93 research outputs found

    Analysis of Surface Electromyography in Parkinson's Disease Using Time Frequency and Recurrence Quantification Methods

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    Bioengineering in Ireland 2015 Conference, Maynooth, Ireland, 16-17 January 2015The work presented here aims to establish the optimal RQA variables for the calculation of RQA parameters (REC, DET, JRP, etc.), and to apply these parameters to EMG data of Parkinson’s disease patients. Additionally, the cross-correlation of these parameters with time frequency features will be assessed with the intention of classifying Parkinson’s patients from healthy controls.Science Foundation Irelan

    Analysis of Parkinsonian Surface Electomyography Through Advanced Signal Processing and Nonlinear Methods

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    Bioengineering in Ireland Annual Conference, NUI Galway, Ireland, 22-23 January 2016Parkinson’s disease (PD) is a neurodegenerative disease that affects approx. 4% of people over 80 years of age [4]. The result of depleted dopaminergic neurons in the substantia nigra, PD is characterised with symptoms such as muscle rigidity, bradykinetic gait, and severe tremor. To distinguish Parkinsonian electromyographic (EMG) signals from those of healthy controls, recent studies have employed nonlinear methods which can capture the underlying activity of the neuromuscular system. Recurrence quantification analysis (RQA) has been shown to effectively characterise the degree of repeated synchronous structure in non-linear dynamical systems including parkinsonian EMG, through parameters such as determinism (%DET) and recurrence rate (%REC) [1]. Additional parameters such as intermuscular coherence and kurtosis have also been used to observe changes in EMG signals under various conditions [2,3]. To date, limited research has examined the potential to discern EMG of individuals with PD from healthy controls using RQA and intermuscular coherence. The work presented here aims to examine differences in Parkinsonian EMG from that of healthy controls using these measures

    Non-Linear Analyses of Surface Electromyography in Parkinsons Disease

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    Insight Student Conference 2015, NUIG, Galway, Ireland, 30 October 2015Non-linear measures, such as recurrence quantification analysis, have been applied to electromyographic (EMG) data to capture the underlying activity of the neuromuscular system. The application of such approaches to EMG data from individuals with Parkinson’s disease (PD) is presented here. Preliminary results indicate differences in the level of determinism and coherence that distinguish Parkinsonian EMG from that of healthy age-matched controls

    Histone H3K36 methylation regulates pre-mRNA splicing in Saccharomyces cerevisiae

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    Co-transcriptional splicing takes place in the context of a highly dynamic chromatin architecture, yet the role of chromatin restructuring in coordinating transcription with RNA splicing has not been fully resolved. To further define the contribution of histone modifications to pre-mRNA splicing in Saccharomyces cerevisiae, we probed a library of histone point mutants using a reporter to monitor pre-mRNA splicing. We found that mutation of H3 lysine 36 (H3K36) – a residue methylated by Set2 during transcription elongation – exhibited phenotypes similar to those of pre-mRNA splicing mutants. We identified genetic interactions between genes encoding RNA splicing factors and genes encoding the H3K36 methyltransferase Set2 and the demethylase Jhd1 as well as point mutations of H3K36 that block methylation. Consistent with the genetic interactions, deletion of SET2, mutations modifying the catalytic activity of Set2 or H3K36 point mutations significantly altered expression of our reporter and reduced splicing of endogenous introns. These effects were dependent on the association of Set2 with RNA polymerase II and H3K36 dimethylation. Additionally, we found that deletion of SET2 reduces the association of the U2 and U5 snRNPs with chromatin. Thus, our study provides the first evidence that H3K36 methylation plays a role in co-transcriptional RNA splicing in yeast

    Quantitative clinical assessment of motor function during and following LSVT-BIGÂź therapy

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    Background LSVT-BIG¼ is an intensively delivered, amplitude-oriented exercise therapy reported to improve mobility in individuals with Parkinson’s disease (PD). However, questions remain surrounding the efficacy of LSVT-BIG¼ when compared with similar exercise therapies. Instrumented clinical tests using body-worn sensors can provide a means to objectively monitor patient progression with therapy by quantifying features of motor function, yet research exploring the feasibility of this approach has been limited to date. The aim of this study was to use accelerometer-instrumented clinical tests to quantify features of gait, balance and fine motor control in individuals with PD, in order to examine motor function during and following LSVT-BIG¼ therapy. Methods Twelve individuals with PD undergoing LSVT-BIG¼ therapy, eight non-exercising PD controls and 14 healthy controls were recruited to participate in the study. Functional mobility was examined using features derived from accelerometry recorded during five instrumented clinical tests: 10 m walk, Timed-Up-and-Go, Sit-to-Stand, quiet stance, and finger tapping. PD subjects undergoing therapy were assessed before, each week during, and up to 13 weeks following LSVT-BIG¼. Results Accelerometry data captured significant improvements in 10 m walk and Timed-Up-and-Go times with LSVT-BIG¼ (p <  0.001), accompanied by increased stride length. Temporal features of the gait cycle were significantly lower following therapy, though no change was observed with measures of asymmetry or stride variance. The total number of Sit-to-Stand transitions significantly increased with LSVT-BIG¼ (p <  0.001), corresponding to a significant reduction of time spent in each phase of the Sit-to-Stand cycle. No change in measures related to postural or fine motor control was observed with LSVT-BIG¼. PD subjects undergoing LSVT-BIG¼ showed significant improvements in 10 m walk (p <  0.001) and Timed-Up-and-Go times (p = 0.004) over a four-week period when compared to non-exercising PD controls, who showed no week-to-week improvement in any task examined. Conclusions This study demonstrates the potential for wearable sensors to objectively quantify changes in motor function in response to therapeutic exercise interventions in PD. The observed improvements in accelerometer-derived features provide support for instrumenting gait and sit-to-stand tasks, and demonstrate a rescaling of the speed-amplitude relationship during gait in PD following LSVT-BIG¼.European Research CouncilScience Foundation IrelandInsight Research CentreThe Royal Hospital Donnybrook2020-10-06 JG: PDF replaced with correct versio

    Routine activities and proactive police activity: a macro-scale analysis of police searches in London and New York City

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    This paper explored how city-level changes in routine activities were associated with changes in frequencies of police searches using six years of police records from the London Metropolitan Police Service and the New York City Police Department. Routine activities were operationalised through selecting events that potentially impacted on (a) the street population, (b) the frequency of crime or (c) the level of police activity. OLS regression results indicated that routine activity variables (e.g. day of the week, periods of high demand for police service) can explain a large proportion of the variance in search frequency throughout the year. A complex set of results emerged, revealing cross-national dissimilarities and the differential impact of certain activities (e.g. public holidays). Importantly, temporal frequencies in searches are not reducible to associations between searches and recorded street crime, nor changes in on-street population. Based on the routine activity approach, a theoretical police-action model is proposed

    Large expert-curated database for benchmarking document similarity detection in biomedical literature search

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    Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe

    Global urban environmental change drives adaptation in white clover

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    Urbanization transforms environments in ways that alter biological evolution. We examined whether urban environmental change drives parallel evolution by sampling 110,019 white clover plants from 6169 populations in 160 cities globally. Plants were assayed for a Mendelian antiherbivore defense that also affects tolerance to abiotic stressors. Urban-rural gradients were associated with the evolution of clines in defense in 47% of cities throughout the world. Variation in the strength of clines was explained by environmental changes in drought stress and vegetation cover that varied among cities. Sequencing 2074 genomes from 26 cities revealed that the evolution of urban-rural clines was best explained by adaptive evolution, but the degree of parallel adaptation varied among cities. Our results demonstrate that urbanization leads to adaptation at a global scale
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