Parameterized Link Functions in Generalized Linear Random Effect Models: a Case Study on Breast Cancer Treatment

In non-linear random effects some attention has been very recently devoted to the analysis ofsuitable transformation of the response variables separately (Taylor 1996) or not (Oberg and Davidian 2000) from the transformations of the covariates and, as far as we know, no investigation has been carried out on the choice of link function in such models. In our study we consider the use of a random effect model when a parameterized family of links (Aranda-Ordaz 1981, Prentice 1996, Pregibon 1980, Stukel 1988 and Czado 1997) is introduced. We point out the advantages and the drawbacks associated with the choice of this data-driven kind of modeling. Difficulties in the interpretation of regression parameters, and therefore in understanding the influence of covariates, as well as problems related to loss of efficiency of estimates and overfitting, are discussed. A case study on radiotherapy usage in breast cancer treatment is discussed.

Data collapse, scaling functions, and analytical solutions of generalized growth models

We consider a nontrivial one-species population dynamics model with finite and infinite carrying capacities. Time-dependent intrinsic and extrinsic growth rates are considered in these models. Through the model per capita growth rate we obtain a heuristic general procedure to generate scaling functions to collapse data into a simple linear behavior even if an extrinsic growth rate is included. With this data collapse, all the models studied become independent from the parameters and initial condition. Analytical solutions are found when time-dependent coefficients are considered. These solutions allow us to perceive nontrivial transitions between species extinction and survival and to calculate the transition's critical exponents. Considering an extrinsic growth rate as a cancer treatment, we show that the relevant quantity depends not only on the intensity of the treatment, but also on when the cancerous cell growth is maximum.

Effects of chlorogenic acid on neutrophil locomotion functions in response to inflammatory stimulus

Aim of the study: Species of Lychnophora are used in Brazilian folk medicine as analgesic and anti-inflammatory agents. Chlorogenic acid (CGA) and their analogues are important components of polar extracts of these species, as well in several European and Asian medicinal plants. Some of these phenolic compounds display anti-inflammatory effects. In this paper we report the isolation of CGA from Lychnophora salicifolia and its effects on functions involved in neutrophils locomotion. Materials and methods: LC-MS(n) data confirmed the presence of CGA in the plant. Actions of CGA were investigated on neutrophils obtained from peritoneal cavity of Wistar rats (4h after 1% oyster glycogen solution injection; 10 ml), and incubated with vehicle or with 50, 100 or 1000 mu M CGA in presence of lipopolysaccharide from Escherichia coil (LPS, 5 mu g/ml). Nitric oxide (NO; Griess reaction); prostaglandin E(2) (PGE(2)), interleukin-1 beta (IL-1 beta) and tumor necrosis factor-alpha [TNF-alpha; enzyme-linked immunosorbent assay (EIA)]; protein (flow cytometry) and gene (RT-PCR) expression of L-selectin, beta(2)integrin and platelet-endothelial cell adhesion molecule-1 (PECAM-1) were quantified. In vitro neutrophil adhesion to primary culture of microvascular endothelial cell (PMEC) and neutrophil migration in response to formyl-methionil-leucil-phenilalanine (fMLP, 10(-8)M, Boyden chamber) was determined. Results: CGA treatment did not modify the secretion of inflammatory mediators, but inhibited L-selectin cleavage and reduced beta(2) integrin, independently from its mRNA synthesis, and reduced membrane PECAM-1 expression: inhibited neutrophil adhesion and neutrophil migration induced by fMLP. Conclusions: Based on these findings, we highlight the direct inhibitory actions of CGA on adhesive and locomotion properties of neutrophils, which may contribute to its anti-inflammatory effects and help to explain the use of Lychnophora salicifolia as an anti-inflammatory agent. (C) 2011 Elsevier Ireland Ltd. All rights reserved.

Some results on holomorphic generalized functions

In this note, we present three independent results within generalized complex analysis (in the Colombeau sense). The first of them deals with non-removable singularities; we construct a generalized function u on an open subset Omega of C(n), which is not a holomorphic generalized function on Omega but it is a holomorphic generalized function on Omega\S, where S is a hypersurface contained in Omega. The second result shows the existence of a holomorphic generalized function with prescribed values in the zero-set of a classical holomorphic function. The last result states the existence of a compactly supported solution to the (partial derivative) over bar operator.

On derivatives and norms of generalized matrix functions and respective symmetric powers

In recent papers, the authors obtained formulas for directional derivatives of all orders, of the immanant and of the m-th xi-symmetric tensor power of an operator and a matrix, when xi is a character of the full symmetric group. The operator norm of these derivatives was also calculated. In this paper, similar results are established for generalized matrix functions and for every symmetric tensor power.

Neuroendocrine, metabolic, and immune functions during the acute phase response of inflammatory stress in monosodium L-glutamate-damaged, hyperadipose male rat.

In rats, neonatal treatment with monosodium L-glutamate (MSG) induces several metabolic and neuroendocrine abnormalities, which result in hyperadiposity. No data exist, however, regarding neuroendocrine, immune and metabolic responses to acute endotoxemia in the MSG-damaged rat. We studied the consequences of MSG treatment during the acute phase response of inflammatory stress. Neonatal male rats were treated with MSG or vehicle (controls, CTR) and studied at age 90 days. Pituitary, adrenal, adipo-insular axis, immune, metabolic and gonadal functions were explored before and up to 5 h after single sub-lethal i.p. injection of bacterial lipopolysaccharide (LPS; 150 microg/kg). Our results showed that, during the acute phase response of inflammatory stress in MSG rats: (1) the corticotrope-adrenal, leptin, insulin and triglyceride responses were higher than in CTR rats, (2) pro-inflammatory (TNFalpha) cytokine response was impaired and anti-inflammatory (IL-10) cytokine response was normal, and (3) changes in peripheral estradiol and testosterone levels after LPS varied as in CTR rats. These data indicate that metabolic and neroendocrine-immune functions are altered in MSG-damaged rats. Our study also suggests that the enhanced corticotrope-corticoadrenal activity in MSG animals could be responsible, at least in part, for the immune and metabolic derangements characterizing hypothalamic obesity.

Generalized multiresolution analyses with given multiplicity functions

Generalized multiresolution analyses are increasing sequences of subspaces of a Hilbert space H that fail to be multiresolution analyses in the sense of wavelet theory because the core subspace does not have an orthonormal basis generated by a fixed scaling function. Previous authors have studied a multiplicity function m which, loosely speaking, measures the failure of the GMRA to be an MRA. When the Hilbert space H is L2(Rn), the possible multiplicity functions have been characterized by Baggett and Merrill. Here we start with a function m satisfying a consistency condition which is known to be necessary, and build a GMRA in an abstract Hilbert space with multiplicity function m.

Using spatially distributed parameters and multi-response objective functions to solve parameterization of complex applications of semi-distributed hydrological models

Application of semi-distributed hydrological models to large, heterogeneous watersheds deals with several problems. On one hand, the spatial and temporal variability in catchment features should be adequately represented in the model parameterization, while maintaining the model complexity in an acceptable level to take advantage of state-of-the-art calibration techniques. On the other hand, model complexity enhances uncertainty in adjusted model parameter values, therefore increasing uncertainty in the water routing across the watershed. This is critical for water quality applications, where not only streamflow, but also a reliable estimation of the surface versus subsurface contributions to the runoff is needed. In this study, we show how a regularized inversion procedure combined with a multiobjective function calibration strategy successfully solves the parameterization of a complex application of a water quality-oriented hydrological model. The final value of several optimized parameters showed significant and consistentdifferences across geological and landscape features. Although the number of optimized parameters was significantly increased by the spatial and temporal discretization of adjustable parameters, the uncertainty in water routing results remained at reasonable values. In addition, a stepwise numerical analysis showed that the effects on calibration performance due to inclusion of different data types in the objective function could be inextricably linked. Thus caution should be taken when adding or removing data from an aggregated objective function.

Computing Distance Functions from Generalized Sources on Weighted Polyhedral Surfaces

We present algorithms for computing approximate distance functions and shortest paths from a generalized source (point, segment, polygonal chain or polygonal region) on a weighted non-convex polyhedral surface in which obstacles (represented by polygonal chains or polygons) are allowed. We also describe an algorithm for discretizing, by using graphics hardware capabilities, distance functions. Finally, we present algorithms for computing discrete k-order Voronoi diagrams

A Functional Magnetic Resonance Imaging Predictor of Treatment Response to Venlafaxine in Generalized Anxiety Disorder

Background: Functional magnetic resonance imaging (fMRI) holds promise as a noninvasive means of identifying neural responses that can be used to predict treatment response before beginning a drug trial. Imaging paradigms employing facial expressions as presented stimuli have been shown to activate the amygdala and anterior cingulate cortex (ACC). Here, we sought to determine whether pretreatment amygdala and rostral ACC (rACC) reactivity to facial expressions could predict treatment outcomes in patients with generalized anxiety disorder (GAD).Methods: Fifteen subjects (12 female subjects) with GAD participated in an open-label venlafaxine treatment trial. Functional magnetic resonance imaging responses to facial expressions of emotion collected before subjects began treatment were compared with changes in anxiety following 8 weeks of venlafaxine administration. In addition, the magnitude of fMRI responses of subjects with GAD were compared with that of 15 control subjects (12 female subjects) who did not have GAD and did not receive venlafaxine treatment.Results The magnitude of treatment response was predicted by greater pretreatment reactivity to fearful faces in rACC and lesser reactivity in the amygdala. These individual differences in pretreatment rACC and amygdala reactivity within the GAD group were observed despite the fact that 1) the overall magnitude of pretreatment rACC and amygdala reactivity did not differ between subjects with GAD and control subjects and 2) there was no main effect of treatment on rACC-amygdala reactivity in the GAD group.Conclusions: These findings show that this pattern of rACC-amygdala responsivity could prove useful as a predictor of venlafaxine treatment response in patients with GAD.

Anticipatory activation in the amygdala and anterior cingulate in generalized anxiety disorder and prediction of treatment response

OBJECTIVE: The anticipation of adverse outcomes, or worry, is a cardinal symptom of generalized anxiety disorder. Prior work with healthy subjects has shown that anticipating aversive events recruits a network of brain regions, including the amygdala and anterior cingulate cortex. This study tested whether patients with generalized anxiety disorder have alterations in anticipatory amygdala function and whether anticipatory activity in the anterior cingulate cortex predicts treatment response. METHOD: Functional magnetic resonance imaging (fMRI) was employed with 14 generalized anxiety disorder patients and 12 healthy comparison subjects matched for age, sex, and education. The event-related fMRI paradigm was composed of one warning cue that preceded aversive pictures and a second cue that preceded neutral pictures. Following the fMRI session, patients received 8 weeks of treatment with extended-release venlafaxine. RESULTS: Patients with generalized anxiety disorder showed greater anticipatory activity than healthy comparison subjects in the bilateral dorsal amygdala preceding both aversive and neutral pictures. Building on prior reports of pretreatment anterior cingulate cortex activity predicting treatment response, anticipatory activity in that area was associated with clinical outcome 8 weeks later following treatment with venlafaxine. Higher levels of pretreatment anterior cingulate cortex activity in anticipation of both aversive and neutral pictures were associated with greater reductions in anxiety and worry symptoms. CONCLUSIONS: These findings of heightened and indiscriminate amygdala responses to anticipatory signals in generalized anxiety disorder and of anterior cingulate cortex associations with treatment response provide neurobiological support for the role of anticipatory processes in the pathophysiology of generalized anxiety disorder.

Generalized neurofuzzy network modeling algorithms using Bezier-Bernstein polynomial functions and additive decomposition

This paper introduces a new neurofuzzy model construction algorithm for nonlinear dynamic systems based upon basis functions that are Bezier-Bernstein polynomial functions. This paper is generalized in that it copes with n-dimensional inputs by utilising an additive decomposition construction to overcome the curse of dimensionality associated with high n. This new construction algorithm also introduces univariate Bezier-Bernstein polynomial functions for the completeness of the generalized procedure. Like the B-spline expansion based neurofuzzy systems, Bezier-Bernstein polynomial function based neurofuzzy networks hold desirable properties such as nonnegativity of the basis functions, unity of support, and interpretability of basis function as fuzzy membership functions, moreover with the additional advantages of structural parsimony and Delaunay input space partition, essentially overcoming the curse of dimensionality associated with conventional fuzzy and RBF networks. This new modeling network is based on additive decomposition approach together with two separate basis function formation approaches for both univariate and bivariate Bezier-Bernstein polynomial functions used in model construction. The overall network weights are then learnt using conventional least squares methods. Numerical examples are included to demonstrate the effectiveness of this new data based modeling approach.

The full infinite dimensional moment problem on semi-algebraic sets of generalized functions

We consider a generic basic semi-algebraic subset S of the space of generalized functions, that is a set given by (not necessarily countably many) polynomial constraints. We derive necessary and sufficient conditions for an infinite sequence of generalized functions to be realizable on S, namely to be the moment sequence of a finite measure concentrated on S. Our approach combines the classical results about the moment problem on nuclear spaces with the techniques recently developed to treat the moment problem on basic semi-algebraic sets of Rd. In this way, we determine realizability conditions that can be more easily verified than the well-known Haviland type conditions. Our result completely characterizes the support of the realizing measure in terms of its moments. As concrete examples of semi-algebraic sets of generalized functions, we consider the set of all Radon measures and the set of all the measures having bounded Radon–Nikodym density w.r.t. the Lebesgue measure.

Specific leaf areas of the tank bromeliad Guzmania monostachia perform distinct functions in response to water shortage

Leaves comprise most of the vegetative body of tank bromeliads and are usually subjected to strong longitudinal gradients. For instance, while the leaf base is in contact with the water accumulated in the tank, the more light-exposed middle and upper leaf sections have no direct access to this water reservoir. Therefore, the present study attempted to investigate whether different leaf portions of Guzmania monostachia, a tank-forming C(3)-CAM bromeliad, play distinct physiological roles in response to water shortage, which is a major abiotic constraint in the epiphytic habitat. Internal and external morphological features, relative water content, pigment composition and the degree of CAM expression were evaluated in basal, middle and apical leaf portions in order to allow the establishment of correlations between the structure and the functional importance of each leaf region. Results indicated that besides marked structural differences, a high level of functional specialization is also present along the leaves of this bromeliad. When the tank water was depleted, the abundant hydrenchyma of basal leaf portions was the main reservoir for maintaining a stable water status in the photosynthetic tissues of the apical region. In contrast, the CAM pathway was intensified specifically in the upper leaf section, which is in agreement with the presence of features more suitable for the occurrence of photosynthesis at this portion. Gas exchange data indicated that internal recycling of respiratory CO(2) accounted for virtually all nighttime acid accumulation, characterizing a typical CAM-idling pathway in the drought-exposed plants. Altogether, these data reveal a remarkable physiological complexity along the leaves of G. monostachia, which might be a key adaptation to the intermittent water supply of the epiphytic niche. (C) 2009 Elsevier GmbH. All rights reserved.