proteins and corresponding transcripts coupled with controlled experiments and bioinformatics demonstrate that poplar depends on constitutive and inducible factors to deal with water, pathogen, and oxidative stress. However, each apoplast possessed a unique set of proteins, indicating that response to stress is partly compartmentalized. Apoplast proteins that are involved in glycolysis, fermentation, and catabolism of sucrose and starch appear to enable poplar to grow normally under water stress. Pathogenesis-related proteins mediating water and pathogen stress in apoplast were particularly abundant and effective in suppressing growth of the most prevalent poplar pathogen <it>Melampsora</it>. Unexpectedly, we found diverse peroxidases that appear to be involved in stress-induced cell wall modification in apoplast, particularly during the growing season. Poplar developed a robust antioxidative system to buffer oxidation in stem apoplast.</p> <p>Conclusion</p> <p>These findings suggest that multistress response in the apoplast constitutes an important adaptive trait for poplar to inhabit dynamic environments and is also a potential mechanism in other riverine plant species.</p

    User-centered Development of STOP (Successful Treatment for Paranoia)::Material Development and Usability Testing for a Digital Therapeutic for Paranoia

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    Background: Paranoia is a highly debilitating mental health condition. One novel intervention for paranoia is cognitive bias modification for paranoia (CBM-pa). CBM-pa comes from a class of interventions that focus on manipulating interpretation bias. Here, we aimed to develop and evaluate new therapy content for CBM-pa for later use in a self-administered digital therapeutic for paranoia called STOP ("Successful Treatment of Paranoia"). Objective: This study aimed to (1) take a user-centered approach with input from living experts, clinicians, and academics to create and evaluate paranoia-relevant item content to be used in STOP and (2) engage with living experts and the design team from a digital health care solutions company to cocreate and pilot-test the STOP mobile app prototype. Methods: We invited 18 people with living or lived experiences of paranoia to create text exemplars of personal, everyday emotionally ambiguous scenarios that could provoke paranoid thoughts. Researchers then adapted 240 suitable exemplars into corresponding intervention items in the format commonly used for CBM training and created 240 control items for the purpose of testing STOP. Each item included newly developed, visually enriching graphics content to increase the engagement and realism of the basic text scenarios. All items were then evaluated for their paranoia severity and readability by living experts (n=8) and clinicians (n=7) and for their item length by the research team. Items were evenly distributed into six 40-item sessions based on these evaluations. Finalized items were presented in the STOP mobile app, which was co-designed with a digital health care solutions company, living or lived experts, and the academic team; user acceptance was evaluated across 2 pilot tests involving living or lived experts. Results: All materials reached predefined acceptable thresholds on all rating criteria: paranoia severity (intervention items: ≥1; control items: ≤1, readability: ≥3, and length of the scenarios), and there was no systematic difference between the intervention and control group materials overall or between individual sessions within each group. For item graphics, we also found no systematic differences in users' ratings of complexity (P=.68), attractiveness (P=.15), and interest (P=.14) between intervention and control group materials. User acceptance testing of the mobile app found that it is easy to use and navigate, interactive, and helpful. Conclusions: Material development for any new digital therapeutic requires an iterative and rigorous process of testing involving multiple contributing groups. Appropriate user-centered development can create user-friendly mobile health apps, which may improve face validity and have a greater chance of being engaging and acceptable to the target end users.</p

    Observations on the release of gas-phase potassium during the combustion of single particles of biomass

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    One of the more significant characteristics of solid biomass fuels as compared to coal is the quantity of potassium that they contain. Potassium content influences ash deposition and corrosion mechanisms in furnaces, the effects of which may differ depending on phase transformations of potassium species in the gas phase and condensed phase. The fate of potassium from the fuel during the combustion process is therefore an important concern. To investigate this, an experimental method is presented in which the release patterns from single particles of various biomass fuels are measured by use of flame emission spectroscopy implemented using a custom-built photo-detector device. Single particles of fuel are combusted in a methane flame with a gas temperature of ∼1800 K. The observed potassium release patterns for thirteen solid biomass materials are presented. The data are analyzed to examine the relationships between: the level of potassium in the fuel particle; the fraction of potassium released at each stage of combustion and the peak rate of release of potassium to gas-phase during combustion. Correlations between these quantities are identified with key trends, patterns and differences highlighted. The analyses provide useful information for the development and validation of modelling of potassium release during combustion of biomass
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