1,593 research outputs found

    Splenic nerve bundle stimulation in acute and chronic inflammation

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    Splenic neurovascular bundle stimulation holds potential to treat acute and chronic inflammatory conditions. In the first part of the thesis, the available literature on the interactions between the immune system and nervous system in the intestine is summarized. Then, it is shown that a specialized T-cell, that can produce the neurotransmitter acetylcholine, resides in the gut an plays a dual role in the development of experimental colitis in mice. Furthermore, electrical splenic neurovascular bundle stimulation ameliorated the outcomes of colitis in mice and reversed transcriptomic changes in the gut that were induced by colitis. The second part of the thesis focused on the translation of splenic neurovascular bundle stimulation to the human situation. It is shown that there are significant changes between murine and human innervation of the spleen. Using computed tomography (CT) images the course and the characteristics of the splenic artery were described. These data were used to develop a cuff electrode that could be used for electrical stimulation of the splenic neurovascular bundle in humans. Finally, it was demonstrated that splenic neurovascular bundle stimulation in humans was safe and feasible in a pilot study with patients that underwent esophagectomy

    Simultaneous Multiparametric and Multidimensional Cardiovascular Magnetic Resonance Imaging

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    Advances and Applications of DSmT for Information Fusion. Collected Works, Volume 5

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    This fifth volume on Advances and Applications of DSmT for Information Fusion collects theoretical and applied contributions of researchers working in different fields of applications and in mathematics, and is available in open-access. The collected contributions of this volume have either been published or presented after disseminating the fourth volume in 2015 in international conferences, seminars, workshops and journals, or they are new. The contributions of each part of this volume are chronologically ordered. First Part of this book presents some theoretical advances on DSmT, dealing mainly with modified Proportional Conflict Redistribution Rules (PCR) of combination with degree of intersection, coarsening techniques, interval calculus for PCR thanks to set inversion via interval analysis (SIVIA), rough set classifiers, canonical decomposition of dichotomous belief functions, fast PCR fusion, fast inter-criteria analysis with PCR, and improved PCR5 and PCR6 rules preserving the (quasi-)neutrality of (quasi-)vacuous belief assignment in the fusion of sources of evidence with their Matlab codes. Because more applications of DSmT have emerged in the past years since the apparition of the fourth book of DSmT in 2015, the second part of this volume is about selected applications of DSmT mainly in building change detection, object recognition, quality of data association in tracking, perception in robotics, risk assessment for torrent protection and multi-criteria decision-making, multi-modal image fusion, coarsening techniques, recommender system, levee characterization and assessment, human heading perception, trust assessment, robotics, biometrics, failure detection, GPS systems, inter-criteria analysis, group decision, human activity recognition, storm prediction, data association for autonomous vehicles, identification of maritime vessels, fusion of support vector machines (SVM), Silx-Furtif RUST code library for information fusion including PCR rules, and network for ship classification. Finally, the third part presents interesting contributions related to belief functions in general published or presented along the years since 2015. These contributions are related with decision-making under uncertainty, belief approximations, probability transformations, new distances between belief functions, non-classical multi-criteria decision-making problems with belief functions, generalization of Bayes theorem, image processing, data association, entropy and cross-entropy measures, fuzzy evidence numbers, negator of belief mass, human activity recognition, information fusion for breast cancer therapy, imbalanced data classification, and hybrid techniques mixing deep learning with belief functions as well

    2017 GREAT Day Program

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    SUNY Geneseo’s Eleventh Annual GREAT Day.https://knightscholar.geneseo.edu/program-2007/1011/thumbnail.jp

    Optimisation, evaluation and application of cerebrovascular reactivity measurement using magnetic resonance imaging in patients with cerebral small vessel disease

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    Small vessel disease (SVD) is a common cause of strokes and dementia. Currently, there are no treatments; therefore, developing and validating early biomarkers of disease progression and treatment response is important for future drug trials. Though SVD pathogenesis is not well understood, findings from previous studies suggest that blood-brain barrier dysfunction and impaired cerebrovascular reactivity (CVR) contribute to the disease. The latter can be measured in vivo using a vasoactive stimulus in parallel with magnetic resonance imaging (MRI) techniques sensitive to blood flow, such as blood oxygen level dependent (BOLD) contrast, and has frequently been assessed in patients with steno-occlusive diseases. However, it is unclear if the technique is reliable when investigating cerebrovascular health in deep structures of the brain where SVD is prevalent. Therefore, this thesis aimed to assess and optimise the reliability of CVR measurements and deepen our understanding of its role in SVD pathogenesis. A systematic review was performed to provide a detailed overview of CVR MRI methodologies and clinical applications, including SVD, present in the literature, which identified several acquisition and analysis methods, a need for greater standardisation and lack of data on reliability. Specifically in SVD research, there was limited application of CVR MRI in SVD populations, little optimisation and reliability assessment of CVR in deep brain structures relevant to SVD, such as in white and subcortical grey matter. Following those findings, the effects of voxel- and region-based analysis approaches on reliability of CVR estimates were investigated using simulations and test-retest data from healthy volunteers. Voxel-based CVR magnitude estimates in tissues with high noise levels were prone to bias, whereas biases in region-based estimates were independent of noise level, but consistently underestimated CVR magnitude relative to the ground-truth mean. Furthermore, the test-retest study confirmed the repeatability of CVR estimates from a BOLD-CVR experiment with fixed inhaled stimulus, although a systematic, but small, bias was detected due to habituation to the gas challenge. The data from healthy volunteers were further used to conduct a proof-of-concept and investigate the feasibility of extracting cerebral pulsatility from BOLD-CVR data. Small-to-moderate correlations with pulsatility from phase-contrast MRI were found depending on the regions considered. CVR pulsatility was also computed in a small cohort of SVD patients: it was higher than in healthy volunteers, but no associations were found with SVD burden. It was concluded that further optimisation and validation of the technique is needed before being suitable for clinical research. Following the optimisation of the CVR MRI technique, relationships between CVR and SVD neuroimaging features, cognition, stroke severity and outcome were investigated cross-sectionally and longitudinally in a cohort of patients with mild stroke. In the cross-sectional analysis, CVR impairment in normal-appearing and damaged tissues was associated with worse SVD burden and cognition deficit. Furthermore, the longitudinal analysis showed that baseline CVR impairment predicted worsening of white matter hyperintensity and perivascular space volumes after one year. In conclusion, assessment of CVR in the brain and its deeper structures was successfully conducted in healthy volunteers and patients with SVD using MRI. However, this required appropriate optimisation of processing strategy as the latter can affect accuracy of CVR parameters and inter-study comparability. Importantly, applying the technique in a cohort of SVD patients led to the findings that CVR impairment was related to worse SVD burden and is a potential marker of SVD severity and progression

    Disease progression and genetic risk factors in the primary tauopathies

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    The primary tauopathies are a group of progressive neurodegenerative diseases within the frontotemporal lobar degeneration spectrum (FTLD) characterised by the accumulation of misfolded, hyperphosphorylated microtubule-associated tau protein (MAPT) within neurons and glial cells. They can be classified according to the underlying ratio of three-repeat (3R) to four-repeat (4R) tau and include Pick’s disease (PiD), which is the only 3R tauopathy, and the 4R tauopathies the most common of which are progressive supranuclear palsy (PSP) and corticobasal degeneration (CBD). There are no disease modifying therapies currently available, with research complicated by the wide variability in clinical presentations for each underlying pathology, with presentations often overlapping, as well as the frequent occurrence of atypical presentations that may mimic other non-FTLD pathologies. Although progress has been made in understanding the genetic contribution to disease risk in the more common 4R tauopathies (PSP and CBD), very little is known about the genetics of the 3R tauopathy PiD. There are two broad aims to this thesis; firstly, to use data-driven generative models of disease progression to try and more accurately stage and subtype patients presenting with PSP and corticobasal syndrome (CBS, the most common presentation of CBD), and secondly to identify genetic drivers of disease risk and progression in PiD. Given the rarity of these disorders, as part of this PhD I had to assemble two large cohorts through international collaboration, the 4R tau imaging cohort and the Pick’s disease International Consortium (PIC), to build large enough sample sizes to enable the required analyses. In Chapter 3 I use a probabilistic event-based modelling (EBM) approach applied to structural MRI data to determine the sequence of brain atrophy changes in clinically diagnosed PSP - Richardson syndrome (PSP-RS). The sequence of atrophy predicted by the model broadly mirrors the sequential spread of tau pathology in PSP post-mortem staging studies, and has potential utility to stratify PSP patients on entry into clinical trials based on disease stage, as well as track disease progression. To better characterise the spatiotemporal heterogeneity of the 4R tauopathies, I go on to use Subtype and Stage Inference (SuStaIn), an unsupervised machine algorithm, to identify population subgroups with distinct patterns of atrophy in PSP (Chapter 4) and CBS (Chapter 5). The SuStaIn model provides data-driven evidence for the existence of two spatiotemporal subtypes of atrophy in clinically diagnosed PSP, giving insights into the relationship between pathology and clinical syndrome. In CBS I identify two distinct imaging subtypes that are differentially associated with underlying pathology, and potentially a third subtype that if confirmed in a larger dataset may allow the differentiation of CBD from both PSP and AD pathology using a baseline MRI scan. In Chapter 6 I investigate the association between the MAPT H1/H2 haplotype and PiD, showing for the first time that the H2 haplotype, known to be strongly protective against developing PSP or CBD, is associated with an increased risk of PiD. This is an important finding and has implications for the future development of MAPT isoform-specific therapeutic strategies for the primary tauopathies. In Chapter 7 I perform the first genome wide association study (GWAS) in PiD, identifying five genomic loci that are nominally associated with risk of disease. The top two loci implicate perturbed GABAergic signalling (KCTD8) and dysregulation of the ubiquitin proteosome system (TRIM22) in the pathogenesis of PiD. In the final chapter (Chapter 8) I investigate the genetic determinants of survival in PiD, by carrying out a Cox proportional hazards genome wide survival study (GWSS). I identify a genome-wide significant association with survival on chromosome 3, within the NLGN1 gene. which encodes a synaptic scaffolding protein located at the neuronal pre-synaptic membrane. Loss of synaptic integrity with resulting dysregulation of synaptic transmission leading to increased pathological tau accumulation is a plausible mechanism though which NLGN1 dysfunction could impact on survival in PiD
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