22 resultados para Disease assessment


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Bovine tuberculosis (bTB) caused by infection with Mycobacterium bovis is causing considerable economic loss to farmers and Government in the United Kingdom as its incidence is increasing. Efforts to control bTB in the UK are hampered by the infection in Eurasian badgers (Metes metes) that represent a wildlife reservoir and source of recurrent M. bovis exposure to cattle. Vaccination of badgers with the human TB vaccine, M. bovis Bacille Calmette-Guerin (BCG), in oral bait represents a possible disease control tool and holds the best prospect for reaching badger populations over a wide geographical area. Using mouse and guinea pig models, we evaluated the immunogenicity and protective efficacy, respectively, of candidate badger oral vaccines based on formulation of BCG in lipid matrix, alginate beads, or a novel microcapsular hybrid of both lipid and alginate. Two different oral doses of BCG were evaluated in each formulation for their protective efficacy in guinea pigs, while a single dose was evaluated in mice. In mice, significant immune responses (based on lymphocyte proliferation and expression of IFN-gamma) were only seen with the lipid matrix and the lipid in alginate microcapsular formulation, corresponding to the isolation of viable BCG from alimentary tract lymph nodes. In guinea pigs, only BCG formulated in lipid matrix conferred protection to the spleen and lungs following aerosol route challenge with M. bovis. Protection was seen with delivery doses in the range 10(6)-10(7) CFU, although this was more consistent in the spleen at the higher dose. No protection in terms of organ CFU was seen with BCG administered in alginate beads or in lipid in alginate microcapsules, although 10(7) in the latter formulation conferred protection in terms of increasing body weight after challenge and a smaller lung to body weight ratio at necropsy. These results highlight the potential for lipid, rather than alginate, -based vaccine formulations as suitable delivery vehicles for an oral BCG vaccine in badgers.

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We present an assessment of the practical value of existing traditional and non-standard measures for discriminating healthy people from people with Parkinson's disease (PD) by detecting dysphonia. We introduce a new measure of dysphonia, Pitch Period Entropy (PPE), which is robust to many uncontrollable confounding effects including noisy acoustic environments and normal, healthy variations in voice frequency. We collected sustained phonations from 31 people, 23 with PD. We then selected 10 highly uncorrelated measures, and an exhaustive search of all possible combinations of these measures finds four that in combination lead to overall correct classification performance of 91.4%, using a kernel support vector machine. In conclusion, we find that non-standard methods in combination with traditional harmonics-to-noise ratios are best able to separate healthy from PD subjects. The selected non-standard methods are robust to many uncontrollable variations in acoustic environment and individual subjects, and are thus well-suited to telemonitoring applications.

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The standard reference clinical score quantifying average Parkinson's disease (PD) symptom severity is the Unified Parkinson's Disease Rating Scale (UPDRS). At present, UPDRS is determined by the subjective clinical evaluation of the patient's ability to adequately cope with a range of tasks. In this study, we extend recent findings that UPDRS can be objectively assessed to clinically useful accuracy using simple, self-administered speech tests, without requiring the patient's physical presence in the clinic. We apply a wide range of known speech signal processing algorithms to a large database (approx. 6000 recordings from 42 PD patients, recruited to a six-month, multi-centre trial) and propose a number of novel, nonlinear signal processing algorithms which reveal pathological characteristics in PD more accurately than existing approaches. Robust feature selection algorithms select the optimal subset of these algorithms, which is fed into non-parametric regression and classification algorithms, mapping the signal processing algorithm outputs to UPDRS. We demonstrate rapid, accurate replication of the UPDRS assessment with clinically useful accuracy (about 2 UPDRS points difference from the clinicians' estimates, p < 0.001). This study supports the viability of frequent, remote, cost-effective, objective, accurate UPDRS telemonitoring based on self-administered speech tests. This technology could facilitate large-scale clinical trials into novel PD treatments.

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Background: Parkinson’s disease (PD) is an incurable neurological disease with approximately 0.3% prevalence. The hallmark symptom is gradual movement deterioration. Current scientific consensus about disease progression holds that symptoms will worsen smoothly over time unless treated. Accurate information about symptom dynamics is of critical importance to patients, caregivers, and the scientific community for the design of new treatments, clinical decision making, and individual disease management. Long-term studies characterize the typical time course of the disease as an early linear progression gradually reaching a plateau in later stages. However, symptom dynamics over durations of days to weeks remains unquantified. Currently, there is a scarcity of objective clinical information about symptom dynamics at intervals shorter than 3 months stretching over several years, but Internet-based patient self-report platforms may change this. Objective: To assess the clinical value of online self-reported PD symptom data recorded by users of the health-focused Internet social research platform PatientsLikeMe (PLM), in which patients quantify their symptoms on a regular basis on a subset of the Unified Parkinson’s Disease Ratings Scale (UPDRS). By analyzing this data, we aim for a scientific window on the nature of symptom dynamics for assessment intervals shorter than 3 months over durations of several years. Methods: Online self-reported data was validated against the gold standard Parkinson’s Disease Data and Organizing Center (PD-DOC) database, containing clinical symptom data at intervals greater than 3 months. The data were compared visually using quantile-quantile plots, and numerically using the Kolmogorov-Smirnov test. By using a simple piecewise linear trend estimation algorithm, the PLM data was smoothed to separate random fluctuations from continuous symptom dynamics. Subtracting the trends from the original data revealed random fluctuations in symptom severity. The average magnitude of fluctuations versus time since diagnosis was modeled by using a gamma generalized linear model. Results: Distributions of ages at diagnosis and UPDRS in the PLM and PD-DOC databases were broadly consistent. The PLM patients were systematically younger than the PD-DOC patients and showed increased symptom severity in the PD off state. The average fluctuation in symptoms (UPDRS Parts I and II) was 2.6 points at the time of diagnosis, rising to 5.9 points 16 years after diagnosis. This fluctuation exceeds the estimated minimal and moderate clinically important differences, respectively. Not all patients conformed to the current clinical picture of gradual, smooth changes: many patients had regimes where symptom severity varied in an unpredictable manner, or underwent large rapid changes in an otherwise more stable progression. Conclusions: This information about short-term PD symptom dynamics contributes new scientific understanding about the disease progression, currently very costly to obtain without self-administered Internet-based reporting. This understanding should have implications for the optimization of clinical trials into new treatments and for the choice of treatment decision timescales.

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Despite improvements in interventional and pharmacological therapy of atherosclerotic disease, it is still the leading cause of death in the developed world. Hence, there is a need for further development of effective therapeutic approaches. This requires better understanding of the molecular mechanisms and pathophysiology of the disease. Atherosclerosis has long been identified as having an inflammatory component contributing to its pathogenesis, whereas the available therapy primarily targets hyperlipidemia and prevention of thrombosis. Notwithstanding a pleotropic anti-inflammatory effect to some therapies, such as acetyl salicylic acid and the statins, none of the currently approved medicines for management of either stable or complicated atherosclerosis has inflammation as a primary target. Monocytes, as representatives of the innate immune system, play a major role in the initiation, propagation, and progression of atherosclerosis from a stable to an unstable state. Experimental data support a role of monocytes in acute coronary syndromes and in outcome post-infarction; however, limited research has been done in humans. Analysis of expression of various cell surface receptors allows characterization of the different monocyte subsets phenotypically, whereas downstream assessment of inflammatory pathways provides an insight into their activity. In this review we discuss the functional role of monocytes and their different subpopulations in atherosclerosis, acute coronary syndromes, cardiac healing, and recovery with an aim of critical evaluation of potential future therapeutic targets in atherosclerosis and its complications. We will also discuss technical difficulties of delineating different monocyte subpopulations, understanding their differentiation potential and function.

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Introduction: Serum concentrations of polyclonal free light chains (FLC) represent the activity of the adaptive immune system. This study assessed the relationship between polyclonal FLC and the established marker of innate immunity, C-reactive protein (CRP), in chronic and acute disease. Methods: We utilized four cross-sectional chronic disease patient cohorts: chronic kidney disease (CKD), diabetes, vasculitis and kidney transplantation; and a longitudinal intensive care case series to assess the kinetics of production in acute disease. Results: There was a weak association between polyclonal FLC and high-sensitivity CRP (hs-CRP) in the study cohorts. A longitudinal assessment in acute disease showed a gradual increase in FLC concentrations over time, often when CRP levels were falling, demonstrating clear differences in the response kinetics of CRP and FLC in this setting. Conclusion: Polyclonal FLC and hs-CRP provide independent information as to inflammatory status. Prospective studies are now required to assess the utility of hs-CRP and polyclonal FLC in combination for risk stratification in disease populations. © 2013 John Wiley & Sons Ltd.

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Purpose: To to evaluate the benefit of bilinear and linear fitting to characterize the retinal vessel dilation to flicker light stimulation for the purpose of risk stratification in cardiovascular disease. Methods: Forty-five patients (15 with coronary artery disease (CAD), 15 with Diabetes Mellitus (DM) and 15 with CAD and DM) all underwent contact tonometry, digital blood pressure measurement, fundus photography, retinal vessel oximetry, static retinal vessel analysis and continous retinal diameter assessment using the retinal vessel analyser (and flicker light provocation). In addition we measured blood glucose (HbA1c) and keratinin levels in DM patients. Results: With increased severity of cardiovascular disease a more linear reaction profile of retinal arteriolar diameter to flicker light provocation can be observed. Conclusion: Absolute values of vessel dilation provide only limited information on the state of retinal arteriolar dilatory response to flicker light. The approach of bilinear fitting takes into account the immediate response to flicker light provocation as well as the maintained dilatory capacity during prolonged stimulation. Individuals with cardiovascular disease however show a largely linear reaction profile indicating an impairment of the initial rapid dilatory response as usually observed in healty individuals