791 research outputs found

    Automated, high accuracy classification of Parkinsonian disorders: a pattern recognition approach

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    Progressive supranuclear palsy (PSP), multiple system atrophy (MSA) and idiopathic Parkinson’s disease (IPD) can be clinically indistinguishable, especially in the early stages, despite distinct patterns of molecular pathology. Structural neuroimaging holds promise for providing objective biomarkers for discriminating these diseases at the single subject level but all studies to date have reported incomplete separation of disease groups. In this study, we employed multi-class pattern recognition to assess the value of anatomical patterns derived from a widely available structural neuroimaging sequence for automated classification of these disorders. To achieve this, 17 patients with PSP, 14 with IPD and 19 with MSA were scanned using structural MRI along with 19 healthy controls (HCs). An advanced probabilistic pattern recognition approach was employed to evaluate the diagnostic value of several pre-defined anatomical patterns for discriminating the disorders, including: (i) a subcortical motor network; (ii) each of its component regions and (iii) the whole brain. All disease groups could be discriminated simultaneously with high accuracy using the subcortical motor network. The region providing the most accurate predictions overall was the midbrain/brainstem, which discriminated all disease groups from one another and from HCs. The subcortical network also produced more accurate predictions than the whole brain and all of its constituent regions. PSP was accurately predicted from the midbrain/brainstem, cerebellum and all basal ganglia compartments; MSA from the midbrain/brainstem and cerebellum and IPD from the midbrain/brainstem only. This study demonstrates that automated analysis of structural MRI can accurately predict diagnosis in individual patients with Parkinsonian disorders, and identifies distinct patterns of regional atrophy particularly useful for this process

    Cortical thickness, surface area and volume measures in Parkinson's disease, multiple system atrophy and progressive supranuclear palsy

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    OBJECTIVE Parkinson's disease (PD), Multiple System Atrophy (MSA) and Progressive Supranuclear Palsy (PSP) are neurodegenerative diseases that can be difficult to distinguish clinically. The objective of the current study was to use surface-based analysis techniques to assess cortical thickness, surface area and grey matter volume to identify unique morphological patterns of cortical atrophy in PD, MSA and PSP and to relate these patterns of change to disease duration and clinical features. METHODS High resolution 3D T1-weighted MRI volumes were acquired from 14 PD patients, 18 MSA, 14 PSP and 19 healthy control participants. Cortical thickness, surface area and volume analyses were carried out using the automated surface-based analysis package FreeSurfer (version 5.1.0). Measures of disease severity and duration were assessed for correlation with cortical morphometric changes in each clinical group. RESULTS Results show that in PSP, widespread cortical thinning and volume loss occurs within the frontal lobe, particularly the superior frontal gyrus. In addition, PSP patients also displayed increased surface area in the pericalcarine. In comparison, PD and MSA did not display significant changes in cortical morphology. CONCLUSION These results demonstrate that patients with clinically established PSP exhibit distinct patterns of cortical atrophy, particularly affecting the frontal lobe. These results could be used in the future to develop a useful clinical application of MRI to distinguish PSP patients from PD and MSA patients

    Diffusion tensor imaging of Parkinson's disease, multiple system atrophy and progressive supranuclear palsy: a tract-based spatial statistics study

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    Although often clinically indistinguishable in the early stages, Parkinson's disease (PD), Multiple System Atrophy (MSA) and Progressive Supranuclear Palsy (PSP) have distinct neuropathological changes. The aim of the current study was to identify white matter tract neurodegeneration characteristic of each of the three syndromes. Tract-based spatial statistics (TBSS) was used to perform a whole-brain automated analysis of diffusion tensor imaging (DTI) data to compare differences in fractional anisotropy (FA) and mean diffusivity (MD) between the three clinical groups and healthy control subjects. Further analyses were conducted to assess the relationship between these putative indices of white matter microstructure and clinical measures of disease severity and symptoms. In PSP, relative to controls, changes in DTI indices consistent with white matter tract degeneration were identified in the corpus callosum, corona radiata, corticospinal tract, superior longitudinal fasciculus, anterior thalamic radiation, superior cerebellar peduncle, medial lemniscus, retrolenticular and anterior limb of the internal capsule, cerebral peduncle and external capsule bilaterally, as well as the left posterior limb of the internal capsule and the right posterior thalamic radiation. MSA patients also displayed differences in the body of the corpus callosum corticospinal tract, cerebellar peduncle, medial lemniscus, anterior and superior corona radiata, posterior limb of the internal capsule external capsule and cerebral peduncle bilaterally, as well as the left anterior limb of the internal capsule and the left anterior thalamic radiation. No significant white matter abnormalities were observed in the PD group. Across groups, MD correlated positively with disease severity in all major white matter tracts. These results show widespread changes in white matter tracts in both PSP and MSA patients, even at a mid-point in the disease process, which are not found in patients with PD

    Diagnostic applications of molecular and serological assays for bluetongue and African horse sickness

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    The availability of rapid, highly sensitive and specific molecular and serologic diagnostic assays, such as competitive enzyme-linked immunosorbent assay (cELISA), has expedited the diagnosis of emerging transboundary animal diseases, including bluetongue (BT) and African horse sickness (AHS), and facilitated more thorough characterisation of their epidemiology. The development of assays based on real-time, reverse-transcription polymerase chain reaction (RT-PCR) to detect and identify the numerous serotypes of BT virus (BTV) and AHS virus (AHSV) has aided in-depth studies of the epidemiology of BTV infection in California and AHSV infection in South Africa. The subsequent evaluation of pan-serotype, real-time, RT-PCR-positive samples through the use of serotype-specific RT-PCR assays allows the rapid identification of virus serotypes, reducing the need for expensive and time-consuming conventional methods, such as virus isolation and serotype-specific virus neutralisation assays. These molecular assays and cELISA platforms provide tools that have enhanced epidemiologic surveillance strategies and improved our understanding of potentially altered Culicoides midge behaviour when infected with BTV. They have also supported the detection of subclinical AHSV infection of vaccinated horses in South Africa. Moreover, in conjunction with whole genome sequence analysis, these tests have clarified that the mechanism behind recent outbreaks of AHS in the AHS-controlled area of South Africa was the result of the reversion to virulence and/or genome reassortment of live attenuated vaccine viruses. This review focuses on the use of contemporary molecular diagnostic assays in the context of recent epidemiologic studies and explores their advantages over historic virus isolation and serologic techniques.https://www.woah.org/en/what-we-do/publications/scientific-and-technical-reviewVeterinary Tropical Disease

    Maternal Postpartum Distress and Childhood Overweight

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    OBJECTIVE: We investigated associations between maternal postpartum distress covering anxiety, depression and stress and childhood overweight. METHODS: We performed a prospective cohort study, including 21,121 mother-child-dyads from the Danish National Birth Cohort (DNBC). Maternal distress was measured 6 months postpartum by 9 items covering anxiety, depression and stress. Outcome was childhood overweight at 7-years-of age. Multiple logistic regression analyses were performed and information on maternal age, socioeconomic status, pre-pregnancy BMI, gestational weight gain, parity, smoking during pregnancy, paternal BMI, birth weight, gestational age at birth, sex, breastfeeding and finally infant weight at 5 and 12 month were included in the analyses. RESULTS: We found, that postpartum distress was not associated with childhood risk of overweight, OR 1.00, 95%CI [0.98-1.02]. Neither was anxiety, depression, or stress exposure, separately. There were no significant differences between the genders. Adjustment for potential confounders did not alter the results. CONCLUSION: Maternal postpartum distress is apparently not an independent risk factor for childhood overweight at 7-years-of-age. However, we can confirm previous findings of perinatal determinants as high maternal pre-pregnancy BMI, and smoking during pregnancy being risk factors for childhood overweight

    Fetal Growth versus Birthweight: The Role of Placenta versus Other Determinants

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    in utero. We aimed to study the effects of maternal characteristics on both birthweight and fetal growth in third trimester and introduce placental weight as a possible determinant of both birthweight and fetal growth in third trimester.The STORK study is a prospective cohort study including 1031 healthy pregnant women of Scandinavian heritage with singleton pregnancies. Maternal determinants (age, parity, body mass index (BMI), gestational weight gain and fasting plasma glucose) of birthweight and fetal growth estimated by biometric ultrasound measures were explored by linear regression models. Two models were fitted, one with only maternal characteristics and one which included placental weight.Placental weight was a significant determinant of birthweight. Parity, BMI, weight gain and fasting glucose remained significant when adjusted for placental weight. Introducing placental weight as a covariate reduced the effect estimate of the other variables in the model by 62% for BMI, 40% for weight gain, 33% for glucose and 22% for parity. Determinants of fetal growth were parity, BMI and weight gain, but not fasting glucose. Placental weight was significant as an independent variable. Parity, BMI and weight gain remained significant when adjusted for placental weight. Introducing placental weight reduced the effect of BMI on fetal growth by 23%, weight gain by 14% and parity by 17%.In conclusion, we find that placental weight is an important determinant of both birthweight and fetal growth. Our findings indicate that placental weight markedly modifies the effect of maternal determinants of both birthweight and fetal growth. The differential effect of third trimester glucose on birthweight and growth parameters illustrates that birthweight and fetal growth are not identical entities

    Optimasi Portofolio Resiko Menggunakan Model Markowitz MVO Dikaitkan dengan Keterbatasan Manusia dalam Memprediksi Masa Depan dalam Perspektif Al-Qur`an

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    Risk portfolio on modern finance has become increasingly technical, requiring the use of sophisticated mathematical tools in both research and practice. Since companies cannot insure themselves completely against risk, as human incompetence in predicting the future precisely that written in Al-Quran surah Luqman verse 34, they have to manage it to yield an optimal portfolio. The objective here is to minimize the variance among all portfolios, or alternatively, to maximize expected return among all portfolios that has at least a certain expected return. Furthermore, this study focuses on optimizing risk portfolio so called Markowitz MVO (Mean-Variance Optimization). Some theoretical frameworks for analysis are arithmetic mean, geometric mean, variance, covariance, linear programming, and quadratic programming. Moreover, finding a minimum variance portfolio produces a convex quadratic programming, that is minimizing the objective function ðð¥with constraintsð ð 𥠥 ðandð´ð¥ = ð. The outcome of this research is the solution of optimal risk portofolio in some investments that could be finished smoothly using MATLAB R2007b software together with its graphic analysis

    Genome-wide association identifies nine common variants associated with fasting proinsulin levels and provides new insights into the pathophysiology of type 2 diabetes.

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    OBJECTIVE: Proinsulin is a precursor of mature insulin and C-peptide. Higher circulating proinsulin levels are associated with impaired β-cell function, raised glucose levels, insulin resistance, and type 2 diabetes (T2D). Studies of the insulin processing pathway could provide new insights about T2D pathophysiology. RESEARCH DESIGN AND METHODS: We have conducted a meta-analysis of genome-wide association tests of ∼2.5 million genotyped or imputed single nucleotide polymorphisms (SNPs) and fasting proinsulin levels in 10,701 nondiabetic adults of European ancestry, with follow-up of 23 loci in up to 16,378 individuals, using additive genetic models adjusted for age, sex, fasting insulin, and study-specific covariates. RESULTS: Nine SNPs at eight loci were associated with proinsulin levels (P < 5 × 10(-8)). Two loci (LARP6 and SGSM2) have not been previously related to metabolic traits, one (MADD) has been associated with fasting glucose, one (PCSK1) has been implicated in obesity, and four (TCF7L2, SLC30A8, VPS13C/C2CD4A/B, and ARAP1, formerly CENTD2) increase T2D risk. The proinsulin-raising allele of ARAP1 was associated with a lower fasting glucose (P = 1.7 × 10(-4)), improved β-cell function (P = 1.1 × 10(-5)), and lower risk of T2D (odds ratio 0.88; P = 7.8 × 10(-6)). Notably, PCSK1 encodes the protein prohormone convertase 1/3, the first enzyme in the insulin processing pathway. A genotype score composed of the nine proinsulin-raising alleles was not associated with coronary disease in two large case-control datasets. CONCLUSIONS: We have identified nine genetic variants associated with fasting proinsulin. Our findings illuminate the biology underlying glucose homeostasis and T2D development in humans and argue against a direct role of proinsulin in coronary artery disease pathogenesis
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