MGMT testing-the challenges for biomarker-based glioma treatment.

Many patients with malignant gliomas do not respond to alkylating agent chemotherapy. Alkylator resistance of glioma cells is mainly mediated by the DNA repair enzyme O(6)-methylguanine-DNA methyltransferase (MGMT). Epigenetic silencing of the MGMT gene by promoter methylation in glioma cells compromises this DNA repair mechanism and increases chemosensitivity. MGMT promoter methylation is, therefore, a strong prognostic biomarker in paediatric and adult patients with glioblastoma treated with temozolomide. Notably, elderly patients (>65-70 years) with glioblastoma whose tumours lack MGMT promoter methylation derive minimal benefit from such chemotherapy. Thus, MGMT promoter methylation status has become a frequently requested laboratory test in neuro-oncology. This Review presents current data on the prognostic and predictive relevance of MGMT testing, discusses clinical trials that have used MGMT status to select participants, evaluates known issues concerning the molecular testing procedure, and addresses the necessity for molecular-context-dependent interpretation of MGMT test results. Whether MGMT promoter methylation testing should be offered to all individuals with glioblastoma, or only to elderly patients and those in clinical trials, is also discussed. Justifications for withholding alkylating agent chemotherapy in patients with MGMT-unmethylated glioblastomas outside clinical trials, and the potential role for MGMT testing in other gliomas, are also discussed.

Modeling and control of electromechanical systems

The material presented in the these notes covers the sessions Modelling of electromechanical systems, Passive control theory I and Passive control theory II of the II EURON/GEOPLEX Summer School on Modelling and Control of Complex Dynamical Systems.We start with a general description of what an electromechanical system is from a network modelling point of view. Next, a general formulation in terms of PHDS is introduced, and some of the previous electromechanical systems are rewritten in this formalism. Power converters, which are variable structure systems (VSS), can also be given a PHDS form.We conclude the modelling part of these lectures with a rather complex example, showing the interconnection of subsystems from several domains, namely an arrangement to temporally store the surplus energy in a section of a metropolitan transportation system based on dc motor vehicles, using either arrays of supercapacitors or an electric poweredflywheel. The second part of the lectures addresses control of PHD systems. We first present the idea of control as power connection of a plant and a controller. Next we discuss how to circumvent this obstacle and present the basic ideas of Interconnection and Damping Assignment (IDA) passivity-based control of PHD systems.

Recombinant human tumor necrosis factor: an efficient agent for cancer treatment.

Recombinant human TNF (rhTNF) has a selective effect on endothelial cells in tumour angiogenic vessels. Its clinical use has been limited because of its property to induce vascular collapsus. TNF administration through isolated limb perfusion (ILP) for regionally advanced melanomas and soft tissue sarcomas of the limbs was shown to be safe and efficient. When combined to the alkylating agent melphalan, a single ILP produces a very high objective response rate. ILP with TNF and melphalan provided the proof of concept that a vasculotoxic strategy combined to chemotherapy may produce a strong anti-tumour effect. The registered indication of TNF-based ILP is a regional therapy for regionally spread tumours. In soft tissue sarcomas, it is a limb sparing neoadjuvant treatment and, in melanoma in-transit metastases, a curative treatment. Despite its demonstrated regional efficiency TNF-based ILP is unlikely to have any impact on survival. High TNF dosages induce endothelial cells apoptosis, leading to vascular destruction. However, lower TNF dosage produces a very strong effect that is to increase the drug penetration into the tumour, presumably by decreasing the intratumoural hypertension resulting in better tumour uptake. TNF-ILP allowed the identification of the role of alphaVbeta3 integrin deactivation as an important mechanism of antiangiogenesis. Several recent studies have shown that TNF targeting is possible, paving the way to a new opportunity to administer TNF systemically for improving cancer drug penetration. TNF was the first agent registered for the treatment of cancer that improves drug penetration in tumours and selectively destroys angiogenic vessels.

Pore-scale modeling of two-phase flow instabilities in porous media

Les problèmes d'écoulements multiphasiques en média poreux sont d'un grand intérêt pour de nombreuses applications scientifiques et techniques ; comme la séquestration de C02, l'extraction de pétrole et la dépollution des aquifères. La complexité intrinsèque des systèmes multiphasiques et l'hétérogénéité des formations géologiques sur des échelles multiples représentent un challenge majeur pour comprendre et modéliser les déplacements immiscibles dans les milieux poreux. Les descriptions à l'échelle supérieure basées sur la généralisation de l'équation de Darcy sont largement utilisées, mais ces méthodes sont sujettes à limitations pour les écoulements présentant de l'hystérèse. Les avancées récentes en terme de performances computationnelles et le développement de méthodes précises pour caractériser l'espace interstitiel ainsi que la distribution des phases ont favorisé l'utilisation de modèles qui permettent une résolution fine à l'échelle du pore. Ces modèles offrent un aperçu des caractéristiques de l'écoulement qui ne peuvent pas être facilement observées en laboratoire et peuvent être utilisé pour expliquer la différence entre les processus physiques et les modèles à l'échelle macroscopique existants. L'objet premier de la thèse se porte sur la simulation numérique directe : les équations de Navier-Stokes sont résolues dans l'espace interstitiel et la méthode du volume de fluide (VOF) est employée pour suivre l'évolution de l'interface. Dans VOF, la distribution des phases est décrite par une fonction fluide pour l'ensemble du domaine et des conditions aux bords particulières permettent la prise en compte des propriétés de mouillage du milieu poreux. Dans la première partie de la thèse, nous simulons le drainage dans une cellule Hele-Shaw 2D avec des obstacles cylindriques. Nous montrons que l'approche proposée est applicable même pour des ratios de densité et de viscosité très importants et permet de modéliser la transition entre déplacement stable et digitation visqueuse. Nous intéressons ensuite à l'interprétation de la pression capillaire à l'échelle macroscopique. Nous montrons que les techniques basées sur la moyenne spatiale de la pression présentent plusieurs limitations et sont imprécises en présence d'effets visqueux et de piégeage. Au contraire, une définition basée sur l'énergie permet de séparer les contributions capillaires des effets visqueux. La seconde partie de la thèse est consacrée à l'investigation des effets d'inertie associés aux reconfigurations irréversibles du ménisque causé par l'interface des instabilités. Comme prototype pour ces phénomènes, nous étudions d'abord la dynamique d'un ménisque dans un pore angulaire. Nous montrons que, dans un réseau de pores cubiques, les sauts et reconfigurations sont si fréquents que les effets d'inertie mènent à différentes configurations des fluides. A cause de la non-linéarité du problème, la distribution des fluides influence le travail des forces de pression, qui, à son tour, provoque une chute de pression dans la loi de Darcy. Cela suggère que ces phénomènes devraient être pris en compte lorsque que l'on décrit l'écoulement multiphasique en média poreux à l'échelle macroscopique. La dernière partie de la thèse s'attache à démontrer la validité de notre approche par une comparaison avec des expériences en laboratoire : un drainage instable dans un milieu poreux quasi 2D (une cellule Hele-Shaw avec des obstacles cylindriques). Plusieurs simulations sont tournées sous différentes conditions aux bords et en utilisant différents modèles (modèle intégré 2D et modèle 3D) afin de comparer certaines quantités macroscopiques avec les observations au laboratoire correspondantes. Malgré le challenge de modéliser des déplacements instables, où, par définition, de petites perturbations peuvent grandir sans fin, notre approche numérique apporte de résultats satisfaisants pour tous les cas étudiés. - Problems involving multiphase flow in porous media are of great interest in many scientific and engineering applications including Carbon Capture and Storage, oil recovery and groundwater remediation. The intrinsic complexity of multiphase systems and the multi scale heterogeneity of geological formations represent the major challenges to understand and model immiscible displacement in porous media. Upscaled descriptions based on generalization of Darcy's law are widely used, but they are subject to several limitations for flow that exhibit hysteric and history- dependent behaviors. Recent advances in high performance computing and the development of accurate methods to characterize pore space and phase distribution have fostered the use of models that allow sub-pore resolution. These models provide an insight on flow characteristics that cannot be easily achieved by laboratory experiments and can be used to explain the gap between physical processes and existing macro-scale models. We focus on direct numerical simulations: we solve the Navier-Stokes equations for mass and momentum conservation in the pore space and employ the Volume Of Fluid (VOF) method to track the evolution of the interface. In the VOF the distribution of the phases is described by a fluid function (whole-domain formulation) and special boundary conditions account for the wetting properties of the porous medium. In the first part of this thesis we simulate drainage in a 2-D Hele-Shaw cell filled with cylindrical obstacles. We show that the proposed approach can handle very large density and viscosity ratios and it is able to model the transition from stable displacement to viscous fingering. We then focus on the interpretation of the macroscopic capillary pressure showing that pressure average techniques are subject to several limitations and they are not accurate in presence of viscous effects and trapping. On the contrary an energy-based definition allows separating viscous and capillary contributions. In the second part of the thesis we investigate inertia effects associated with abrupt and irreversible reconfigurations of the menisci caused by interface instabilities. As a prototype of these phenomena we first consider the dynamics of a meniscus in an angular pore. We show that in a network of cubic pores, jumps and reconfigurations are so frequent that inertia effects lead to different fluid configurations. Due to the non-linearity of the problem, the distribution of the fluids influences the work done by pressure forces, which is in turn related to the pressure drop in Darcy's law. This suggests that these phenomena should be taken into account when upscaling multiphase flow in porous media. The last part of the thesis is devoted to proving the accuracy of the numerical approach by validation with experiments of unstable primary drainage in a quasi-2D porous medium (i.e., Hele-Shaw cell filled with cylindrical obstacles). We perform simulations under different boundary conditions and using different models (2-D integrated and full 3-D) and we compare several macroscopic quantities with the corresponding experiment. Despite the intrinsic challenges of modeling unstable displacement, where by definition small perturbations can grow without bounds, the numerical method gives satisfactory results for all the cases studied.

Use of LIDAR-based Elevation Data for Highway Drainage Analysis: A Qualitative Assessment, 2003

US Geological Survey (USGS) based elevation data are the most commonly used data source for highway hydraulic analysis; however, due to the vertical accuracy of USGS-based elevation data, USGS data may be too “coarse” to adequately describe surface profiles of watershed areas or drainage patterns. Additionally hydraulic design requires delineation of much smaller drainage areas (watersheds) than other hydrologic applications, such as environmental, ecological, and water resource management. This research study investigated whether higher resolution LIDAR based surface models would provide better delineation of watersheds and drainage patterns as compared to surface models created from standard USGS-based elevation data. Differences in runoff values were the metric used to compare the data sets. The two data sets were compared for a pilot study area along the Iowa 1 corridor between Iowa City and Mount Vernon. Given the limited breadth of the analysis corridor, areas of particular emphasis were the location of drainage area boundaries and flow patterns parallel to and intersecting the road cross section. Traditional highway hydrology does not appear to be significantly impacted, or benefited, by the increased terrain detail that LIDAR provided for the study area. In fact, hydrologic outputs, such as streams and watersheds, may be too sensitive to the increased horizontal resolution and/or errors in the data set. However, a true comparison of LIDAR and USGS-based data sets of equal size and encompassing entire drainage areas could not be performed in this study. Differences may also result in areas with much steeper slopes or significant changes in terrain. LIDAR may provide possibly valuable detail in areas of modified terrain, such as roads. Better representations of channel and terrain detail in the vicinity of the roadway may be useful in modeling problem drainage areas and evaluating structural surety during and after significant storm events. Furthermore, LIDAR may be used to verify the intended/expected drainage patterns at newly constructed highways. LIDAR will likely provide the greatest benefit for highway projects in flood plains and areas with relatively flat terrain where slight changes in terrain may have a significant impact on drainage patterns.

Toxicokinetic modeling of folpet fungicide and its ring-biomarkers of exposure in humans.

A human in vivo toxicokinetic model was built to allow a better understanding of the toxicokinetics of folpet fungicide and its key ring biomarkers of exposure: phthalimide (PI), phthalamic acid (PAA) and phthalic acid (PA). Both PI and the sum of ring metabolites, expressed as PA equivalents (PAeq), may be used as biomarkers of exposure. The conceptual representation of the model was based on the analysis of the time course of these biomarkers in volunteers orally and dermally exposed to folpet. In the model, compartments were also used to represent the body burden of folpet and experimentally relevant PI, PAA and PA ring metabolites in blood and in key tissues as well as in excreta, hence urinary and feces. The time evolution of these biomarkers in each compartment of the model was then mathematically described by a system of coupled differential equations. The mathematical parameters of the model were then determined from best fits to the time courses of PI and PAeq in blood and urine of five volunteers administered orally 1 mg kg(-1) and dermally 10 mg kg(-1) of folpet. In the case of oral administration, the mean elimination half-life of PI from blood (through feces, urine or metabolism) was found to be 39.9 h as compared with 28.0 h for PAeq. In the case of a dermal application, mean elimination half-life of PI and PAeq was estimated to be 34.3 and 29.3 h, respectively. The average final fractions of administered dose recovered in urine as PI over the 0-96 h period were 0.030 and 0.002%, for oral and dermal exposure, respectively. Corresponding values for PAeq were 24.5 and 1.83%, respectively. Finally, the average clearance rate of PI from blood calculated from the oral and dermal data was 0.09 ± 0.03 and 0.13 ± 0.05 ml h(-1) while the volume of distribution was 4.30 ± 1.12 and 6.05 ± 2.22 l, respectively. It was not possible to obtain the corresponding values from PAeq data owing to the lack of blood time course data.

Combining digital elevation model analysis and run-out modeling to characterize hazard posed by a potentially unstable rock slope at Turtle Mountain, Alberta, Canada

Turtle Mountain in Alberta, Canada has become an important field laboratory for testing different techniques related to the characterization and monitoring of large slope mass movements as the stability of large portions of the eastern face of the mountain is still questionable. In order to better quantify the volumes potentially unstable and the most probable failure mechanisms and potential consequences, structural analysis and runout modeling were preformed. The structural features of the eastern face were investigated using a high resolution digital elevation model (HRDEM). According to displacement datasets and structural observations, potential failure mechanisms affecting different portions of the mountain have been assessed. The volumes of the different potentially unstable blocks have been calculated using the Sloping Local Base Level (SLBL) method. Based on the volume estimation, two and three dimensional dynamic runout analyses have been performed. Calibration of this analysis is based on the experience from the adjacent Frank Slide and other similar rock avalanches. The results will be used to improve the contingency plans within the hazard area.

Cancer chronotherapeutics: experimental, theoretical, and clinical aspects.

The circadian timing system controls cell cycle, apoptosis, drug bioactivation, and transport and detoxification mechanisms in healthy tissues. As a consequence, the tolerability of cancer chemotherapy varies up to several folds as a function of circadian timing of drug administration in experimental models. Best antitumor efficacy of single-agent or combination chemotherapy usually corresponds to the delivery of anticancer drugs near their respective times of best tolerability. Mathematical models reveal that such coincidence between chronotolerance and chronoefficacy is best explained by differences in the circadian and cell cycle dynamics of host and cancer cells, especially with regard circadian entrainment and cell cycle variability. In the clinic, a large improvement in tolerability was shown in international randomized trials where cancer patients received the same sinusoidal chronotherapy schedule over 24h as compared to constant-rate infusion or wrongly timed chronotherapy. However, sex, genetic background, and lifestyle were found to influence optimal chronotherapy scheduling. These findings support systems biology approaches to cancer chronotherapeutics. They involve the systematic experimental mapping and modeling of chronopharmacology pathways in synchronized cell cultures and their adjustment to mouse models of both sexes and distinct genetic background, as recently shown for irinotecan. Model-based personalized circadian drug delivery aims at jointly improving tolerability and efficacy of anticancer drugs based on the circadian timing system of individual patients, using dedicated circadian biomarker and drug delivery technologies.

Modeling morphogen gradient formation from arbitrary realistically shaped sources.

Much of the analytical modeling of morphogen profiles is based on simplistic scenarios, where the source is abstracted to be point-like and fixed in time, and where only the steady state solution of the morphogen gradient in one dimension is considered. Here we develop a general formalism allowing to model diffusive gradient formation from an arbitrary source. This mathematical framework, based on the Green's function method, applies to various diffusion problems. In this paper, we illustrate our theory with the explicit example of the Bicoid gradient establishment in Drosophila embryos. The gradient formation arises by protein translation from a mRNA distribution followed by morphogen diffusion with linear degradation. We investigate quantitatively the influence of spatial extension and time evolution of the source on the morphogen profile. For different biologically meaningful cases, we obtain explicit analytical expressions for both the steady state and time-dependent 1D problems. We show that extended sources, whether of finite size or normally distributed, give rise to more realistic gradients compared to a single point-source at the origin. Furthermore, the steady state solutions are fully compatible with a decreasing exponential behavior of the profile. We also consider the case of a dynamic source (e.g. bicoid mRNA diffusion) for which a protein profile similar to the ones obtained from static sources can be achieved.

A connectome-based comparison of diffusion MRI schemes.

Diffusion MRI has evolved towards an important clinical diagnostic and research tool. Though clinical routine is using mainly diffusion weighted and tensor imaging approaches, Q-ball imaging and diffusion spectrum imaging techniques have become more widely available. They are frequently used in research-oriented investigations in particular those aiming at measuring brain network connectivity. In this work, we aim at assessing the dependency of connectivity measurements on various diffusion encoding schemes in combination with appropriate data modeling. We process and compare the structural connection matrices computed from several diffusion encoding schemes, including diffusion tensor imaging, q-ball imaging and high angular resolution schemes, such as diffusion spectrum imaging with a publically available processing pipeline for data reconstruction, tracking and visualization of diffusion MR imaging. The results indicate that the high angular resolution schemes maximize the number of obtained connections when applying identical processing strategies to the different diffusion schemes. Compared to the conventional diffusion tensor imaging, the added connectivity is mainly found for pathways in the 50-100mm range, corresponding to neighboring association fibers and long-range associative, striatal and commissural fiber pathways. The analysis of the major associative fiber tracts of the brain reveals striking differences between the applied diffusion schemes. More complex data modeling techniques (beyond tensor model) are recommended 1) if the tracts of interest run through large fiber crossings such as the centrum semi-ovale, or 2) if non-dominant fiber populations, e.g. the neighboring association fibers are the subject of investigation. An important finding of the study is that since the ground truth sensitivity and specificity is not known, the comparability between results arising from different strategies in data reconstruction and/or tracking becomes implausible to understand.

Preclinical evaluation of the immunogenicity of C-type HIV-1-based DNA and NYVAC vaccines in the Balb/C mouse model.

As part of a European initiative (EuroVacc), we report the design, construction, and immunogenicity of two HIV-1 vaccine candidates based on a clade C virus strain (CN54) representing the current major epidemic in Asia and parts of Africa. Open reading frames encoding an artificial 160-kDa GagPolNef (GPN) polyprotein and the external glycoprotein gp120 were fully RNA and codon optimized. A DNA vaccine (DNA-GPN and DNA-gp120, referred to as DNA-C), and a replication-deficient vaccinia virus encoding both reading frames (NYVAC-C), were assessed regarding immunogenicity in Balb/C mice. The intramuscular administration of both plasmid DNA constructs, followed by two booster DNA immunizations, induced substantial T-cell responses against both antigens as well as Env-specific antibodies. Whereas low doses of NYVAC-C failed to induce specific CTL or antibodies, high doses generated cellular as well as humoral immune responses, but these did not reach the levels seen following DNA vaccination. The most potent immune responses were detectable using prime:boost protocols, regardless of whether DNA-C or NYVAC-C was used as the priming or boosting agent. These preclinical findings revealed the immunogenic response triggered by DNA-C and its enhancement by combining it with NYVAC-C, thus complementing the macaque preclinical and human phase I clinical studies of EuroVacc.

ADME pharmacogenetics: investigation of the pharmacokinetics of the antiretroviral agent lopinavir coformulated with ritonavir.

BACKGROUND: An ADME (absorption, distribution, metabolism and excretion)-pharmacogenetics association study may identify functional variants relevant to the pharmacokinetics of lopinavir co-formulated with ritonavir (LPV/r), a first-line anti-HIV agent. METHODS: An extensive search of literature and web resources helped select ADME genes and single nucleotide polymorphisms (SNPs, functional and HapMap tagging SNPs) with a proven or potentially relevant role in LPV/r pharmacokinetics. The study followed a two-stage design. Stage 1 (discovery) considered a Caucasian population (n=638) receiving LPV/r, where we selected 117 individuals with low LPV clearance (cases) and 90 individuals with high clearance (controls). Genotyping was performed by a 1536-SNP customized GoldenGate Illumina BeadArray. Stage 2 (confirmation) represented a replication study of candidate SNPs from the stage 1 in 148 individuals receiving LPV/r. The analysis led to formal population pharmacokinetic-pharmacogenetic modeling of demographic, environmental and candidate SNP effects. RESULTS: One thousand three hundred and eighty SNPs were successfully genotyped. Nine SNPs prioritized by the stage 1 analysis were brought to replication. Stage 2 confirmed the contribution of two functional SNPs in SLCO1B1, one functional SNP in ABCC2 and a tag SNP of the CYP3A locus in addition to body weight effect and ritonavir coadministration. According to the population pharmacokinetic-pharmacogenetic model, genetic variants explained 5% of LPV variability. Individuals homozygous rs11045819 (SLCO1B1*4) had a clearance of 12.6 l/h, compared with 5.4 l/h in the reference group, and 3.9 l/h in individuals with two or more variant alleles of rs4149056 (SLCO1B1*5), rs717620 (ABCC2) or rs6945984 (CYP3A). A subanalysis confirmed that although a significant part of the variance in LPV clearance was attributed to fluctuation in ritonavir levels, genetic variants had an additional effect on LPV clearance. CONCLUSION: The two-stage strategy successfully identified genetic variants affecting LPV/r pharmacokinetics. Such a general approach of ADME pharmacogenetics should be generalized to other drugs.

Implicit methods for qualitative modeling of gene regulatory networks.

Advancements in high-throughput technologies to measure increasingly complex biological phenomena at the genomic level are rapidly changing the face of biological research from the single-gene single-protein experimental approach to studying the behavior of a gene in the context of the entire genome (and proteome). This shift in research methodologies has resulted in a new field of network biology that deals with modeling cellular behavior in terms of network structures such as signaling pathways and gene regulatory networks. In these networks, different biological entities such as genes, proteins, and metabolites interact with each other, giving rise to a dynamical system. Even though there exists a mature field of dynamical systems theory to model such network structures, some technical challenges are unique to biology such as the inability to measure precise kinetic information on gene-gene or gene-protein interactions and the need to model increasingly large networks comprising thousands of nodes. These challenges have renewed interest in developing new computational techniques for modeling complex biological systems. This chapter presents a modeling framework based on Boolean algebra and finite-state machines that are reminiscent of the approach used for digital circuit synthesis and simulation in the field of very-large-scale integration (VLSI). The proposed formalism enables a common mathematical framework to develop computational techniques for modeling different aspects of the regulatory networks such as steady-state behavior, stochasticity, and gene perturbation experiments.

Promoting the development of secure mobile agent applications

Peer-reviewed

JPEG standard uniform quantization error modeling with applications to sequential and progressive operation modes

In this paper we propose a method for computing JPEG quantization matrices for a given mean square error or PSNR. Then, we employ our method to compute JPEG standard progressive operation mode definition scripts using a quantization approach. Therefore, it is no longer necessary to use a trial and error procedure to obtain a desired PSNR and/or definition script, reducing cost. Firstly, we establish a relationship between a Laplacian source and its uniform quantization error. We apply this model to the coefficients obtained in the discrete cosine transform stage of the JPEG standard. Then, an image may be compressed using the JPEG standard under a global MSE (or PSNR) constraint and a set of local constraints determined by the JPEG standard and visual criteria. Secondly, we study the JPEG standard progressive operation mode from a quantization based approach. A relationship between the measured image quality at a given stage of the coding process and a quantization matrix is found. Thus, the definition script construction problem can be reduced to a quantization problem. Simulations show that our method generates better quantization matrices than the classical method based on scaling the JPEG default quantization matrix. The estimation of PSNR has usually an error smaller than 1 dB. This figure decreases for high PSNR values. Definition scripts may be generated avoiding an excessive number of stages and removing small stages that do not contribute during the decoding process with a noticeable image quality improvement.