Factors affecting mortality in late stage Parkinson’s Disease

To determine the effect of dysphagia and hospital admissions on mortality in late stage Parkinson’s disease

Trade and Investment in Central and Eastern Europe: A Bibliographic Survey of Current Literature in English

The year 1989 will be remembered as an important year in the histories of the Central and Eastern European countries because of the demise of the Soviet-controlled regimes and the emergence of independent and largely pluralistic political movements. A major catalyst for such radical political change was the decline of the centralized command economies in the Central and Eastern European countries. These so-called Soviet Bloc countries modeled their economic systems after the Soviet Union and, like the Soviet model, these countries found themselves saddled with an increasingly inefficient economic system. When the political systems changed, the new governments immediately took steps to change their economic situation through decentralization, establishing market mechanisms, and privatization. Aware that any improvement required international capital and technology assistance in addition to the development of export markets in the West, they also set out to reshape their foreign trade and investment mechanisms. Their goal was to liberalize foreign trade and open their economies to foreign investment and acquisitions

A Chemical Composition Survey of the Iron-Complex Globular Cluster NGC 6273 (M 19)

Recent observations have shown that a growing number of the most massive Galactic globular clusters contain multiple populations of stars with different [Fe/H] and neutron-capture element abundances. NGC 6273 has only recently been recognized as a member of this "iron-complex" cluster class, and we provide here a chemical and kinematic analysis of > 300 red giant branch (RGB) and asymptotic giant branch (AGB) member stars using high resolution spectra obtained with the Magellan-M2FS and VLT-FLAMES instruments. Multiple lines of evidence indicate that NGC 6273 possesses an intrinsic metallicity spread that ranges from about [Fe/H] = -2 to -1 dex, and may include at least three populations with different [Fe/H] values. The three populations identified here contain separate first (Na/Al-poor) and second (Na/Al-rich) generation stars, but a Mg-Al anti-correlation may only be present in stars with [Fe/H] > -1.65. The strong correlation between [La/Eu] and [Fe/H] suggests that the s-process must have dominated the heavy element enrichment at higher metallicities. A small group of stars with low [alpha/Fe] is identified and may have been accreted from a former surrounding field star population. The cluster's large abundance variations are coupled with a complex, extended, and multimodal blue horizontal branch (HB). The HB morphology and chemical abundances suggest that NGC 6273 may have an origin that is similar to omega Cen and M 54.Comment: Accepted for Publication in The Astrophysical Journal; 50 pages; 18 figures; 8 tables; higher resolution figures are available upon request or in the published journal articl

Prediction under Latent Subgroup Shifts with High-Dimensional Observations

We introduce a new approach to prediction in graphical models with latent-shift adaptation, i.e., where source and target environments differ in the distribution of an unobserved confounding latent variable. Previous work has shown that as long as "concept" and "proxy" variables with appropriate dependence are observed in the source environment, the latent-associated distributional changes can be identified, and target predictions adapted accurately. However, practical estimation methods do not scale well when the observations are complex and high-dimensional, even if the confounding latent is categorical. Here we build upon a recently proposed probabilistic unsupervised learning framework, the recognition-parametrised model (RPM), to recover low-dimensional, discrete latents from image observations. Applied to the problem of latent shifts, our novel form of RPM identifies causal latent structure in the source environment, and adapts properly to predict in the target. We demonstrate results in settings where predictor and proxy are high-dimensional images, a context to which previous methods fail to scale

Unsupervised representation learning with recognition-parametrised probabilistic models

We introduce a new approach to probabilistic unsupervised learning based on the recognition-parametrised model (RPM): a normalised semi-parametric hypothesis class for joint distributions over observed and latent variables. Under the key assumption that observations are conditionally independent given latents, the RPM combines parametric prior and observation-conditioned latent distributions with non-parametric observation marginals. This approach leads to a flexible learnt recognition model capturing latent dependence between observations, without the need for an explicit, parametric generative model. The RPM admits exact maximum-likelihood learning for discrete latents, even for powerful neural-network-based recognition. We develop effective approximations applicable in the continuous-latent case. Experiments demonstrate the effectiveness of the RPM on high-dimensional data, learning image classification from weak indirect supervision; direct image-level latent Dirichlet allocation; and recognition-parametrised Gaussian process factor analysis (RP-GPFA) applied to multi-factorial spatiotemporal datasets. The RPM provides a powerful framework to discover meaningful latent structure underlying observational data, a function critical to both animal and artificial intelligence

Unlocking biomarker discovery: Large scale application of aptamer proteomic technology for early detection of lung cancer

Lung cancer is the leading cause of cancer deaths, because ~84% of cases are diagnosed at an advanced stage. Worldwide in 2008, ~1.5 million people were diagnosed and ~1.3 million died – a survival rate unchanged since 1960. However, patients diagnosed at an early stage and have surgery experience an 86% overall 5-year survival. New diagnostics are therefore needed to identify lung cancer at this stage. Here we present the first large scale clinical use of aptamers to discover blood protein biomarkers in disease with our breakthrough proteomic technology. This multi-center case-control study was conducted in archived samples from 1,326 subjects from four independent studies of non-small cell lung cancer (NSCLC) in long-term tobacco-exposed populations. We measured >800 proteins in 15uL of serum, identified 44 candidate biomarkers, and developed a 12-protein panel that distinguished NSCLC from controls with 91% sensitivity and 84% specificity in a training set and 89% sensitivity and 83% specificity in a blinded, independent verification set. Performance was similar for early and late stage NSCLC. This is a significant advance in proteomics in an area of high clinical need

Reproducibility of ambulatory blood pressure changes from the initial values on two different days

OBJECTIVE: We tested the reproducibility of changes in the ambulatory blood pressure (BP) from the initial values, an indicator of BP reactivity and cardiovascular health outcomes, in young, healthy adults. METHOD: The subjects wore an ambulatory BP monitor attached by the same investigator at the same time of day until the next morning on two different days (day 1 and day 2) separated by a week. We compared the ambulatory BP change from the initial values at hourly intervals over 24 waking and sleeping hours on days 1 and 2 using linear regression and repeated measures analysis of covariance. RESULTS: The subjects comprised 88 men and 57 women (mean age±SE 22.4±0.3 years) with normal BP (118.3±0.9/69.7±0.6 mmHg). For the total sample, the correlation between the ambulatory BP change on day 1 vs. day 2 over 24, waking, and sleeping hours ranged from 0.37-0.61; among women, the correlation was 0.38-0.71, and among men, it was 0.24-0.52. Among women, the ambulatory systolic/diastolic BP change was greater by 3.1±1.0/2.4±0.8 mmHg over 24 hours and by 3.0±1.1/2.4±0.8 mmHg over waking hours on day 1 than on day 2. The diastolic ambulatory BP change during sleeping hours was greater by 2.2±0.9 mmHg on day 1 than on day 2, but the systolic ambulatory BP change during sleeping hours on days 1 and 2 did not differ. Among men, the ambulatory BP change on days 1 and 2 did not differ. CONCLUSION: Our primary findings were that the ambulatory BP change from the initial values was moderately reproducible; however, it was more reproducible in men than in women. These results suggest that women, but not men, may experience an alerting reaction to initially wearing the ambulatory BP monitor