31 resultados para dependent data


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Glomerulosclerosis of any cause is characterized by loss of functional glomerular cells and deposition of excessive amounts of interstitial collagens including collagen I. We have previously reported that mesangial cell attachment to collagen I leads to upregulation of Hic-5 in vitro, which mediates mesangial cell apoptosis. Furthermore, glomerular Hic-5 expression was increased during the progression of experimental glomerulosclerosis. We hypothesized that reducing collagen I accumulation in glomerulosclerosis would in turn lower Hic-5 expression, reducing mesangial cell apoptosis, and thus maintaining glomerular integrity. We examined archive renal tissue from rats undergoing experimental diabetic glomerulosclerosis, treated with the transglutaminase-2 inhibitor NTU281. Untreated animals exhibited increased glomerular collagen I accumulation, associated with increased glomerular Hic-5 expression, apoptosis, and mesangial myofibroblast transdifferentiation characterized by a-smooth muscle actin (a-SMA) expression. NTU281 treatment reduced glomerular collagen I accumulation, Hic-5 and a-SMA expression, and apoptosis. Proteinurea and serum creatinine levels were significantly reduced in animals with reduced Hic-5 expression. In vitro studies of Hic-5 knockdown or overexpression show that mesangial cell apoptosis and expression of both a-SMA and collagen I are Hic-5 dependent. Together, these data suggest that there exists, in vitro and in vivo, a positive feedback loop whereby increased levels of collagen I lead to increased mesangial Hic-5 expression favoring not only increased apoptosis, but also mesangial myofibroblast transdifferentiation and increased collagen I expression. Prevention of collagen I accumulation interrupts this Hic-5-dependent positive feedback loop, preserving glomerular architecture, cellular phenotype, and function. © 2013 USCAP, Inc All rights reserved.

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The transactive response (TAR) DNA-binding protein of 43kDa (TDP-43) is an RNA binding protein encoded by the TARDPB gene. Abnormal aggregations of TDP-43 in neurons in the form of neuronal cytoplasmic inclusions (NCI) are the pathological hallmark of frontotemporal lobar degeneration with TDP-43 proteinopathy (FTLD-TDP). To investigate the role of TDP-43 in FTLD-TDP, the spatial patterns of the NCI were studied in frontal and temporal cortex of FTLD-TDP cases using a phosphorylation dependent anti-TDP-43 antibody (pTDP-43). In many regions, the NCI formed clusters and the clusters were distributed regularly parallel to the tissue boundary. In about 35% of cortical regions, cluster size of the NCI was within the size range of the modular columns of the cortex. The spatial patterns of the pTDP-immunoreactive inclusions were similar to those revealed by a phosphorylation-independent anti-TDP-43 antibody and also similar to inclusions characterized by other molecular pathologies such as tau, ?-synuclein and ‘fused in sarcoma’ (FUS). In conclusion, the data suggest degeneration of cortical and hippocampal anatomical pathways associated with accumulation of cellular pTDP-43 is characteristic of FTLD-TDP. In addition, the data are consistent with the hypothesis of cell to cell transfer of pTDP-43 within the brain.

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Distributed Brillouin sensing of strain and temperature works by making spatially resolved measurements of the position of the measurand-dependent extremum of the resonance curve associated with the scattering process in the weakly nonlinear regime. Typically, measurements of backscattered Stokes intensity (the dependent variable) are made at a number of predetermined fixed frequencies covering the design measurand range of the apparatus and combined to yield an estimate of the position of the extremum. The measurand can then be found because its relationship to the position of the extremum is assumed known. We present analytical expressions relating the relative error in the extremum position to experimental errors in the dependent variable. This is done for two cases: (i) a simple non-parametric estimate of the mean based on moments and (ii) the case in which a least squares technique is used to fit a Lorentzian to the data. The question of statistical bias in the estimates is discussed and in the second case we go further and present for the first time a general method by which the probability density function (PDF) of errors in the fitted parameters can be obtained in closed form in terms of the PDFs of the errors in the noisy data.

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The inverse problem of determining a spacewise-dependent heat source for the parabolic heat equation using the usual conditions of the direct problem and information from one supplementary temperature measurement at a given instant of time is studied. This spacewise-dependent temperature measurement ensures that this inverse problem has a unique solution, but the solution is unstable and hence the problem is ill-posed. We propose a variational conjugate gradient-type iterative algorithm for the stable reconstruction of the heat source based on a sequence of well-posed direct problems for the parabolic heat equation which are solved at each iteration step using the boundary element method. The instability is overcome by stopping the iterative procedure at the first iteration for which the discrepancy principle is satisfied. Numerical results are presented which have the input measured data perturbed by increasing amounts of random noise. The numerical results show that the proposed procedure yields stable and accurate numerical approximations after only a few iterations.

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This paper investigates the inverse problem of determining a spacewise dependent heat source in the parabolic heat equation using the usual conditions of the direct problem and information from a supplementary temperature measurement at a given single instant of time. The spacewise dependent temperature measurement ensures that the inverse problem has a unique solution, but this solution is unstable, hence the problem is ill-posed. For this inverse problem, we propose an iterative algorithm based on a sequence of well-posed direct problems which are solved at each iteration step using the boundary element method (BEM). The instability is overcome by stopping the iterations at the first iteration for which the discrepancy principle is satisfied. Numerical results are presented for various typical benchmark test examples which have the input measured data perturbed by increasing amounts of random noise.

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We present information-theory analysis of the tradeoff between bit-error rate improvement and the data-rate loss using skewed channel coding to suppress pattern-dependent errors in digital communications. Without loss of generality, we apply developed general theory to the particular example of a high-speed fiber communication system with a strong patterning effect. © 2007 IEEE.

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Optimal design for parameter estimation in Gaussian process regression models with input-dependent noise is examined. The motivation stems from the area of computer experiments, where computationally demanding simulators are approximated using Gaussian process emulators to act as statistical surrogates. In the case of stochastic simulators, which produce a random output for a given set of model inputs, repeated evaluations are useful, supporting the use of replicate observations in the experimental design. The findings are also applicable to the wider context of experimental design for Gaussian process regression and kriging. Designs are proposed with the aim of minimising the variance of the Gaussian process parameter estimates. A heteroscedastic Gaussian process model is presented which allows for an experimental design technique based on an extension of Fisher information to heteroscedastic models. It is empirically shown that the error of the approximation of the parameter variance by the inverse of the Fisher information is reduced as the number of replicated points is increased. Through a series of simulation experiments on both synthetic data and a systems biology stochastic simulator, optimal designs with replicate observations are shown to outperform space-filling designs both with and without replicate observations. Guidance is provided on best practice for optimal experimental design for stochastic response models. © 2013 Elsevier Inc. All rights reserved.

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One of the main challenges of classifying clinical data is determining how to handle missing features. Most research favours imputing of missing values or neglecting records that include missing data, both of which can degrade accuracy when missing values exceed a certain level. In this research we propose a methodology to handle data sets with a large percentage of missing values and with high variability in which particular data are missing. Feature selection is effected by picking variables sequentially in order of maximum correlation with the dependent variable and minimum correlation with variables already selected. Classification models are generated individually for each test case based on its particular feature set and the matching data values available in the training population. The method was applied to real patients' anonymous mental-health data where the task was to predict the suicide risk judgement clinicians would give for each patient's data, with eleven possible outcome classes: zero to ten, representing no risk to maximum risk. The results compare favourably with alternative methods and have the advantage of ensuring explanations of risk are based only on the data given, not imputed data. This is important for clinical decision support systems using human expertise for modelling and explaining predictions.

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Robust controllers for nonlinear stochastic systems with functional uncertainties can be consistently designed using probabilistic control methods. In this paper a generalised probabilistic controller design for the minimisation of the Kullback-Leibler divergence between the actual joint probability density function (pdf) of the closed loop control system, and an ideal joint pdf is presented emphasising how the uncertainty can be systematically incorporated in the absence of reliable systems models. To achieve this objective all probabilistic models of the system are estimated from process data using mixture density networks (MDNs) where all the parameters of the estimated pdfs are taken to be state and control input dependent. Based on this dependency of the density parameters on the input values, explicit formulations to the construction of optimal generalised probabilistic controllers are obtained through the techniques of dynamic programming and adaptive critic methods. Using the proposed generalised probabilistic controller, the conditional joint pdfs can be made to follow the ideal ones. A simulation example is used to demonstrate the implementation of the algorithm and encouraging results are obtained.

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Glucose-dependent insulinotropic polypeptide (GIP) is a physiological insulin releasing peptide. We have developed two novel fatty acid derivatized GIP analogues, which bind to serum albumin and demonstrate enhanced duration of action in vivo. GIP(Lys16PAL) and GIP(Lys37PAL) were resistant to dipeptidyl peptidase IV (DPP IV) degradation. In vitro studies demonstrated that GIP analogues retained their ability to activate the GIP receptor through production of cAMP and to stimulate insulin secretion. Intraperitoneal administration of GIP analogues to obese diabetic (ob/ob) mice significantly decreased the glycemic excursion and elicited increased and prolonged insulin responses compared to native GIP. A protracted glucose-lowering effect was observed 24 h following GIP(Lys37PAL) administration. Once a day injection for 14 days decreased nonfasting glucose, improved glucose tolerance, and enhanced the insulin response to glucose. These data demonstrate that fatty acid derivatized GIP peptides represent a novel class of long-acting stable GIP analogues for therapy of type 2 diabetes. © 2006 American Chemical Society.

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Cyclooxygenase 2 (COX2), a key regulatory enzyme of the prostaglandin/eicosanoid pathway, is an important target for anti-inflammatory therapy. It is highly induced by pro-inflammatory cytokines in a Nuclear factor kappa B (NFκB)-dependent manner. However, the mechanisms determining the amplitude and dynamics of this important pro-inflammatory event are poorly understood. Furthermore, there is significant difference between human and mouse COX2 expression in response to the inflammatory stimulus tumor necrosis factor alpha (TNFα). Here, we report the presence of a molecular logic AND gate composed of two NFκB response elements (NREs) which controls the expression of human COX2 in a switch-like manner. Combining quantitative kinetic modeling and thermostatistical analysis followed by experimental validation in iterative cycles, we show that the human COX2 expression machinery regulated by NFκB displays features of a logic AND gate. We propose that this provides a digital, noise-filtering mechanism for a tighter control of expression in response to TNFα, such that a threshold level of NFκB activation is required before the promoter becomes active and initiates transcription. This NFκB-regulated AND gate is absent in the mouse COX2 promoter, most likely contributing to its differential graded response in promoter activity and protein expression to TNFα. Our data suggest that the NFκB-regulated AND gate acts as a novel mechanism for controlling the expression of human COX2 to TNFα, and its absence in the mouse COX2 provides the foundation for further studies on understanding species-specific differential gene regulation.

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Association of receptor activity-modifying proteins (RAMP1-3) with the G protein-coupled receptor (GPCR) calcitonin receptor-like receptor (CLR) enables selective recognition of the peptides calcitonin gene-related peptide (CGRP) and adrenomedullin (AM) that have diverse functions in the cardiovascular and lymphatic systems. How peptides selectively bind GPCR:RAMP complexes is unknown. We report crystal structures of CGRP analog-bound CLR:RAMP1 and AM-bound CLR:RAMP2 extracellular domain heterodimers at 2.5 and 1.8 Å resolutions, respectively. The peptides similarly occupy a shared binding site on CLR with conformations characterized by a β-turn structure near their C termini rather than the α-helical structure common to peptides that bind related GPCRs. The RAMPs augment the binding site with distinct contacts to the variable C-terminal peptide residues and elicit subtly different CLR conformations. The structures and accompanying pharmacology data reveal how a class of accessory membrane proteins modulate ligand binding of a GPCR and may inform drug development targeting CLR:RAMP complexes.

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Internal quantum efficiency (IQE) of a blue high-brightness InGaN/GaN light-emitting diode (LED) was evaluated from the external quantum efficiency measured as a function of current at various temperatures ranged between 13 and 440 K. Processing the data with a novel evaluation procedure based on the ABC-model, we have determined the temperature-dependent IQE of the LED structure and light extraction efficiency of the LED chip. Separate evaluation of these parameters is helpful for further optimization of the heterostructure and chip designs. The data obtained enable making a guess on the temperature dependence of the radiative and Auger recombination coefficients, which may be important for identification of dominant mechanisms responsible for the efficiency droop in III-nitride LEDs. Thermal degradation of the LED performance in terms of the emission efficiency is also considered.

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We present experimental results for wavelength-division multiplexed (WDM) transmission performance using unbalanced proportions of 1s and 0s in pseudo-random bit sequence (PRBS) data. This investigation simulates the effect of local, in time, data unbalancing which occurs in some coding systems such as forward error correction when extra bits are added to the WDM data stream. We show that such local unbalancing, which would practically give a time-dependent error-rate, can be employed to improve the legacy long-haul WDM system performance if the system is allowed to operate in the nonlinear power region. We use a recirculating loop to simulate a long-haul fibre system.

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The determination of the displacement and the space-dependent force acting on a vibrating structure from measured final or time-average displacement observation is thoroughly investigated. Several aspects related to the existence and uniqueness of a solution of the linear but ill-posed inverse force problems are highlighted. After that, in order to capture the solution a variational formulation is proposed and the gradient of the least-squares functional that is minimized is rigorously and explicitly derived. Numerical results obtained using the Landweber method and the conjugate gradient method are presented and discussed illustrating the convergence of the iterative procedures for exact input data. Furthermore, for noisy data the semi-convergence phenomenon appears, as expected, and stability is restored by stopping the iterations according to the discrepancy principle criterion once the residual becomes close to the amount of noise. The present investigation will be significant to researchers concerned with wave propagation and control of vibrating structures.