Accounting for baseline differences and measurement error in the analysis of change over time

If change over time is compared in several groups, it is important to take into account baseline values so that the comparison is carried out under the same preconditions. As the observed baseline measurements are distorted by measurement error, it may not be sufficient to include them as covariate. By fitting a longitudinal mixed-effects model to all data including the baseline observations and subsequently calculating the expected change conditional on the underlying baseline value, a solution to this problem has been provided recently so that groups with the same baseline characteristics can be compared. In this article, we present an extended approach where a broader set of models can be used. Specifically, it is possible to include any desired set of interactions between the time variable and the other covariates, and also, time-dependent covariates can be included. Additionally, we extend the method to adjust for baseline measurement error of other time-varying covariates. We apply the methodology to data from the Swiss HIV Cohort Study to address the question if a joint infection with HIV-1 and hepatitis C virus leads to a slower increase of CD4 lymphocyte counts over time after the start of antiretroviral therapy.

AMR-Me inhibits PI3K/Akt signaling in hormone-dependent MCF-7 breast cancer cells and inactivates NF-κB in hormone-independent MDA-MB-231 cells

AMR-Me, a C-28 methylester derivative of triterpenoid compound Amooranin isolated from Amoora rohituka stem bark and the plant has been reported to possess multitude of medicinal properties. Our previous studies have shown that AMR-Me can induce apoptosis through mitochondrial apoptotic and MAPK signaling pathways by regulating the expression of apoptosis related genes in human breast cancer MCF-7 cells. However, the molecular mechanism of AMR-Me induced apoptotic cell death remains unclear. Our results showed that AMR-Me dose-dependently inhibited the proliferation of MCF-7 and MDA-MB-231 cells under serum-free conditions supplemented with 1 nM estrogen (E2) with an IC50 value of 0.15 µM, 0.45 µM, respectively. AMR-Me had minimal effects on human normal breast epithelial MCF-10A + ras and MCF-10A cells with IC50 value of 6 and 6.5 µM, respectively. AMR-Me downregulated PI3K p85, Akt1, and p-Akt in an ERα-independent manner in MCF-7 cells and no change in expression levels of PI3K p85 and Akt were observed in MDA-MB-231 cells treated under similar conditions. The PI3K inhibitor LY294002 suppressed Akt activation similar to AMR-Me and potentiated AMR-Me induced apoptosis in MCF-7 cells. EMSA revealed that AMR-Me inhibited nuclear factor-kappaB (NF-κB) DNA binding activity in MDA-MB-231 cells in a time-dependent manner and abrogated EGF induced NF-κB activation. From these studies we conclude that AMR-Me decreased ERα expression and effectively inhibited Akt phosphorylation in MCF-7 cells and inactivate constitutive nuclear NF-κB and its regulated proteins in MDA-MB-231 cells. Due to this multifactorial effect in hormone-dependent and independent breast cancer cells AMR-Me deserves attention for use in breast cancer prevention and therapy

Time to renal disease and end-stage renal disease in PROFILE: a multiethnic lupus cohort.

BACKGROUND: Renal involvement is a serious manifestation of systemic lupus erythematosus (SLE); it may portend a poor prognosis as it may lead to end-stage renal disease (ESRD). The purpose of this study was to determine the factors predicting the development of renal involvement and its progression to ESRD in a multi-ethnic SLE cohort (PROFILE). METHODS AND FINDINGS: PROFILE includes SLE patients from five different United States institutions. We examined at baseline the socioeconomic-demographic, clinical, and genetic variables associated with the development of renal involvement and its progression to ESRD by univariable and multivariable Cox proportional hazards regression analyses. Analyses of onset of renal involvement included only patients with renal involvement after SLE diagnosis (n = 229). Analyses of ESRD included all patients, regardless of whether renal involvement occurred before, at, or after SLE diagnosis (34 of 438 patients). In addition, we performed a multivariable logistic regression analysis of the variables associated with the development of renal involvement at any time during the course of SLE.In the time-dependent multivariable analysis, patients developing renal involvement were more likely to have more American College of Rheumatology criteria for SLE, and to be younger, hypertensive, and of African-American or Hispanic (from Texas) ethnicity. Alternative regression models were consistent with these results. In addition to greater accrued disease damage (renal damage excluded), younger age, and Hispanic ethnicity (from Texas), homozygosity for the valine allele of FcgammaRIIIa (FCGR3A*GG) was a significant predictor of ESRD. Results from the multivariable logistic regression model that included all cases of renal involvement were consistent with those from the Cox model. CONCLUSIONS: Fcgamma receptor genotype is a risk factor for progression of renal disease to ESRD. Since the frequency distribution of FCGR3A alleles does not vary significantly among the ethnic groups studied, the additional factors underlying the ethnic disparities in renal disease progression remain to be elucidated.

Sedimentary Metal Bioavailability Determined By the Digestive Constraints of Marine Deposit Feeders: Gut Retention Time and Dissolved Amino Acids

Contaminant metals bound to sediments are subject to considerable solubilization during passage of the sediments through the digestive systems of deposit feeders. We examined the kinetics of this process, using digestive fluids extracted from deposit feeders Arenicola marina and Parastichopus californicus and then incubated with contaminated sediments. Kinetics are complex, with solubilization followed occasionally by readsorption onto the sediment. In general, solubilization kinetics are biphasic, with an initial rapid step followed by a slower reaction. For many sediment-organism combinations, the reaction will not reach a steady state or equilibrium within the gut retention time (GRT) of the organisms, suggesting that metal bioavailability in sediments is a time-dependent parameter. Experiments with commercial protein solutions mimic the kinetic patterns observed with digestive fluids, which corroborates our previous study that complexation by dissolved amino acids (AA) in digestive fluids leads to metal solubilization (Chen & Mayer 1998b; Environ Sci Technol 32:770-778). The relative importance of the fast and slow reactions appears to depend on the ratio of ligands in gut fluids to the amount of bound metal in sediments. High ligand to solid metal ratios result in more metals released in fast reactions and thus higher lability of sedimentary metals. Multiple extractions of a sediment with digestive fluid of A. marina confirm the potential importance of incomplete reactions within a single deposit-feeding event, and make clear that bioavailability to a single animal is Likely different from that to a community of organisms. The complex kinetic patterns lead to the counterintuitive prediction that toxification of digestive enzymes by solubilized metals will occur more readily in species that dissolve less metals.

Analysis of caesarean section rates over time in a single Swiss centre using a ten-group classification system.

OBJECTIVE Caesarean section (CS) rates have risen over the past two decades. The aim of this observational study was to identify time-dependent variations in CS and vaginal delivery rates over a period of 11 years. METHOD All deliveries (13,701 deliveries during the period 1999-2009) at the University Women's Hospital Bern were analysed using an internationally standardised and approved ten-group classification system. Caesarean sections on maternal request (CSMR) were evaluated separately. RESULTS We detected an overall CS rate of 36.63% and an increase in the CS rate over time (p <0.001). Low-risk profile groups were the two largest populations and displayed low CS rates, with significantly decreasing relative size over time. The relative size of groups with induced labour increased significantly, but this did not have an impact on the overall CS rate. Pregnancies complicated by breech position, multiple pregnancies and abnormal lies did not have an impact on overall CS rate. The biggest contributor to a high CS rate was preterm delivery and the existence of a uterine scar from a previous CS. CSMR was 1.45% and did not have an impact on the overall CS rate. CONCLUSION The observational study identified wide variations in caesarean section and vaginal delivery rates across the groups over time, and a shift towards high-risk populations was noted. The biggest contributors to high CS rates were identified; namely, previous uterine scar and preterm delivery. Interventions aiming to reduce CS rates are planned.

Resolving diffusion in clay minerals at different time scales: Combination of experimental and modeling approaches

Since no single experimental or modeling technique provides data that allow a description of transport processes in clays and clay minerals at all relevant scales, several complementary approaches have to be combined to understand and explain the interplay between transport relevant phenomena. In this paper molecular dynamics simulations (MD) were used to investigate the mobility of water in the interlayer of montmorillonite (Mt), and to estimate the influence of mineral surfaces and interlayer ions on the water diffusion. Random Walk (RW) simulations based on a simplified representation of pore space in Mt were used to estimate and understand the effect of the arrangement of Mt particles on the meso- to macroscopic diffusivity of water. These theoretical calculations were complemented with quasielastic neutron scattering (QENS) measurements of aqueous diffusion in Mt with two pseudo-layers of water performed at four significantly different energy resolutions (i.e. observation times). The size of the interlayer and the size of Mt particles are two characteristic dimensions which determine the time dependent behavior of water diffusion in Mt. MD simulations show that at very short time scales water dynamics has the characteristic features of an oscillatory motion in the cage formed by neighbors in the first coordination shell. At longer time scales, the interaction of water with the surface determines the water dynamics, and the effect of confinement on the overall water mobility within the interlayer becomes evident. At time scales corresponding to an average water displacement equivalent to the average size of Mt particles, the effects of tortuosity are observed in the meso- to macroscopic pore scale simulations. Consistent with the picture obtained in the simulations, the QENS data can be described using a (local) 3D diffusion at short observation times, whereas at sufficiently long observation times a 2D diffusive motion is clearly observed. The effects of tortuosity measured in macroscopic tracer diffusion experiments are in qualitative agreement with RW simulations. By using experimental data to calibrate molecular and mesoscopic theoretical models, a consistent description of water mobility in clay minerals from the molecular to the macroscopic scale can be achieved. In turn, simulations help in choosing optimal conditions for the experimental measurements and the data interpretation. (C) 2014 Elsevier B.V. All rights reserved.

Effect of patient accrual patterns on power and size of log-rank test for time-to-event outcome in clinical trials

The determination of size as well as power of a test is a vital part of a Clinical Trial Design. This research focuses on the simulation of clinical trial data with time-to-event as the primary outcome. It investigates the impact of different recruitment patterns, and time dependent hazard structures on size and power of the log-rank test. A non-homogeneous Poisson process is used to simulate entry times according to the different accrual patterns. A Weibull distribution is employed to simulate survival times according to the different hazard structures. The current study utilizes simulation methods to evaluate the effect of different recruitment patterns on size and power estimates of the log-rank test. The size of the log-rank test is estimated by simulating survival times with identical hazard rates between the treatment and the control arm of the study resulting in a hazard ratio of one. Powers of the log-rank test at specific values of hazard ratio (≠1) are estimated by simulating survival times with different, but proportional hazard rates for the two arms of the study. Different shapes (constant, decreasing, or increasing) of the hazard function of the Weibull distribution are also considered to assess the effect of hazard structure on the size and power of the log-rank test. ^

TRIM24-REGULATED ESTROGEN RESPONSE IS DEPENDENT ON SPECIFIC HISTONE MODIFICATIONS IN BREAST CANCER CELLS

In this dissertation, I discovered that function of TRIM24 as a co-activator of ERα-mediated transcriptional activation is dependent on specific histone modifications in tumorigenic human breast cancer-derived MCF7 cells. In the first part, I proved that TRIM24-PHD finger domain, which recognizes unmethylated histone H3 lysine K4 (H3K4me0), is critical for ERα-regulated transcription. Therefore, when LSD1-mediated demethylation of H3K4 is inhibited, activation of TRIM24-regulated ERα target genes is greatly impaired. Importantly, I demonstrated that TRIM24 and LSD1 are cyclically recruited to estrogen responsive elements (EREs) in a time-dependent manner upon estrogen induction, and depletion of their expression exert corresponding time-dependent effect on target gene activation. I also identified that phosphorylation of histone H3 threonine T6 disrupts TRIM24 from binding to the chromatin and from activating ERα-regulated targets. In the second part, I revealed that TRIM24 depletion has additive effect to LSD1 inhibitor- and Tamoxifen-mediated reduction in survival and proliferation in breast cancer cells.

Reference list of 120 datasets from time series station Payerne used for exploratory search

The analysis of time-dependent data is an important problem in many application domains, and interactive visualization of time-series data can help in understanding patterns in large time series data. Many effective approaches already exist for visual analysis of univariate time series supporting tasks such as assessment of data quality, detection of outliers, or identification of periodically or frequently occurring patterns. However, much fewer approaches exist which support multivariate time series. The existence of multiple values per time stamp makes the analysis task per se harder, and existing visualization techniques often do not scale well. We introduce an approach for visual analysis of large multivariate time-dependent data, based on the idea of projecting multivariate measurements to a 2D display, visualizing the time dimension by trajectories. We use visual data aggregation metaphors based on grouping of similar data elements to scale with multivariate time series. Aggregation procedures can either be based on statistical properties of the data or on data clustering routines. Appropriately defined user controls allow to navigate and explore the data and interactively steer the parameters of the data aggregation to enhance data analysis. We present an implementation of our approach and apply it on a comprehensive data set from the field of earth bservation, demonstrating the applicability and usefulness of our approach.

Mixing Snapshots and Fast Time Integration of PDEs

A local proper orthogonal decomposition (POD) plus Galerkin projection method was recently developed to accelerate time dependent numerical solvers of PDEs. This method is based on the combined use of a numerical code (NC) and a Galerkin sys- tem (GS) in a sequence of interspersed time intervals, INC and IGS, respectively. POD is performed on some sets of snapshots calculated by the numerical solver in the INC inter- vals. The governing equations are Galerkin projected onto the most energetic POD modes and the resulting GS is time integrated in the next IGS interval. The major computa- tional e®ort is associated with the snapshots calculation in the ¯rst INC interval, where the POD manifold needs to be completely constructed (it is only updated in subsequent INC intervals, which can thus be quite small). As the POD manifold depends only weakly on the particular values of the parameters of the problem, a suitable library can be con- structed adapting the snapshots calculated in other runs to drastically reduce the size of the ¯rst INC interval and thus the involved computational cost. The strategy is success- fully tested in (i) the one-dimensional complex Ginzburg-Landau equation, including the case in which it exhibits transient chaos, and (ii) the two-dimensional unsteady lid-driven cavity problem

A second order in time modified Lagrange-Galerkin finite element method for the incompressible Navier-Stokes equations

We introduce a second order in time modified Lagrange--Galerkin (MLG) method for the time dependent incompressible Navier--Stokes equations. The main ingredient of the new method is the scheme proposed to calculate in a more efficient manner the Galerkin projection of the functions transported along the characteristic curves of the transport operator. We present error estimates for velocity and pressure in the framework of mixed finite elements when either the mini-element or the $P2/P1$ Taylor--Hood element are used.

Modeling the evolution of item rating networks using time-domain preferential attachment

The understanding of the structure and dynamics of the intricate network of connections among people that consumes products through Internet appears as an extremely useful asset in order to study emergent properties related to social behavior. This knowledge could be useful, for example, to improve the performance of personal recommendation algorithms. In this contribution, we analyzed five-year records of movie-rating transactions provided by Netflix, a movie rental platform where users rate movies from an online catalog. This dataset can be studied as a bipartite user-item network whose structure evolves in time. Even though several topological properties from subsets of this bipartite network have been reported with a model that combines random and preferential attachment mechanisms [Beguerisse Díaz et al., 2010], there are still many aspects worth to be explored, as they are connected to relevant phenomena underlying the evolution of the network. In this work, we test the hypothesis that bursty human behavior is essential in order to describe how a bipartite user-item network evolves in time. To that end, we propose a novel model that combines, for user nodes, a network growth prescription based on a preferential attachment mechanism acting not only in the topological domain (i.e. based on node degrees) but also in time domain. In the case of items, the model mixes degree preferential attachment and random selection. With these ingredients, the model is not only able to reproduce the asymptotic degree distribution, but also shows an excellent agreement with the Netflix data in several time-dependent topological properties.

Electrical Power Fluctuations in a Network of DC/AC inverters in a Large PV Plant: relationship between correlation, distance and time scale

This paper analyzes the correlation between the fluctuations of the electrical power generated by the ensemble of 70 DC/AC inverters from a 45.6 MW PV plant. The use of real electrical power time series from a large collection of photovoltaic inverters of a same plant is an impor- tant contribution in the context of models built upon simplified assumptions to overcome the absence of such data. This data set is divided into three different fluctuation categories with a clustering proce- dure which performs correctly with the clearness index and the wavelet variances. Afterwards, the time dependent correlation between the electrical power time series of the inverters is esti- mated with the wavelet transform. The wavelet correlation depends on the distance between the inverters, the wavelet time scales and the daily fluctuation level. Correlation values for time scales below one minute are low without dependence on the daily fluctuation level. For time scales above 20 minutes, positive high correlation values are obtained, and the decay rate with the distance depends on the daily fluctuation level. At intermediate time scales the correlation depends strongly on the daily fluctuation level. The proposed methods have been implemented using free software. Source code is available as supplementary material.

Fast magnetosonic wave excitation by an array of wires with time-modulated currents

The excitation of Fast Magnetosonic (FMS)waves by a cylindrical array of parallel tethers carrying timemodulated current is discussed. The tethers would fly vertical in the equatorial plane, which is perpendicular to the geomagnetic field when its tilt is ignored, and would be stabilized by the gravity gradient. The tether array would radiate a single FMS wave. In the time-dependent background made of geomagnetic field plus radiated wave, plasma FMS perturbations are excited in the array vicinity through a parametric instability. The growth rate is estimated by truncating the evolution equation for FMS perturbations to the two azimuthal modes of lowest order. Design parameters such as tether length and number, required power and mass are discussed for Low Earth Orbit conditions. The array-attached wave structure would have the radiated wave controlled by the intensity and modulation frequency of the currents, making an active experiment on non-linear low frequency waves possible in real space plasma conditions.

Detection of Ca2+-Dependent Transglutaminase Activity in Root and Leaf Tissue of Monocotyledonous and Dicotyledonous Plants

Protein extracted from root and leaf tissue of the dicotyledonous plants pea (Pisum sativum) and broad bean (Vicia faba) and the monocotyledonous plants wheat (Triticum aestivum) and barley (Hordeum vulgare) were shown to catalyze the incorporation of biotin-labeled cadaverine into microtiter-plate-bound N′,N′-dimethylcasein and the cross-linking of biotin-labeled casein to microtiter-plate-bound casein in a Ca2+-dependent manner. The cross-linking of biotinylated casein and the incorporation of biotin-labeled cadaverine into N′,N′-dimethylcasein were time-dependent reactions with a pH optimum of 7.9. Transglutaminase activity was shown to increase over a 2-week growth period in both the roots and leaves of pea. The product of transglutaminase's protein-cross-linking activity, ε-(γ-glutamyl)-lysine isodipeptide, was detected in root and shoot protein from pea, broad bean, wheat, and barley by cation-exchange chromatography. The presence of the isodipeptide was confirmed by reversed-phase chromatography. Hydrolysis of the isodipeptide after cation-exchange chromatography confirmed the presence of glutamate and lysine.