On-Line Real-Time Service-Oriented Task Scheduling Using TUF

We present our approach to real-time service-oriented scheduling problems with the objective of maximizing the total system utility. Different from the traditional utility accrual scheduling problems that each task is associated with only a single time utility function (TUF), we associate two different TUFs—a profit TUF and a penalty TUF—with each task, to model the real-time services that not only need to reward the early completions but also need to penalize the abortions or deadline misses. The scheduling heuristics we proposed in this paper judiciously accept, schedule, and abort real-time services when necessary to maximize the accrued utility. Our extensive experimental results show that our proposed algorithms can significantly outperform the traditional scheduling algorithms such as the Earliest Deadline First (EDF), the traditional utility accrual (UA) scheduling algorithms, and an earlier scheduling approach based on a similar model.

A Comparative Study of Concurrent Acoustic and Diver Survey Data, and Fish Community Descriptions of a High Latitude Coral Reef, Florida, USA

Fisheries independent data on relatively unstudied nekton communities were used to explore the efficacy of new tools to be applied in the investigation of shallow coastal coral reef habitats. These data obtained through concurrent diver visual and acoustic surveys provided descriptions of spatial community distribution patterns across seasonal temporal scales in a previously undocumented region. Fish density estimates by both diver and acoustic methodologies showed a general agreement in ability to detect distributional patterns across reef tracts, though magnitude of density estimates were different. Fish communities in southeastern Florida showed significant trends in spatial distribution and seasonal abundance, with higher estimates of biomass obtained in the dry season. Further, community composition shifted across reef tracts and seasons as a function of the movements of several key reef species.

Structure and dynamics of thin colloidal films

This thesis begins by studying the thickness of evaporative spin coated colloidal crystals and demonstrates the variation of the thickness as a function of suspension concentration and spin rate. Particularly, the films are thicker with higher suspension concentration and lower spin rate. This study also provides evidence for the reproducibility of spin coating in terms of the thickness of the resulting colloidal films. These colloidal films, as well as the ones obtained from various other methods such as convective assembly and dip coating, usually possess a crystalline structure. Due to the lack of a comprehensive method for characterization of order in colloidal structures, a procedure is developed for such a characterization in terms of local and longer range translational and orientational order. Translational measures turn out to be adequate for characterizing small deviations from perfect order, while orientational measures are more informative for polycrystalline and highly disordered crystals. Finally, to obtain an understanding of the relationship between dynamics and structure, the dynamics of colloids in a quasi-2D suspension as a function of packing fraction is studied. The tools that are used are mean square displacement (MSD) and the self part of the van Hove function. The slow down of dynamics is observed as the packing fraction increases, accompanied with the emergence of 6-fold symmetry within the system. The dynamics turns out to be non-Gaussian at early times and Gaussian at later times for packing fractions below 0.6. Above this packing fraction, the dynamics is non-Gaussian at all times. Also the diffusion coefficient is calculated from MSD and the van Hove function. It goes down as the packing fraction is increased.

Bayesian adaptive estimation of arbitrary points on a psychometric function

Bayesian adaptive methods have been extensively used in psychophysics to estimate the point at which performance on a task attains arbitrary percentage levels, although the statistical properties of these estimators have never been assessed. We used simulation techniques to determine the small-sample properties of Bayesian estimators of arbitrary performance points, specifically addressing the issues of bias and precision as a function of the target percentage level. The study covered three major types of psychophysical task (yes-no detection, 2AFC discrimination and 2AFC detection) and explored the entire range of target performance levels allowed for by each task. Other factors included in the study were the form and parameters of the actual psychometric function Psi, the form and parameters of the model function M assumed in the Bayesian method, and the location of Psi within the parameter space. Our results indicate that Bayesian adaptive methods render unbiased estimators of any arbitrary point on psi only when M=Psi, and otherwise they yield bias whose magnitude can be considerable as the target level moves away from the midpoint of the range of Psi. The standard error of the estimator also increases as the target level approaches extreme values whether or not M=Psi. Contrary to widespread belief, neither the performance level at which bias is null nor that at which standard error is minimal can be predicted by the sweat factor. A closed-form expression nevertheless gives a reasonable fit to data describing the dependence of standard error on number of trials and target level, which allows determination of the number of trials that must be administered to obtain estimates with prescribed precision.

Antenatal origins of reduced lung function : but not asthma?

Peer reviewed

Advanced Techniques for Image Quality Assessment of Modern X-ray Computed Tomography Systems

X-ray computed tomography (CT) imaging constitutes one of the most widely used diagnostic tools in radiology today with nearly 85 million CT examinations performed in the U.S in 2011. CT imparts a relatively high amount of radiation dose to the patient compared to other x-ray imaging modalities and as a result of this fact, coupled with its popularity, CT is currently the single largest source of medical radiation exposure to the U.S. population. For this reason, there is a critical need to optimize CT examinations such that the dose is minimized while the quality of the CT images is not degraded. This optimization can be difficult to achieve due to the relationship between dose and image quality. All things being held equal, reducing the dose degrades image quality and can impact the diagnostic value of the CT examination.

A recent push from the medical and scientific community towards using lower doses has spawned new dose reduction technologies such as automatic exposure control (i.e., tube current modulation) and iterative reconstruction algorithms. In theory, these technologies could allow for scanning at reduced doses while maintaining the image quality of the exam at an acceptable level. Therefore, there is a scientific need to establish the dose reduction potential of these new technologies in an objective and rigorous manner. Establishing these dose reduction potentials requires precise and clinically relevant metrics of CT image quality, as well as practical and efficient methodologies to measure such metrics on real CT systems. The currently established methodologies for assessing CT image quality are not appropriate to assess modern CT scanners that have implemented those aforementioned dose reduction technologies.

Thus the purpose of this doctoral project was to develop, assess, and implement new phantoms, image quality metrics, analysis techniques, and modeling tools that are appropriate for image quality assessment of modern clinical CT systems. The project developed image quality assessment methods in the context of three distinct paradigms, (a) uniform phantoms, (b) textured phantoms, and (c) clinical images.

The work in this dissertation used the “task-based” definition of image quality. That is, image quality was broadly defined as the effectiveness by which an image can be used for its intended task. Under this definition, any assessment of image quality requires three components: (1) A well defined imaging task (e.g., detection of subtle lesions), (2) an “observer” to perform the task (e.g., a radiologists or a detection algorithm), and (3) a way to measure the observer’s performance in completing the task at hand (e.g., detection sensitivity/specificity).

First, this task-based image quality paradigm was implemented using a novel multi-sized phantom platform (with uniform background) developed specifically to assess modern CT systems (Mercury Phantom, v3.0, Duke University). A comprehensive evaluation was performed on a state-of-the-art CT system (SOMATOM Definition Force, Siemens Healthcare) in terms of noise, resolution, and detectability as a function of patient size, dose, tube energy (i.e., kVp), automatic exposure control, and reconstruction algorithm (i.e., Filtered Back-Projection– FPB vs Advanced Modeled Iterative Reconstruction– ADMIRE). A mathematical observer model (i.e., computer detection algorithm) was implemented and used as the basis of image quality comparisons. It was found that image quality increased with increasing dose and decreasing phantom size. The CT system exhibited nonlinear noise and resolution properties, especially at very low-doses, large phantom sizes, and for low-contrast objects. Objective image quality metrics generally increased with increasing dose and ADMIRE strength, and with decreasing phantom size. The ADMIRE algorithm could offer comparable image quality at reduced doses or improved image quality at the same dose (increase in detectability index by up to 163% depending on iterative strength). The use of automatic exposure control resulted in more consistent image quality with changing phantom size.

Based on those results, the dose reduction potential of ADMIRE was further assessed specifically for the task of detecting small (<=6 mm) low-contrast (<=20 HU) lesions. A new low-contrast detectability phantom (with uniform background) was designed and fabricated using a multi-material 3D printer. The phantom was imaged at multiple dose levels and images were reconstructed with FBP and ADMIRE. Human perception experiments were performed to measure the detection accuracy from FBP and ADMIRE images. It was found that ADMIRE had equivalent performance to FBP at 56% less dose.

Using the same image data as the previous study, a number of different mathematical observer models were implemented to assess which models would result in image quality metrics that best correlated with human detection performance. The models included naïve simple metrics of image quality such as contrast-to-noise ratio (CNR) and more sophisticated observer models such as the non-prewhitening matched filter observer model family and the channelized Hotelling observer model family. It was found that non-prewhitening matched filter observers and the channelized Hotelling observers both correlated strongly with human performance. Conversely, CNR was found to not correlate strongly with human performance, especially when comparing different reconstruction algorithms.

The uniform background phantoms used in the previous studies provided a good first-order approximation of image quality. However, due to their simplicity and due to the complexity of iterative reconstruction algorithms, it is possible that such phantoms are not fully adequate to assess the clinical impact of iterative algorithms because patient images obviously do not have smooth uniform backgrounds. To test this hypothesis, two textured phantoms (classified as gross texture and fine texture) and a uniform phantom of similar size were built and imaged on a SOMATOM Flash scanner (Siemens Healthcare). Images were reconstructed using FBP and a Sinogram Affirmed Iterative Reconstruction (SAFIRE). Using an image subtraction technique, quantum noise was measured in all images of each phantom. It was found that in FBP, the noise was independent of the background (textured vs uniform). However, for SAFIRE, noise increased by up to 44% in the textured phantoms compared to the uniform phantom. As a result, the noise reduction from SAFIRE was found to be up to 66% in the uniform phantom but as low as 29% in the textured phantoms. Based on this result, it clear that further investigation was needed into to understand the impact that background texture has on image quality when iterative reconstruction algorithms are used.

To further investigate this phenomenon with more realistic textures, two anthropomorphic textured phantoms were designed to mimic lung vasculature and fatty soft tissue texture. The phantoms (along with a corresponding uniform phantom) were fabricated with a multi-material 3D printer and imaged on the SOMATOM Flash scanner. Scans were repeated a total of 50 times in order to get ensemble statistics of the noise. A novel method of estimating the noise power spectrum (NPS) from irregularly shaped ROIs was developed. It was found that SAFIRE images had highly locally non-stationary noise patterns with pixels near edges having higher noise than pixels in more uniform regions. Compared to FBP, SAFIRE images had 60% less noise on average in uniform regions for edge pixels, noise was between 20% higher and 40% lower. The noise texture (i.e., NPS) was also highly dependent on the background texture for SAFIRE. Therefore, it was concluded that quantum noise properties in the uniform phantoms are not representative of those in patients for iterative reconstruction algorithms and texture should be considered when assessing image quality of iterative algorithms.

The move beyond just assessing noise properties in textured phantoms towards assessing detectability, a series of new phantoms were designed specifically to measure low-contrast detectability in the presence of background texture. The textures used were optimized to match the texture in the liver regions actual patient CT images using a genetic algorithm. The so called “Clustured Lumpy Background” texture synthesis framework was used to generate the modeled texture. Three textured phantoms and a corresponding uniform phantom were fabricated with a multi-material 3D printer and imaged on the SOMATOM Flash scanner. Images were reconstructed with FBP and SAFIRE and analyzed using a multi-slice channelized Hotelling observer to measure detectability and the dose reduction potential of SAFIRE based on the uniform and textured phantoms. It was found that at the same dose, the improvement in detectability from SAFIRE (compared to FBP) was higher when measured in a uniform phantom compared to textured phantoms.

The final trajectory of this project aimed at developing methods to mathematically model lesions, as a means to help assess image quality directly from patient images. The mathematical modeling framework is first presented. The models describe a lesion’s morphology in terms of size, shape, contrast, and edge profile as an analytical equation. The models can be voxelized and inserted into patient images to create so-called “hybrid” images. These hybrid images can then be used to assess detectability or estimability with the advantage that the ground truth of the lesion morphology and location is known exactly. Based on this framework, a series of liver lesions, lung nodules, and kidney stones were modeled based on images of real lesions. The lesion models were virtually inserted into patient images to create a database of hybrid images to go along with the original database of real lesion images. ROI images from each database were assessed by radiologists in a blinded fashion to determine the realism of the hybrid images. It was found that the radiologists could not readily distinguish between real and virtual lesion images (area under the ROC curve was 0.55). This study provided evidence that the proposed mathematical lesion modeling framework could produce reasonably realistic lesion images.

Based on that result, two studies were conducted which demonstrated the utility of the lesion models. The first study used the modeling framework as a measurement tool to determine how dose and reconstruction algorithm affected the quantitative analysis of liver lesions, lung nodules, and renal stones in terms of their size, shape, attenuation, edge profile, and texture features. The same database of real lesion images used in the previous study was used for this study. That database contained images of the same patient at 2 dose levels (50% and 100%) along with 3 reconstruction algorithms from a GE 750HD CT system (GE Healthcare). The algorithms in question were FBP, Adaptive Statistical Iterative Reconstruction (ASiR), and Model-Based Iterative Reconstruction (MBIR). A total of 23 quantitative features were extracted from the lesions under each condition. It was found that both dose and reconstruction algorithm had a statistically significant effect on the feature measurements. In particular, radiation dose affected five, three, and four of the 23 features (related to lesion size, conspicuity, and pixel-value distribution) for liver lesions, lung nodules, and renal stones, respectively. MBIR significantly affected 9, 11, and 15 of the 23 features (including size, attenuation, and texture features) for liver lesions, lung nodules, and renal stones, respectively. Lesion texture was not significantly affected by radiation dose.

The second study demonstrating the utility of the lesion modeling framework focused on assessing detectability of very low-contrast liver lesions in abdominal imaging. Specifically, detectability was assessed as a function of dose and reconstruction algorithm. As part of a parallel clinical trial, images from 21 patients were collected at 6 dose levels per patient on a SOMATOM Flash scanner. Subtle liver lesion models (contrast = -15 HU) were inserted into the raw projection data from the patient scans. The projections were then reconstructed with FBP and SAFIRE (strength 5). Also, lesion-less images were reconstructed. Noise, contrast, CNR, and detectability index of an observer model (non-prewhitening matched filter) were assessed. It was found that SAFIRE reduced noise by 52%, reduced contrast by 12%, increased CNR by 87%. and increased detectability index by 65% compared to FBP. Further, a 2AFC human perception experiment was performed to assess the dose reduction potential of SAFIRE, which was found to be 22% compared to the standard of care dose.

In conclusion, this dissertation provides to the scientific community a series of new methodologies, phantoms, analysis techniques, and modeling tools that can be used to rigorously assess image quality from modern CT systems. Specifically, methods to properly evaluate iterative reconstruction have been developed and are expected to aid in the safe clinical implementation of dose reduction technologies.

Development and Testing of An Automatic Lung IMRT Planning Algorithm

Knowledge-based radiation treatment is an emerging concept in radiotherapy. It

mainly refers to the technique that can guide or automate treatment planning in

clinic by learning from prior knowledge. Dierent models are developed to realize

it, one of which is proposed by Yuan et al. at Duke for lung IMRT planning. This

model can automatically determine both beam conguration and optimization ob-

jectives with non-coplanar beams based on patient-specic anatomical information.

Although plans automatically generated by this model demonstrate equivalent or

better dosimetric quality compared to clinical approved plans, its validity and gener-

ality are limited due to the empirical assignment to a coecient called angle spread

constraint dened in the beam eciency index used for beam ranking. To eliminate

these limitations, a systematic study on this coecient is needed to acquire evidences

for its optimal value.

To achieve this purpose, eleven lung cancer patients with complex tumor shape

with non-coplanar beams adopted in clinical approved plans were retrospectively

studied in the frame of the automatic lung IMRT treatment algorithm. The primary

and boost plans used in three patients were treated as dierent cases due to the

dierent target size and shape. A total of 14 lung cases, thus, were re-planned using

the knowledge-based automatic lung IMRT planning algorithm by varying angle

spread constraint from 0 to 1 with increment of 0.2. A modied beam angle eciency

index used for navigate the beam selection was adopted. Great eorts were made to assure the quality of plans associated to every angle spread constraint as good

as possible. Important dosimetric parameters for PTV and OARs, quantitatively

re

ecting the plan quality, were extracted from the DVHs and analyzed as a function

of angle spread constraint for each case. Comparisons of these parameters between

clinical plans and model-based plans were evaluated by two-sampled Students t-tests,

and regression analysis on a composite index built on the percentage errors between

dosimetric parameters in the model-based plans and those in the clinical plans as a

function of angle spread constraint was performed.

Results show that model-based plans generally have equivalent or better quality

than clinical approved plans, qualitatively and quantitatively. All dosimetric param-

eters except those for lungs in the automatically generated plans are statistically

better or comparable to those in the clinical plans. On average, more than 15% re-

duction on conformity index and homogeneity index for PTV and V40, V60 for heart

while an 8% and 3% increase on V5, V20 for lungs, respectively, are observed. The

intra-plan comparison among model-based plans demonstrates that plan quality does

not change much with angle spread constraint larger than 0.4. Further examination

on the variation curve of the composite index as a function of angle spread constraint

shows that 0.6 is the optimal value that can result in statistically the best achievable

plans.

Pyrrolidine Dithiocarbamate Prevents Neuroinflammation and Cognitive Dysfunction after Endotoxemia in Rats.

Systemic inflammation, for example as a result of infection, often contributes to long-term complications. Neuroinflammation and cognitive decline are key hallmarks of several neurological conditions, including advance age. The contribution of systemic inflammation to the central nervous system (CNS) remains not fully understood. Using a model of peripheral endotoxemia with lipopolysaccharide (LPS) we investigated the role of nuclear factor-κB (NF-κB) activity in mediating long-term neuroinflammation and cognitive dysfunction in aged rats. Herein we describe the anti-inflammatory effects of pyrrolidine dithiocarbamate (PDTC), a selective NF-κB inhibitor, in modulating systemic cytokines including tumor necrosis factor (TNF)-α and interleukin-1β (IL-1β) and CNS markers after LPS exposure in aged rats. In the hippocampus, PDTC not only reduced neuroinflammation by modulating canonical NF-κB activity but also affected IL-1β expression in astrocytes. Parallel effects were observed on behavior and postsynaptic density-95 (PSD95), a marker of synaptic function. Taken together these changes improved acute and long-term cognitive function in aged rats after LPS exposure.

An investigation of the role of TRIB2 in steady state and stressed haematopoiesis

TRIB2 is a member of the mammalian Tribbles family of serine/threonine pseudokinases (TRIB1-3). Here, we studied murine haematopoiesis after Trib2 ablation under steady state and proliferative stress conditions, including genotoxic and oncogenic stress. At the steady state, we found that TRIB2 loss did not adversely affect peripheral blood cell counts and populations. No detectable significant differences were found in the populations of haematopoietic stem and progenitor cells. However, Trib2-/- mice had significantly higher thymic cellularity due to the increased proliferation of Trib2-/- developing thymocytes which give rise to increased number of mature thymic subsets. During stressed haematopoiesis, Trib2-/- developing thymocytes demonstrate hypersensitivity to 5-fluorouracil-induced cell death. Nevertheless, Trib2-/- mice exhibit accelerated thymopoietic recovery post 5-fluorouracil treatment due to increased cell division kinetics of developing thymocytes. In an experimental murine T-cell acute lymphoblastic leukaemia (T-ALL) model, Trib2-/- mice had reduced latency in vivo which associated with aggressive T-ALL phenotypes and impaired activation of mitogen-activated protein kinase. Gene set enrichment analysis showed that TRIB2 expression is elevated in immature subtype of human T-ALL enriched with mitogen-activated protein kinase signalling. However, TRIB2 expression is suppressed in mature subtype of human T-ALL. Thus, TRIB2 emerges as a novel regulator of thymocyte cellular proliferation, important for the thymopoietic response to genotoxic and oncogenic stress, and possessing tumour suppressor function. In Drosophila, Tribbles promotes degradation of String which is an orthologue of mammalian CDC25 phosphatases in order to arrest cell cycle during embryonic development. Here, we showed that the role of Tribbles-induced degradation of String is evolutionarily conserved in TRIB2. We found that TRIB2 interacts with CDC25B/C but not CDC25A isoform. Overexpression of TRIB2 promotes polyubiquitination and degradation of CDC25C. Hence, future works are warranted to examine TRIB2-CDC25C interaction in the context of developing thymocytes and in T-cell acute lymphoblastic leukaemia, the malignant counterpart.

Abundance of tintinnids in waters of the Argentine Shelf and the Drake Passage 2002-2003

The relationship between the abundance and diversity of tintinnids and the concentration of chlorophyll a (Chl a) was contrasted between neritic and oceanic waters of the SW Atlantic during autumn and summer. Chl a and tintinnid abundance and biomass reached maximum values (17.53 µg/L, 2.76 x 10**3 ind./L and 6.29 µg C/L, respectively) in shelf waters during summer, and their mean values generally differed by one order of magnitude between environments. Peaks in species richness (13) and Shannon diversity index (2.12) were found in the shelf-ocean boundary, but both variables showed nonsignificant differences between areas. Species richness correlated significantly with both Chl a and abundance. Such relationships, which followed a negative linear or quadratic function in the shelf and a positive linear function in oceanic waters, are thought to reflect either the competitive dominance of one species or a relatively wide spectrum of tintinnid size-classes, respectively.

Crack propagation in non-homogenous materials: Evaluation of mixed-mode SIFs, T-stress and kinking angle using a variant EFG method

A new variant of the Element-Free Galerkin (EFG) method, that combines the diffraction method, to characterize the crack tip solution, and the Heaviside enrichment function for representing discontinuity due to a crack, has been used to model crack propagation through non-homogenous materials. In the case of interface crack propagation, the kink angle is predicted by applying the maximum tangential principal stress (MTPS) criterion in conjunction with consideration of the energy release rate (ERR). The MTPS criterion is applied to the crack tip stress field described by both the stress intensity factor (SIF) and the T-stress, which are extracted using the interaction integral method. The proposed EFG method has been developed and applied for 2D case studies involving a crack in an orthotropic material, crack along an interface and a crack terminating at a bi-material interface, under mechanical or thermal loading; this is done to demonstrate the advantages and efficiency of the proposed methodology. The computed SIFs, T-stress and the predicted interface crack kink angles are compared with existing results in the literature and are found to be in good agreement. An example of crack growth through a particle-reinforced composite materials, which may involve crack meandering around the particle, is reported.

Modeling of Turbulent Natural Gas and Biogas Flames of the Delft Jet-in-Hot-Coflow Burner: Effects of Coflow Temperature, Fuel Temperature and Fuel Composition on the Flame Lift-Off Height

The structure of a turbulent non-premixed flame of a biogas fuel in a hot and diluted coflow mimicking moderate and intense low dilution (MILD) combustion is studied numerically. Biogas fuel is obtained by dilution of Dutch natural gas (DNG) with CO2. The results of biogas combustion are compared with those of DNG combustion in the Delft Jet-in-Hot-Coflow (DJHC) burner. New experimental measurements of lift-off height and of velocity and temperature statistics have been made to provide a database for evaluating the capability of numerical methods in predicting the flame structure. Compared to the lift-off height of the DNG flame, addition of 30 % carbon dioxide to the fuel increases the lift-off height by less than 15 %. Numerical simulations are conducted by solving the RANS equations using Reynolds stress model (RSM) as turbulence model in combination with EDC (Eddy Dissipation Concept) and transported probability density function (PDF) as turbulence-chemistry interaction models. The DRM19 reduced mechanism is used as chemical kinetics with the EDC model. A tabulated chemistry model based on the Flamelet Generated Manifold (FGM) is adopted in the PDF method. The table describes a non-adiabatic three stream mixing problem between fuel, coflow and ambient air based on igniting counterflow diffusion flamelets. The results show that the EDC/DRM19 and PDF/FGM models predict the experimentally observed decreasing trend of lift-off height with increase of the coflow temperature. Although more detailed chemistry is used with EDC, the temperature fluctuations at the coflow inlet (approximately 100K) cannot be included resulting in a significant overprediction of the flame temperature. Only the PDF modeling results with temperature fluctuations predict the correct mean temperature profiles of the biogas case and compare well with the experimental temperature distributions.

A phase I pharmacokinetic and pharmacodynamic study of the oral mitogen-activated protein kinase kinase (MEK) inhibitor, WX-554, in patients with advanced solid tumours

Purpose: We performed a multi-centre phase I study to assess the safety, pharmacokinetics (PK) and pharmacodynamics (PD) of the orally available small molecule mitogen-activated protein kinase kinase (MEK) 1/2 inhibitor, WX-554, and to determine the optimal biological dose for subsequent trials.
Experimental design: Patients with treatment-refractory, advanced solid tumours, with adequate performance status and organ function were recruited to a dose-escalation study in a standard 3 + 3 design. The starting dose was 25 mg orally once weekly with toxicity, PK and PD guided dose-escalation with potential to explore alternative schedules.
Results: Forty-one patients with advanced solid tumours refractory to standard therapies and with adequate organ function were recruited in eight cohorts up to doses of 150 mg once weekly and 75 mg twice weekly. No dose-limiting toxicities were observed during the study, and a maximum tolerated dose (MTD) was not established. The highest dose cohorts demonstrated sustained inhibition of extracellular signal-regulated kinase (ERK) phosphorylation in peripheral blood mononuclear cells following ex-vivo phorbol 12-myristate 13-acetate stimulation. There was a decrease of 70 ± 26% in mean phosphorylated (p)ERK in C1 day 8 tumour biopsies when compared with pre-treatment tumour levels in the 75 mg twice a week cohort. Prolonged stable disease (>6 months) was seen in two patients, one with cervical cancer and one with ampullary carcinoma.
Conclusions: WX-554 was well tolerated, and an optimal biological dose was established for further investigation in either a once or twice weekly regimens. The recommended phase 2 dose is 75 mg twice weekly.

Assessing microvascular function with breathing maneuvers : an oxygenation-sensitive CMR study

Ce projet illustre cinq études, mettant l'emphase sur le développement d'une nouvelle approche diagnostique cardiovasculaire afin d'évaluer le niveau d’oxygène contenu dans le myocarde ainsi que sa fonction microvasculaire. En combinant une séquence de résonance magnétique cardiovasculaire (RMC) pouvant détecter le niveau d’oxygène (OS), des manœuvres respiratoires ainsi que des analyses de gaz artériels peuvent être utilisés comme procédure non invasive destinée à induire une réponse vasoactive afin d’évaluer la réserve d'oxygénation, une mesure clé de la fonction vasculaire. Le nombre de tests diagnostiques cardiaques prescrits ainsi que les interventions, sont en pleine expansion. L'imagerie et tests non invasifs sont souvent effectués avant l’utilisation de procédures invasives. L'imagerie cardiaque permet d’évaluer la présence ou absence de sténoses coronaires, un important facteur économique dans notre système de soins de santé. Les techniques d'imagerie non invasives fournissent de l’information précise afin d’identifier la présence et l’emplacement du déficit de perfusion chez les patients présentant des symptômes d'ischémie myocardique. Néanmoins, plusieurs techniques actuelles requièrent la nécessité de radiation, d’agents de contraste ou traceurs, sans oublier des protocoles de stress pharmacologiques ou physiques. L’imagerie RMC peut identifier une sténose coronaire significative sans radiation. De nouvelles tendances d’utilisation de RMC visent à développer des techniques diagnostiques qui ne requièrent aucun facteur de stress pharmacologiques ou d’agents de contraste. L'objectif principal de ce projet était de développer et tester une nouvelle technique diagnostique afin d’évaluer la fonction vasculaire coronarienne en utilisant l' OS-RMC, en combinaison avec des manœuvres respiratoires comme stimulus vasoactif. Ensuite, les objectifs, secondaires étaient d’utilisés l’OS-RMC pour évaluer l'oxygénation du myocarde et la réponse coronaire en présence de gaz artériels altérés. Suite aux manœuvres respiratoires la réponse vasculaire a été validée chez un modèle animal pour ensuite être utilisé chez deux volontaires sains et finalement dans une population de patients atteints de maladies cardiovasculaires. Chez le modèle animal, les manœuvres respiratoires ont pu induire un changement significatif, mesuré intrusivement par débit sanguin coronaire. Il a été démontré qu’en présence d'une sténose coronarienne hémodynamiquement significative, l’OS-RMC pouvait détecter un déficit en oxygène du myocarde. Chez l’homme sain, l'application de cette technique en comparaison avec l'adénosine (l’agent standard) pour induire une vasodilatation coronarienne et les manœuvres respiratoires ont pu induire une réponse plus significative en oxygénation dans un myocarde sain. Finalement, nous avons utilisé les manœuvres respiratoires parmi un groupe de patients atteint de maladies coronariennes. Leurs myocardes étant altérées par une sténose coronaire, en conséquence modifiant ainsi leur réponse en oxygénation. Par la suite nous avons évalué les effets des gaz artériels sanguins sur l'oxygénation du myocarde. Ils démontrent que la réponse coronarienne est atténuée au cours de l’hyperoxie, suite à un stimuli d’apnée. Ce phénomène provoque une réduction globale du débit sanguin coronaire et un déficit d'oxygénation dans le modèle animal ayant une sténose lorsqu’un supplément en oxygène est donné. En conclusion, ce travail a permis d'améliorer notre compréhension des nouvelles techniques diagnostiques en imagerie cardiovasculaire. Par ailleurs, nous avons démontré que la combinaison de manœuvres respiratoires et l’imagerie OS-RMC peut fournir une méthode non-invasive et rentable pour évaluer la fonction vasculaire coronarienne régionale et globale.

Understanding stakeholder preferences for flood adaptation alternatives with natural capital implications

Inland flood risks are defined by a range of environmental and social factors, including land use and floodplain management. Shifting patterns of storm intensity and precipitation, attributed to climate change, are exacerbating flood risk in regions across North America. Strategies for adapting to growing flood risks and climate change must account for a community’s specific vulnerabilities, and its local economic, environmental, and social conditions. Through a stakeholder-engaged methodology, we designed an interactive decision exercise to enable stakeholders to evaluate alternatives for addressing specific community flood vulnerabilities. We used a multicriteria framework to understand what drives stakeholder preferences for flood mitigation and adaptation alternatives, including ecosystem-based projects. Results indicated strong preferences for some ecosystem-based projects that utilize natural capital, generated a useful discussion on the role of individual values in driving decisions and a critique of local environmental and hazard planning procedure, and uncovered support for a river management alternative that had previously been considered socially infeasible. We conclude that a multicriteria decision framework may help ensure that the multiple benefit qualities of natural capital projects are considered by decision makers. Application of a utility function can demonstrate the role of individual decision-maker values in decision outcomes and help illustrate why one alternative may be a better choice than another. Although designing an efficient and accurate multicriteria exercise is quite challenging and often data intensive, we imagine that this method is applicable elsewhere. It may be especially suitable to group decisions that involve varying levels of expertise and competing values, as is often the case in planning for the ecological and human impacts of climate change.