Disease Progression Modeling and Prediction through Random Effect Gaussian Processes and Time Transformation

The development of statistical approaches for the joint modelling of the temporal changes of imaging, biochemical, and clinical biomarkers is of paramount importance for improving the understanding of neurodegenerative disorders, and for providing a reference for the prediction and quantification of the pathology in unseen individuals. Nonetheless, the use of disease progression models for probabilistic predictions still requires investigation, for example for accounting for missing observations in clinical data, and for accurate uncertainty quantification. We tackle this problem by proposing a novel Gaussian process-based method for the joint modeling of imaging and clinical biomarker progressions from time series of individual observations. The model is formulated to account for individual random effects and time reparameterization, allowing non-parametric estimates of the biomarker evolution, as well as high flexibility in specifying correlation structure, and time transformation models. Thanks to the Bayesian formulation, the model naturally accounts for missing data, and allows for uncertainty quantification in the estimate of evolutions, as well as for probabilistic prediction of disease staging in unseen patients. The experimental results show that the proposed model provides a biologically plausible description of the evolution of Alzheimer's pathology across the whole disease time-span as well as remarkable predictive performance when tested on a large clinical cohort with missing observations.Comment: 13 pages, 2 figure

Elevated cystatin-C concentration is associated with progression to prediabetes: the Western New York Study

OBJECTIVE – We conducted a nested case-control investigation to examine if elevated baseline concentrations of cystatin-C predicted progression from normoglycaemia to prediabetes over 6 years of follow-up from the Western New York Health Study. RESEARCH DESIGN AND METHODS – 1,455 participants from the Western New York Health Study, free of type 2 diabetes and known cardiovascular disease at baseline (1996-2001), were reexamined in 2002-2004. An incident case of prediabetes was defined as one with fasting glucose below 100 mg/dl at the baseline examination and ≥ 100 mg/dl and ≤ 125 mg/dl at the follow-up examination. All cases (n=91) were matched 1:3 to control participants based upon sex, race/ethnicity and year of study enrollment. All controls had fasting glucose levels < 100 mg/dl at both baseline and follow-up examinations. Cystatin-C concentrations and the urinary albumin to creatinine ratio were measured from frozen (-196 Cº) baseline blood and urine samples. Serum creatinine concentrations were available from the baseline examination. RESULTS –Multivariate conditional logistic regression analyses adjusted for age, baseline glucose level, HOMA-IR, body mass index, hypertension, eGFR, cigarette smoking, and alcohol use revealed a significantly increased risk of progression to prediabetes among those with elevated baseline concentrations of cystatin-C (Odds Ratio, 95% CI: 3.04, 1.34, 6.89) (upper quintile vs. the remainder). Results of secondary analyses that considered hs-CRP, IL-6, E-selectin, or sICAM did not alter these results. CONCLUSIONS - These results suggest that early renal impairment indexed with cystatin-C imparted a three-fold excess risk of progression to prediabetes in this study population. Recent evidence from randomized clinical trials (1,2) among people with prediabetes have provided convincing evidence that early intervention can significantly delay or prevent the progression to type 2 diabetes. The identification of those with prediabetes is assuming greater importance (3) especially in light of the fact that approximately 35 million adults aged 40-74 years old in the United States have prediabetes defined as impaired fasting glucose (4). Microalbuminuria occurs frequently in nondiabetic subjects and places them at increased risk for cardiovascular disease (5-7). The mechanisms behind this observation are poorly understood, however. Albuminuria may reflect underlying vascular damage (8), hypertension (9, 10) endothelial dysfunction (11, 12) and/or low-grade inflammation (13). A large percentage of type 2 individuals pass through a period of prediabetes (14) and may experience early renal dysfunction e.g., a glomerular filtration rate (GFR) above 60 ml/minute per 1.73m2. Currently used estimating equations are poor at identifying early renal impairment and better indices are of great interest (15, 16). Recently, several studies have suggested that cystatin-C levels may be a more sensitive marker of early renal impairment than either albuminuria or serum creatinine concentration (17-20). Therefore, a better understanding of a putative role for cystatin-C in the etiology of prediabetes could shed light on the renal/heart disease connection (21). Given the reported superiority of cystatin C over conventional measures of renal function, we hypothesized that cystatin-C would predict progression to prediabetes independent of serum creatinine or estimated GFR. We also investigated the role of intervening mechanisms including hypertension, insulin resistance, endothelial dysfunction and inflammation

Exact solution of a 2d random Ising model

The model considered is a d=2 layered random Ising system on a square lattice with nearest neighbours interaction. It is assumed that all the vertical couplings are equal and take the positive value J while the horizontal couplings are quenched random variables which are equal in the same row but can take the two possible values J and J-K in different rows. The exact solution is obtained in the limit case of infinite K for any distribution of the horizontal couplings. The model which corresponds to this limit can be seen as an ordinary Ising system where the spins of some rows, chosen at random, are frozen in an antiferromagnetic order. No phase transition is found if the horizontal couplings are independent random variables while for correlated disorder one finds a low temperature phase with some glassy properties.Comment: 10 pages, Plain TeX, 3 ps figures, submitted to Europhys. Let

Numerical Simulation of Turbulent Duct Flows with Constant Power Input

The numerical simulation of a flow through a duct requires an externally specified forcing that makes the fluid flow against viscous friction. To this end, it is customary to enforce a constant value for either the flow rate (CFR) or the pressure gradient (CPG). When comparing a laminar duct flow before and after a geometrical modification that induces a change of the viscous drag, both approaches lead to a change of the power input across the comparison. Similarly, when carrying out direct numerical simulation or large-eddy simulation of unsteady turbulent flows, the power input is not constant over time. Carrying out a simulation at constant power input (CPI) is thus a further physically sound option, that becomes particularly appealing in the context of flow control, where a comparison between control-on and control-off conditions has to be made. We describe how to carry out a CPI simulation, and start with defining a new power-related Reynolds number, whose velocity scale is the bulk flow that can be attained with a given pumping power in the laminar regime. Under the CPI condition, we derive a relation that is equivalent to the Fukagata-Iwamoto-Kasagi relation valid for CFR (and to its extension valid for CPG), that presents the additional advantage of naturally including the required control power. The implementation of the CPI approach is then exemplified in the standard case of a plane turbulent channel flow, and then further applied to a flow control case, where a spanwise-oscillating wall is used for skin-friction drag reduction. For this low-Reynolds-number flow, using 90% of the available power for the pumping system and the remaining 10% for the control system is found to be the optimum share that yields the largest increase of the flow rate above the reference case where 100% of the power goes to the pump

The Horizontal Branch of NGC 1851: Constraints from its RR Lyrae Variables

We use the pulsational properties of the RR Lyrae variables in the globular cluster NGC 1851 to obtain detailed constraints of the various sub-stellar populations present along its horizontal branch. On the basis of detailed synthetic horizontal branch modeling, we find that minor helium variations (Y~0.248-0.280) are able to reproduce the observed periods and amplitudes of the RR Lyrae variables, as well as the frequency of fundamental and first-overtone RR Lyrae stars. Comparison of number ratios amongst the blue and red horizontal branch components and the two observed subgiant branches also suggest that the RR Lyrae variables originated from the progeny of the bright subgiant branch. The RR Lyrae variables with a slightly enhanced helium (Y~0.270-0.280) have longer periods at a given amplitude, as is seen with Oosterhoff II (OoII) RR Lyrae variables, whereas the RR Lyrae variables with Y~0.248-0.270 have shorter periods, exhibiting properties of Oosterhoff I (OoI) variables. This correlation does suggest that the pulsational properties of RR Lyrae stars can be very useful for tracing the various sub-populations and can provide suitable constraints on the multiple population phenomenon. It appears of great interest to explore whether this conclusion can be generalized to other globular clusters hosting multiple populations.Comment: accepted to A

A large stellar evolution database for population synthesis studies. II. Stellar models and isochrones for an alpha-enhanced metal distribution

[Abridged] We present a large, new set of stellar evolution models and isochrones for an alpha-enhanced metal distribution typical of Galactic halo and bulge stars; it represents a homogeneous extension of our stellar model library for a distribution already presented in Pietrinferni et al.(2004). The effect of the alpha-element enhancement has been properly taken into account in the nuclear network, opacity, equation of state and, for the first time, the bolometric corrections, and color transformations. This allows us to avoid the inconsistent use - common to all alpha-enhanced model libraries currently available - of scaled-solar bolometric corrections and color transformations for alpha-enhanced models and isochrones. We show how bolometric corrections to magnitudes obtained for the U,B portion of stellar spectra for T_{eff}<=6500K, are significantly affected by the metal mixture, especially at the higher metallicities. We also provide complete sets of evolutionary models for low-mass, He-burning stellar structures covering the whole metallicity range, to enable synthetic horizontal branch simulations. We compare our database with several widely used stellar model libraries from different authors, as well as with various observed color magnitude and color-color diagrams (Johnson-Cousins BVI and near infrared magnitudes, Stromgren colors) of Galactic field stars and globular clusters. We also test our isochrones comparing integrated optical colors and Surface Brightness Fluctuation magnitudes with selected globular cluster data. We find a general satisfactory agreement with the empirical constraints.Comment: 46 pages, 20 figures, ApJ in press, the whole database presented in this paper can be foud at http://www.te.astro.it/BASTI/index.ph

Towards trajectory anonymization: A generalization-based approach

Trajectory datasets are becoming,popular,due,to the massive,usage,of GPS and,location- based services. In this paper, we address privacy issues regarding the identification of individuals in static trajectory datasets. We first adopt the notion of k-anonymity,to trajectories and propose,a novel generalization-based approach,for anonymization,of trajectories. We further show,that releasing anonymized,trajectories may,still have,some,privacy,leaks. Therefore we propose,a randomization based,reconstruction,algorithm,for releasing anonymized,trajectory data and,also present how,the underlying,techniques,can be adapted,to other anonymity,standards. The experimental,results on real and,synthetic trajectory datasets show,the effectiveness of the proposed,techniques