31,396 research outputs found
Magneto-optical characteristics of magnetic nanowire arrays in anodic aluminium oxide templates
Nanocomposite films consisting of regularly ordered iron nanowires embedded in anodic aluminum oxide templates have been fabricated and their magneto-optical properties studied by determining the four Stokes parameters of the transmitted laser beam (λ=670 nm), originally linearly polarized and at normal incidence to the film surfaces. The results of the nanowire arrays are found to be considerably different from that of bulk iron. While an increase in diameter of the nanowire leads to a substantial increase in the values of the Faraday rotation angles per unit length at a fixed value of the magnetic fields, they are substantially less than that of bulk iron, indicating that the effective media theory may not be directly applicable
Both doublecortin and doublecortin-like kinase play a role in cortical interneuron migration
Type I lissencephaly, a genetic disease characterized by disorganized cortical layers and gyral abnormalities, is associated with severe cognitive impairment and epilepsy. Two genes, LIS1 and doublecortin (DCX), have been shown to be responsible for a large proportion of cases of type I lissencephaly. Both genes encode microtubule-associated proteins that have been shown to be important for radial migration of cortical pyramidal neurons. To investigate whether DCX also plays a role in cortical interneuron migration, we inactivated DCX in the ganglionic eminence of rat embryonic day 17 brain slices using short hairpin RNA. We found that, when DCX expression was blocked, the migration of interneurons from the ganglionic eminence to the cerebral cortex was slowed but not absent, similar to what had previously been reported for radial neuronal migration. In addition, the processes of DCX-deficient migrating interneurons were more branched than their counterparts in control experiments. These effects were rescued by DCX overexpression, confirming the specificity to DCX inactivation. A similar delay in interneuron migration was observed when Doublecortin-like kinase (DCLK), a microtubule-associated protein related to DCX, was inactivated, although the morphology of the cells was not affected. The importance of these genes in interneuron migration was confirmed by our finding that the cortices of Dcx, Dclk, and Dcx/Dclk mutant mice contained a reduced number of such cells in the cortex and their distribution was different compared with wild-type controls. However, the defect was different for each group of mutant animals, suggesting that DCX and DCLK have distinct roles in cortical interneuron migration
Rapid and efficient stable gene transfer to mesenchymal stromal cells using a modified foamy virus vector
Mesenchymal stromal cells (MSCs) hold great promise for regenerative medicine. Stable ex vivo gene transfer to MSCs could improve the outcome and scope of MSC therapy, but current vectors require multiple rounds of transduction, involve genotoxic viral promoters and/or the addition of cytotoxic cationic polymers in order to achieve efficient transduction. We describe a self-inactivating foamy virus vector (FVV), incorporating the simian macaque foamy virus envelope and using physiological promoters, which efficiently transduces murine MSCs (mMSCs) in a single-round. High and sustained expression of the transgene, whether GFP or the lysosomal enzyme, arylsulphatase A (ARSA), was achieved. Defining MSC characteristics (surface marker expression and differentiation potential), as well as long-term engraftment and distribution in the murine brain following intracerebroventricular delivery, are unaffected by FVV transduction. Similarly, greater than 95% of human MSCs (hMSCs) were stably transduced using the same vector, facilitating human application. This work describes the best stable gene transfer vector available for mMSCs and hMSCs
Evaluating and comparing fault-based testing strategies for general Boolean specifications: A series of experiments
A great amount of fault-based testing strategies have been proposed to generate test cases for detecting certain types of faults in Boolean specifications. However, most of the previous studies on these strategies were focused on the Boolean expressions in the disjunctive normal form (DNF), even the irredundant DNF (IDNF)-little work has been conducted to comprehensively investigate their performance on general Boolean specifications. In this study, we conducted a series of experiments to evaluate and compare 18 fault-based testing strategies using over 4000 randomly generated fault-seeded Boolean expressions. In the experiments, a testing strategy is regarded as effective and efficient if it can detect most of the seeded faults using a small number of test cases. Our experimental results show that if a testing strategy is highly effective and efficient when testing the Boolean expressions in the IDNF, it also shows high effectiveness and efficiency on general Boolean expressions. It is found that one family of fault-based testing strategies, namely MUMCUT, normally deliver the best performance among all the 18 strategies. Our study provides an in-depth understanding and insight of fault-based testing for general Boolean expressions
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Developing Children's Oral Health Assessment Toolkits Using Machine Learning Algorithm.
ObjectivesEvaluating children's oral health status and treatment needs is challenging. We aim to build oral health assessment toolkits to predict Children's Oral Health Status Index (COHSI) score and referral for treatment needs (RFTN) of oral health. Parent and Child toolkits consist of short-form survey items (12 for children and 8 for parents) with and without children's demographic information (7 questions) to predict the child's oral health status and need for treatment.MethodsData were collected from 12 dental practices in Los Angeles County from 2015 to 2016. We predicted COHSI score and RFTN using random Bootstrap samples with manually introduced Gaussian noise together with machine learning algorithms, such as Extreme Gradient Boosting and Naive Bayesian algorithms (using R). The toolkits predicted the probability of treatment needs and the COHSI score with percentile (ranking). The performance of the toolkits was evaluated internally and externally by residual mean square error (RMSE), correlation, sensitivity and specificity.ResultsThe toolkits were developed based on survey responses from 545 families with children aged 2 to 17 y. The sensitivity and specificity for predicting RFTN were 93% and 49% respectively with the external data. The correlation(s) between predicted and clinically determined COHSI was 0.88 (and 0.91 for its percentile). The RMSEs of the COHSI toolkit were 4.2 for COHSI (and 1.3 for its percentile).ConclusionsSurvey responses from children and their parents/guardians are predictive for clinical outcomes. The toolkits can be used by oral health programs at baseline among school populations. The toolkits can also be used to quantify differences between pre- and post-dental care program implementation. The toolkits' predicted oral health scores can be used to stratify samples in oral health research.Knowledge transfer statementThis study creates the oral health toolkits that combine self- and proxy- reported short forms with children's demographic characteristics to predict children's oral health and treatment needs using Machine Learning algorithms. The toolkits can be used by oral health programs at baseline among school populations to quantify differences between pre and post dental care program implementation. The toolkits can also be used to stratify samples according to the treatment needs and oral health status
Enhancing conductivity of silver nanowire networks through surface engineering using bidentate rigid ligands
Solution processable metallic nanomaterials present a convenient way to fabricate conductive structures, which are necessary in all electronic devices. However, they tend to require post-treatments to remove the bulky ligands around them to achieve high conductivity. In this work, we present a method to formulate a post-treatment free conductive silver nanowire ink by controlling the type of ligands around the silver nanowires. We found that bidentate ligands with a rigid molecular structure were effective in improving the conductivity of the silver nanowire networks as they could maximize the number of linkages between neighboring nanowires. In addition, DFT calculations also revealed that ligands with good LUMO to silver energy alignment were more effective. Because of these reasons, fumaric acid was found to be the most effective ligand and achieved a large reduction in sheet resistance of 70% or higher depending on the nanowire network density. The concepts elucidated from this study would also be applicable to other solution processable nanomaterials systems such as quantum dots for photovoltaics or LEDs which also require good charge transport being neighboring nanoparticles
Retinal glycoprotein enrichment by concanavalin a enabled identification of novel membrane autoantigen synaptotagmin-1 in equine recurrent uveitis.
Complete knowledge of autoantigen spectra is crucial for understanding pathomechanisms of autoimmune diseases like equine recurrent uveitis (ERU), a spontaneous model for human autoimmune uveitis. While several ERU autoantigens were identified previously, no membrane protein was found so far. As there is a great overlap between glycoproteins and membrane proteins, the aim of this study was to test whether pre-enrichment of retinal glycoproteins by ConA affinity is an effective tool to detect autoantigen candidates among membrane proteins. In 1D Western blots, the glycoprotein preparation allowed detection of IgG reactions to low abundant proteins in sera of ERU patients. Synaptotagmin-1, a Ca2+-sensing protein in synaptic vesicles, was identified as autoantigen candidate from the pre-enriched glycoprotein fraction by mass spectrometry and was validated as a highly prevalent autoantigen by enzyme-linked immunosorbent assay. Analysis of Syt1 expression in retinas of ERU cases showed a downregulation in the majority of ERU affected retinas to 24%. Results pointed to a dysregulation of retinal neurotransmitter release in ERU. Identification of synaptotagmin-1, the first cell membrane associated autoantigen in this spontaneous autoimmune disease, demonstrated that examination of tissue fractions can lead to the discovery of previously undetected novel autoantigens. Further experiments will address its role in ERU pathology
Reading in two writing systems: Accommodation and assimilation of the brain's reading network
Bilingual reading can require more than knowing two languages. Learners must acquire also the writing conventions of their second language, which can differ in its deep mapping principles (writing system) and its visual configurations (script). We review ERP (event-related potential) and fMRI studies of both Chinese-English bilingualism and Chinese second language learning that bear on the system accommodation hypothesis: the neural networks acquired for one system must be modified to accommodate the demands of a new system. ERP bilingual studies demonstrate temporal indicators of the brain's experience with L1 and L2 and with the frequency of encounters of words in L2. ERP learning studies show that early visual processing differences between L1 and L2 diminish during a second term of study. fMRI studies of learning converge in finding that learners recruit bilateral occipital-temporal and also middle frontal areas when reading Chinese, similar to the pattern of native speakers and different from alphabetic reading. The evidence suggests an asymmetry: alphabetic readers have a neural network that accommodates the demands of Chinese by recruiting neural structures less needed for alphabetic reading. Chinese readers have a neural network that partly assimilates English into the Chinese system, especially in the visual stages of word identification. © Cambridge University Press 2007.published_or_final_versio
Room temperature "optical nanodiamond hyperpolarizer": Physics, design, and operation.
Dynamic Nuclear Polarization (DNP) is a powerful suite of techniques that deliver multifold signal enhancements in nuclear magnetic resonance (NMR) and MRI. The generated athermal spin states can also be exploited for quantum sensing and as probes for many-body physics. Typical DNP methods require the use of cryogens, large magnetic fields, and high power microwave excitation, which are expensive and unwieldy. Nanodiamond particles, rich in Nitrogen-Vacancy (NV) centers, have attracted attention as alternative DNP agents because they can potentially be optically hyperpolarized at room temperature. Here, unraveling new physics underlying an optical DNP mechanism first introduced by Ajoy et al. [Sci. Adv. 4, eaar5492 (2018)], we report the realization of a miniature "optical nanodiamond hyperpolarizer," where 13C nuclei within the diamond particles are hyperpolarized via the NV centers. The device occupies a compact footprint and operates at room temperature. Instrumental requirements are very modest: low polarizing fields, low optical and microwave irradiation powers, and convenient frequency ranges that enable miniaturization. We obtain the best reported optical 13C hyperpolarization in diamond particles exceeding 720 times of the thermal 7 T value (0.86% bulk polarization), corresponding to a ten-million-fold gain in averaging time to detect them by NMR. In addition, the hyperpolarization signal can be background-suppressed by over two-orders of magnitude, retained for multiple-minute long periods at low fields, and deployed efficiently even to 13C enriched particles. Besides applications in quantum sensing and bright-contrast MRI imaging, this work opens possibilities for low-cost room-temperature DNP platforms that relay the 13C polarization to liquids in contact with the high surface-area particles
Startup of the High-Intensity Ultracold Neutron Source at the Paul Scherrer Institute
Ultracold neutrons (UCN) can be stored in suitable bottles and observed for
several hundreds of seconds. Therefore UCN can be used to study in detail the
fundamental properties of the neutron. A new user facility providing ultracold
neutrons for fundamental physics research has been constructed at the Paul
Scherrer Institute, the PSI UCN source. Assembly of the facility finished in
December 2010 with the first production of ultracold neutrons. Operation
approval was received in June 2011. We give an overview of the source and the
status at startup.Comment: Proceedings of the International Conference on Exotic Atoms and
Related Topics - EXA2011 September 5-9, 2011 Austrian Academy of Sciences,
Theatersaal, Sonnenfelsgasse 19, 1010 Wien, Austria 6 pages, 3 figure
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