Don't bleach chaotic data

A common first step in time series signal analysis involves digitally filtering the data to remove linear correlations. The residual data is spectrally white (it is ``bleached''), but in principle retains the nonlinear structure of the original time series. It is well known that simple linear autocorrelation can give rise to spurious results in algorithms for estimating nonlinear invariants, such as fractal dimension and Lyapunov exponents. In theory, bleached data avoids these pitfalls. But in practice, bleaching obscures the underlying deterministic structure of a low-dimensional chaotic process. This appears to be a property of the chaos itself, since nonchaotic data are not similarly affected. The adverse effects of bleaching are demonstrated in a series of numerical experiments on known chaotic data. Some theoretical aspects are also discussed.Comment: 12 dense pages (82K) of ordinary LaTeX; uses macro psfig.tex for inclusion of figures in text; figures are uufile'd into a single file of size 306K; the final dvips'd postscript file is about 1.3mb Replaced 9/30/93 to incorporate final changes in the proofs and to make the LaTeX more portable; the paper will appear in CHAOS 4 (Dec, 1993

Combined transcriptomic-(1)H NMR metabonomic study reveals yhat monoethylhexyl phthalate stimulates adipogenesis and glyceroneogenesis in human adipocytes

Adipose tissue is a major storage site for lipophilic environmental contaminants. The environmental metabolic disruptor hypothesis postulates that some pollutants can promote obesity or metabolic disorders by activating nuclear receptors involved in the control of energetic homeostasis. In this context, monoethylhexyl phthalate (MEHP) is of particular concern since it was shown to activate the peroxisome proliferator-activated receptor γ (PPARγ) in 3T3-L1 murine preadipocytes. In the present work, we used an untargeted, combined transcriptomic-(1)H NMR-based metabonomic approach to describe the overall effect of MEHP on primary cultures of human subcutaneous adipocytes differentiated in vitro. MEHP stimulated rapidly and selectively the expression of genes involved in glyceroneogenesis, enhanced the expression of the cytosolic phosphoenolpyruvate carboxykinase, and reduced fatty acid release. These results demonstrate that MEHP increased glyceroneogenesis and fatty acid reesterification in human adipocytes. A longer treatment with MEHP induced the expression of genes involved in triglycerides uptake, synthesis, and storage; decreased intracellular lactate, glutamine, and other amino acids; increased aspartate and NAD, and resulted in a global increase in triglycerides. Altogether, these results indicate that MEHP promoted the differentiation of human preadipocytes to adipocytes. These mechanisms might contribute to the suspected obesogenic effect of MEHP

The complex TIE between macrophages and angiogenesis

Macrophages are primarily known as phagocytic immune cells, but they also play a role in diverse processes, such as morphogenesis, homeostasis and regeneration. In this review, we discuss the influence of macrophages on angiogenesis, the process of new blood vessel formation from the pre-existing vasculature. Macrophages play crucial roles at each step of the angiogenic cascade, starting from new blood vessel sprouting to the remodelling of the vascular plexus and vessel maturation. Macrophages form promising targets for both pro- and anti-angiogenic treatments. However, to target macrophages, we will first need to understand the mechanisms that control the functional plasticity of macrophages during each of the steps of the angiogenic cascade. Here, we review recent insights in this topic. Special attention will be given to the TIE2-expressing macrophage (TEM), which is a subtype of highly angiogenic macrophages that is able to influence angiogenesis via the angiopoietin-TIE pathway

Overlay of conventional angiographic and en-face OCT images enhances their interpretation

BACKGROUND: Combining characteristic morphological and functional information in one image increases pathophysiologic understanding as well as diagnostic accuracy in most clinical settings. En-face optical coherence tomography (OCT) provides a high resolution, transversal OCT image of the macular area combined with a confocal image of the same area (OCT C-scans). Creating an overlay image of a conventional angiographic image onto an OCT image, using the confocal part to facilitate transformation, combines structural and functional information of the retinal area of interest. This paper describes the construction of such overlay images and their aid in improving the interpretation of OCT C-scans. METHODS: In various patients, en-face OCT C-scans (made with a prototype OCT-Ophthalmoscope (OTI, Canada) in use at the Department of Ophthalmology (Academic Medical Centre, Amsterdam, The Netherlands)) and conventional fluorescein angiography (FA) were performed. ImagePro, with a custom made plug-in, was used to make an overlay-image. The confocal part of the OCT C-scan was used to spatially transform the FA image onto the OCT C-scan, using the vascular arcades as a reference. To facilitate visualization the transformed angiographic image and the OCT C-scan were combined in an RGB image. RESULTS: The confocal part of the OCT C-scan could easily be fused with angiographic images. Overlay showed a direct correspondence between retinal thickening and FA leakage in Birdshot retinochoroiditis, localized the subretinal neovascular membrane and correlated anatomic and vascular leakage features in myopia, and showed the extent of retinal and pigment epithelial detachment in retinal angiomatous proliferation as FA leakage was subject to blocked fluorescence. The overlay mode provided additional insight not readily available in either mode alone. CONCLUSION: Combining conventional angiographic images and en-face OCT C-scans assists in the interpretation of both imaging modalities. By combining the physiopathological information in the angiograms with the structural information in the OCT scan, zones of leakage can be correlated to structural changes in the retina or pigment epithelium. This strategy could be used in the evaluation and monitoring of patients with complex central macular pathology

Donors, Aid and Taxation in Developing Countries: An Overview

Recent years have witnessed rapidly growing donor interest in tax issues in the developing world. This reflects a concern with revenue collection to finance public spending, but also recognition of the centrality of taxation to growth, redistribution and broader state-building and governance goals. Against this backdrop, this paper identifies a series of key issues that demand attention if donors are to improve the quality of their support for tax reform. The focus is not, primarily, on the technical design of tax interventions, but, instead, on seven ‘big picture’ considerations for the design of donor programmes: (a) supporting local leadership of reform efforts; (b) incorporating more systematic political economy analysis into the design and implementation of reform programmes; (c) designing tax reform programmes that seek to foster broader linkages between taxation, state-building and governance; (d) paying careful attention to the complexity of the relationship between aid and tax effort; (e) better designing tax-related conditionality, particularly by developing a more nuanced set of performance indicators; (f) ensuring the effective coordination of donor interventions; and (g) paying greater attention to the international policy context, and particularly the role of tax exemptions for donor projects, tax havens and tax evasion by multinational corporations (MNCs) in undermining developing country tax systems.DfI

Reconstructing the 2003/2004 H3N2 influenza epidemic in Switzerland with a spatially explicit, individual-based model

ABSTRACT: BACKGROUND: Simulation models of influenza spread play an important role for pandemic preparedness. However, as the world has not faced a severe pandemic for decades, except the rather mild H1N1 one in 2009, pandemic influenza models are inherently hypothetical and validation is, thus, difficult. We aim at reconstructing a recent seasonal influenza epidemic that occurred in Switzerland and deem this to be a promising validation strategy for models of influenza spread. METHODS: We present a spatially explicit, individual-based simulation model of influenza spread. The simulation model bases upon (i) simulated human travel data, (ii) data on human contact patterns and (iii) empirical knowledge on the epidemiology of influenza. For model validation we compare the simulation outcomes with empirical knowledge regarding (i) the shape of the epidemic curve, overall infection rate and reproduction number, (ii) age-dependent infection rates and time of infection, (iii) spatial patterns. RESULTS: The simulation model is capable of reproducing the shape of the 2003/2004 H3N2 epidemic curve of Switzerland and generates an overall infection rate (14.9 percent) and reproduction numbers (between 1.2 and 1.3), which are realistic for seasonal influenza epidemics. Age and spatial patterns observed in empirical data are also reflected by the model: Highest infection rates are in children between 5 and 14 and the disease spreads along the main transport axes from west to east. CONCLUSIONS: We show that finding evidence for the validity of simulation models of influenza spread by challenging them with seasonal influenza outbreak data is possible and promising. Simulation models for pandemic spread gain more credibility if they are able to reproduce seasonal influenza outbreaks. For more robust modelling of seasonal influenza, serological data complementing sentinel information would be beneficia

Multi-agent systems in epidemiology: a first step for computational biology in the study of vector-borne disease transmission

<p>Abstract</p> <p>Background</p> <p>Computational biology is often associated with genetic or genomic studies only. However, thanks to the increase of computational resources, computational models are appreciated as useful tools in many other scientific fields. Such modeling systems are particularly relevant for the study of complex systems, like the epidemiology of emerging infectious diseases. So far, mathematical models remain the main tool for the epidemiological and ecological analysis of infectious diseases, with SIR models could be seen as an implicit standard in epidemiology. Unfortunately, these models are based on differential equations and, therefore, can become very rapidly unmanageable due to the too many parameters which need to be taken into consideration. For instance, in the case of zoonotic and vector-borne diseases in wildlife many different potential host species could be involved in the life-cycle of disease transmission, and SIR models might not be the most suitable tool to truly capture the overall disease circulation within that environment. This limitation underlines the necessity to develop a standard spatial model that can cope with the transmission of disease in realistic ecosystems.</p> <p>Results</p> <p>Computational biology may prove to be flexible enough to take into account the natural complexity observed in both natural and man-made ecosystems. In this paper, we propose a new computational model to study the transmission of infectious diseases in a spatially explicit context. We developed a multi-agent system model for vector-borne disease transmission in a realistic spatial environment.</p> <p>Conclusion</p> <p>Here we describe in detail the general behavior of this model that we hope will become a standard reference for the study of vector-borne disease transmission in wildlife. To conclude, we show how this simple model could be easily adapted and modified to be used as a common framework for further research developments in this field.</p

The role of chemotherapeutic drugs in the evaluation of breast tumour response to chemotherapy using serial FDG-PET

INTRODUCTION: The aims of this study were to investigate whether drug sequence (docetaxel followed by anthracyclines or the drugs in reverse order) affects changes in the maximal standard uptake volume (SUVmax) on [18F]fluorodeoxyglucose positron emission tomography (FDG-PET) during neoadjuvant chemotherapy in women with locally advanced breast cancer. METHODS: Women were randomly assigned to receive either drug sequence, and FDG-PET scans were taken at baseline, after four cycles and after eight cycles of chemotherapy. Tumour response to chemotherapy was evaluated based on histology from a surgical specimen collected upon completion of chemotherapy. RESULTS: Sixty women were enrolled into the study. Thirty-one received docetaxel followed by anthracyclines (Arm A) and 29 received drugs in the reverse order (Arm B). Most women (83%) had ductal carcinoma and 10 women (17%) had lobular or lobular/ductal carcinoma. All but one tumour were downstaged during therapy. Overall, there was no significant difference in response between the two drug regimens. However, women in Arm B who achieved complete pathological response had mean FDG-PET SUVmax reduction of 87.7% after four cycles, in contrast to those who had no or minor pathological response. These women recorded mean SUVmax reductions of only 27% (P < 0.01). Women in Arm A showed no significant difference in SUVmax response according to pathological response. Sensitivity, specificity, accuracy and positive and negative predictive values were highest in women in Arm B. CONCLUSIONS: Our results show that SUVmax uptake by breast tumours during chemotherapy can be dependent on the drugs used. Care must be taken when interpreting FDG-PET in settings where patients receive varied drug protocols

Towards a characterization of behavior-disease models

The last decade saw the advent of increasingly realistic epidemic models that leverage on the availability of highly detailed census and human mobility data. Data-driven models aim at a granularity down to the level of households or single individuals. However, relatively little systematic work has been done to provide coupled behavior-disease models able to close the feedback loop between behavioral changes triggered in the population by an individual's perception of the disease spread and the actual disease spread itself. While models lacking this coupling can be extremely successful in mild epidemics, they obviously will be of limited use in situations where social disruption or behavioral alterations are induced in the population by knowledge of the disease. Here we propose a characterization of a set of prototypical mechanisms for self-initiated social distancing induced by local and non-local prevalence-based information available to individuals in the population. We characterize the effects of these mechanisms in the framework of a compartmental scheme that enlarges the basic SIR model by considering separate behavioral classes within the population. The transition of individuals in/out of behavioral classes is coupled with the spreading of the disease and provides a rich phase space with multiple epidemic peaks and tipping points. The class of models presented here can be used in the case of data-driven computational approaches to analyze scenarios of social adaptation and behavioral change.Comment: 24 pages, 15 figure