Cardiovascular diseases and vulnerable plaques: data, modeling, predictions and clinical applications PREFACE

Introduction Two symposia on “cardiovascular diseases and vulnerable plaques” Cardiovascular disease (CVD) is the leading cause of death worldwide. Huge effort has been made in many disciplines including medical imaging, computational modeling, bio- mechanics, bioengineering, medical devices, animal and clinical studies, population studies as well as genomic, molecular, cellular and organ-level studies seeking improved methods for early detection, diagnosis, prevention and treatment of these diseases [1-14]. However, the mechanisms governing the initiation, progression and the occurrence of final acute clinical CVD events are still poorly understood. A large number of victims of these dis- eases who are apparently healthy die suddenly without prior symptoms. Available screening and diagnostic methods are insufficient to identify the victims before the event occurs [8,9]. Most cardiovascular diseases are associated with vulnerable plaques. A grand challenge here is to develop new imaging techniques, predictive methods and patient screening tools to identify vulnerable plaques and patients who are more vulnerable to plaque rupture and associated clinical events such as stroke and heart attack, and recommend proper treatment plans to prevent those clinical events from happening. Articles in this special issue came from two symposia held recently focusing on “Cardio-vascular Diseases and Vulnerable Plaques: Data, Modeling, Predictions and Clinical Applications.” One was held at Worcester Polytechnic Institute (WPI), Worcester, MA, USA, July 13-14, 2014, right after the 7th World Congress of Biomechanics. This symposium was endorsed by the World Council of Biomechanics, and partially supported by a grant from NIH-National Institute of Biomedical Image and Bioengineering. The other was held at Southeast University (SEU), Nanjing, China, April 18-20, 2014.

Sediment concentration prediction and statistical evaluation for annual load estimation

We consider the development of statistical models for prediction of constituent concentration of riverine pollutants, which is a key step in load estimation from frequent flow rate data and less frequently collected concentration data. We consider how to capture the impacts of past flow patterns via the average discounted flow (ADF) which discounts the past flux based on the time lapsed - more recent fluxes are given more weight. However, the effectiveness of ADF depends critically on the choice of the discount factor which reflects the unknown environmental cumulating process of the concentration compounds. We propose to choose the discount factor by maximizing the adjusted R-2 values or the Nash-Sutcliffe model efficiency coefficient. The R2 values are also adjusted to take account of the number of parameters in the model fit. The resulting optimal discount factor can be interpreted as a measure of constituent exhaustion rate during flood events. To evaluate the performance of the proposed regression estimators, we examine two different sampling scenarios by resampling fortnightly and opportunistically from two real daily datasets, which come from two United States Geological Survey (USGS) gaging stations located in Des Plaines River and Illinois River basin. The generalized rating-curve approach produces biased estimates of the total sediment loads by -30% to 83%, whereas the new approaches produce relatively much lower biases, ranging from -24% to 35%. This substantial improvement in the estimates of the total load is due to the fact that predictability of concentration is greatly improved by the additional predictors.

Load estimation with uncertainties from opportunistic sampling data: A semiparametric approach

We consider estimating the total load from frequent flow data but less frequent concentration data. There are numerous load estimation methods available, some of which are captured in various online tools. However, most estimators are subject to large biases statistically, and their associated uncertainties are often not reported. This makes interpretation difficult and the estimation of trends or determination of optimal sampling regimes impossible to assess. In this paper, we first propose two indices for measuring the extent of sampling bias, and then provide steps for obtaining reliable load estimates that minimizes the biases and makes use of informative predictive variables. The key step to this approach is in the development of an appropriate predictive model for concentration. This is achieved using a generalized rating-curve approach with additional predictors that capture unique features in the flow data, such as the concept of the first flush, the location of the event on the hydrograph (e.g. rise or fall) and the discounted flow. The latter may be thought of as a measure of constituent exhaustion occurring during flood events. Forming this additional information can significantly improve the predictability of concentration, and ultimately the precision with which the pollutant load is estimated. We also provide a measure of the standard error of the load estimate which incorporates model, spatial and/or temporal errors. This method also has the capacity to incorporate measurement error incurred through the sampling of flow. We illustrate this approach for two rivers delivering to the Great Barrier Reef, Queensland, Australia. One is a data set from the Burdekin River, and consists of the total suspended sediment (TSS) and nitrogen oxide (NO(x)) and gauged flow for 1997. The other dataset is from the Tully River, for the period of July 2000 to June 2008. For NO(x) Burdekin, the new estimates are very similar to the ratio estimates even when there is no relationship between the concentration and the flow. However, for the Tully dataset, by incorporating the additional predictive variables namely the discounted flow and flow phases (rising or recessing), we substantially improved the model fit, and thus the certainty with which the load is estimated.

Modeling strategies in longitudinal data analysis: Covariate, variance function and correlation structure selection

A modeling paradigm is proposed for covariate, variance and working correlation structure selection for longitudinal data analysis. Appropriate selection of covariates is pertinent to correct variance modeling and selecting the appropriate covariates and variance function is vital to correlation structure selection. This leads to a stepwise model selection procedure that deploys a combination of different model selection criteria. Although these criteria find a common theoretical root based on approximating the Kullback-Leibler distance, they are designed to address different aspects of model selection and have different merits and limitations. For example, the extended quasi-likelihood information criterion (EQIC) with a covariance penalty performs well for covariate selection even when the working variance function is misspecified, but EQIC contains little information on correlation structures. The proposed model selection strategies are outlined and a Monte Carlo assessment of their finite sample properties is reported. Two longitudinal studies are used for illustration.

Cyclic plastic deformation characteristics of subgrade under moving train wheel load

Cyclic plastic deformation of subgrade and other engineered layers is generally not taken into account in the design of railway bridge transition zones, although the plastic deformation is the governing factor of frequent track deterioration. Actual stress behavior of fine grained subgrade/embankment layers under train traffic is, however, difficult to replicate using the conventional laboratory test apparatus and techniques. A new type of torsional simple shear apparatus, known as multi-ring shear apparatus, was therefore developed to evaluate the actual stress state and the corresponding cyclic plastic deformation characteristics of subgrade materials under moving wheel load conditions. Multi-ring shear test results has been validated using a theoretical model test results; the capability of the multi-ring shear apparatus for replicating the cyclic plastic deformation characteristics of subgrade under moving train wheel load conditions is thus established. This paper describes the effects of principal stress rotation (PSR) of the subgrade materials to the cyclic plastic deformation in a railroad and impacts of testing methods in evaluating the influence of principal stress rotation to the track deterioration of rail track.

Can the direct measurement of the load applied on the residuum of individuals with transfemoral amputation fitted with bone-anchored prosthesis help to improve the rehabilitation program?

To strive to improve the rehabilitation program of individuals with transfemoral amputation fitted with bone-anchored prosthesis based on data from direct measurements of the load applied on the residuum we first of all need to understand the load applied on the fixation. Therefore the load applied on the residuum was first directly measured during standardized activities of daily living such as straight line level walking, ascending and descending stairs and a ramp and walking around a circle. From measuring the load in standardized activities of daily living the load was also measured during different phases of the rehabilitation program such as during walking with walking aids and during load bearing exercises.[1-15] The rehabilitation program for individuals with a transfemoral amputation fitted with an OPRA implant relies on a combination of dynamic and static load bearing exercises.[16-20] This presentation will focus on the study of a set of experimental static load bearing exercises. [1] A group of eleven individuals with unilateral transfemoral amputation fitted with an OPRA implant participated in this study. The load on the implant during the static load bearing exercises was measured using a portable system including a commercial transducer embedded in a short pylon, a laptop and a customized software package. This apparatus was previously shown effective in a proof-of-concept study published by Prof. Frossard. [1-9] The analysis of the static load bearing exercises included an analysis of the reliability as well as the loading compliance. The analysis of the loading reliability showed a high reliability between the loading sessions indicating a correct repetition of the LBE by the participants. [1, 5] The analysis of the loading compliance showed a significant lack of axial compliance leading to a systematic underloading of the long axis of the implant during the proposed experimental static LBE.

Probabilistic load flow for distribution systems with uncertain PV generation

Large integration of solar Photo Voltaic (PV) in distribution network has resulted in over-voltage problems. Several control techniques are developed to address over-voltage problem using Deterministic Load Flow (DLF). However, intermittent characteristics of PV generation require Probabilistic Load Flow (PLF) to introduce variability in analysis that is ignored in DLF. The traditional PLF techniques are not suitable for distribution systems and suffer from several drawbacks such as computational burden (Monte Carlo, Conventional convolution), sensitive accuracy with the complexity of system (point estimation method), requirement of necessary linearization (multi-linear simulation) and convergence problem (Gram–Charlier expansion, Cornish Fisher expansion). In this research, Latin Hypercube Sampling with Cholesky Decomposition (LHS-CD) is used to quantify the over-voltage issues with and without the voltage control algorithm in the distribution network with active generation. LHS technique is verified with a test network and real system from an Australian distribution network service provider. Accuracy and computational burden of simulated results are also compared with Monte Carlo simulations.

Measuring route passenger load diversity for capacity and quality of service assessment

This poster introduces Passenger Relative Load Factor for a route or individual bus service as a capacity and quality of service measure, distinguishing it from Occupancy Load Factor. It introduces Load Diversity Coefficient as the ratio of Passenger Relative Load Factor to Occupancy Load Factor, and relates Load Diversity Coefficient to Coefficient of Variation in Occupancy Load Factor. It qualifies the operator’s and passengers’ perspectives of load factor based on Coefficient of Variation in Occupancy Load Factor along a route. A case study using weekday Automatic Fare Collection (AFC) data on a premium bus line in Brisbane, Australia illustrates the methodology. The compendium paper also qualifies the operator’s and passengers’ perspectives of these load factors along with Passengers’ Average Travel Time for capacity and quality of service assessment.

MPC controlled multirotor with suspended slung load: System architecture and visual load detection

There is an increased interest in the use of Unmanned Aerial Vehicles for load transportation from environmental remote sensing to construction and parcel delivery. One of the main challenges is accurate control of the load position and trajectory. This paper presents an assessment of real flight trials for the control of an autonomous multi-rotor with a suspended slung load using only visual feedback to determine the load position. This method uses an onboard camera to take advantage of a common visual marker detection algorithm to robustly detect the load location. The load position is calculated using an onboard processor, and transmitted over a wireless network to a ground station integrating MATLAB/SIMULINK and Robotic Operating System (ROS) and a Model Predictive Controller (MPC) to control both the load and the UAV. To evaluate the system performance, the position of the load determined by the visual detection system in real flight is compared with data received by a motion tracking system. The multi-rotor position tracking performance is also analyzed by conducting flight trials using perfect load position data and data obtained only from the visual system. Results show very accurate estimation of the load position (~5% Offset) using only the visual system and demonstrate that the need for an external motion tracking system is not needed for this task.

Modeling multi-stakeholder multi-objective decisions during public participation in major infrastructure and construction projects: A decision rule approach

Major infrastructure and construction (MIC) projects are those with significant traffic or environmental impact, of strategic and regional significance and high sensitivity. The decision making process of schemes of this type is becoming ever more complicated, especially with the increasing number of stakeholders involved and their growing tendency to defend their own varied interests. Failing to address and meet the concerns and expectations of stakeholders may result in project failures. To avoid this necessitates a systematic participatory approach to facilitate decision-making. Though numerous decision models have been established in previous studies (e.g. ELECTRE methods, the analytic hierarchy process and analytic network process) their applicability in the decision process during stakeholder participation in contemporary MIC projects is still uncertain. To resolve this, the decision rule approach is employed for modeling multi-stakeholder multi-objective project decisions. Through this, the result is obtained naturally according to the “rules” accepted by any stakeholder involved. In this sense, consensus is more likely to be achieved since the process is more convincing and the result is easier to be accepted by all concerned. Appropriate “rules”, comprehensive enough to address multiple objectives while straightforward enough to be understood by multiple stakeholders, are set for resolving conflict and facilitating consensus during the project decision process. The West Kowloon Cultural District (WKCD) project is used as a demonstration case and a focus group meeting is conducted in order to confirm the validity of the model established. The results indicate that the model is objective, reliable and practical enough to cope with real world problems. Finally, a suggested future research agenda is provided.

Numerical study on the surface depression of the concrete runway pavement under impact load

Airport runway pavement always subjected to huge impact loading due to the hard landing of aircraft on the pavement surface. Therefore runway pavements should have sufficient impact resistance capability to avoid damage causing by hard impact like surface deflection in downward or penetration since the repair works is cumbersome within the operating condition of airport and also increases the service life cost of the pavement structure. Several research works have been carried out on airport runway pavement to measure the present condition of pavement and also to predict future performance of it. However, most of the works are confined by pavement response under moving aircraft loading. Nevertheless, no comprehensive research work is yet conducted to identify the controlling factors which might have significant effect in changing the common pavements damage like surface penetration depth under impact of aircraft. Therefore, a 3D FE study is conducted to determine some effective factors in controlling the top surface penetration depth of runway pavement. Among the exterior factors, mass of the impactor, velocity of the impactor, impact angle and boundary conditions are selected and as interior factors, thickness of the runway pavement, compressive strength and density of materials used in the runway pavement are selected.

Oxazolidine-2-thiones: A molecular modeling study

Two oxazolidine-2-thiones, thio-analogs of linezolid, were synthesized and their antibacterial properties evaluated. Unlike oxazolidinones, the thio-analogs did not inhibit the growth of Gram positive bacteria. A molecular modeling study has been carried out to aid understanding of this unexpected finding.

Platelet endothelial cell adhesion molecule 1 (PECAM-1) and its interactions with glycosaminoglycans: 1. Molecular modeling studies

Platelet endothelial cell adhesion molecule 1 (PECAM-1) has many functions, including its roles in leukocyte extravasation as part of the inflammatory response and in the maintenance of vascular integrity through its contribution to endothelial cell−cell adhesion. PECAM-1 has been shown to mediate cell−cell adhesion through homophilic binding events that involve interactions between domain 1 of PECAM-1 molecules on adjacent cells. However, various heterophilic ligands of PECAM-1 have also been proposed. The possible interaction of PECAM-1 with glycosaminoglycans (GAGs) is the focus of this study. The three-dimensional structure of the extracellular immunoglobulin (Ig) domains of PECAM-1 were constructed using homology modeling and threading methods. Potential heparin/heparan sulfate-binding sites were predicted on the basis of their amino acid consensus sequences and a comparison with known structures of sulfate-binding proteins. Heparin and other GAG fragments have been docked to investigate the structural determinants of their protein-binding specificity and selectivity. The modeling has predicted two regions in PECAM-1 that appear to bind heparin oligosaccharides. A high-affinity binding site was located in Ig domains 2 and 3, and evidence for a low-affinity site in Ig domains 5 and 6 was obtained. These GAG-binding regions were distinct from regions involved in PECAM-1 homophilic interactions.

Diaryl dihydropyrazole-3-carboxamides with significant in vivo antiobesity activity related to CB1 receptor antagonism: Synthesis, biological evaluation, and molecular modeling in the homology model

A number of analogues of diaryl dihydropyrazole-3-carboxamides have been synthesized. Their activities were evaluated for appetite suppression and body weight reduction in animal models. Depending on the chemical modification of the selected dihydropyrazole scaffold, the lead compoundsthe bisulfate salt of (±)-5-(4-chlorophenyl)-1-(2,4-dichlorophenyl)-4,5-dihydro-1H-pyrazole-3-carboxylic acid morpholin-4-ylamide 26 and the bisulfate salt of (−)-5-(4-chlorophenyl)-1-(2,4-dichlorophenyl)-4,5-dihydro-1H-pyrazole-3-carboxylic acid morpholin-4-ylamide 30showed significant body weight reduction in vivo, which is attributed to their CB1 antagonistic activity and exhibited a favorable pharmacokinetic profile. The molecular modeling studies also showed interactions of two isomers of (±)-5-(4-chlorophenyl)-1-(2,4-dichlorophenyl)-4,5-dihydro-1H-pyrazole-3-carboxylic acid morpholin-4-ylamide 9 with CB1 receptor in the homology model similar to those of N-piperidino-5-(4-chlorophenyl)-1-(2,4-dichlorophenyl)-4-methyl-3-pyrazole-carboxamide (rimonabant) 1 and 4S-(−)-3-(4-chlorophenyl)-N-methyl-N‘-[(4-chlorophenyl)-sulfonyl]-4-phenyl-4,5-dihydro-1H-pyrazole-1-carboxamidine (SLV-319) 2.

Molecular modeling of Bt Cry1Ac (DI–DII)–ASAL (Allium sativum lectin)–fusion protein and its interaction with aminopeptidase N (APN) receptor of Manduca sexta

Genetic engineering of Bacillus thuringiensis (Bt) Cry proteins has resulted in the synthesis of various novel toxin proteins with enhanced insecticidal activity and specificity towards different insect pests. In this study, a fusion protein consisting of the DI–DII domains of Cry1Ac and garlic lectin (ASAL) has been designed in silico by replacing the DIII domain of Cry1Ac with ASAL. The binding interface between the DI–DII domains of Cry1Ac and lectin has been identified using protein–protein docking studies. Free energy of binding calculations and interaction profiles between the Cry1Ac and lectin domains confirmed the stability of fusion protein. A total of 18 hydrogen bonds was observed in the DI–DII–lectin fusion protein compared to 11 hydrogen bonds in the Cry1Ac (DI–DII–DIII) protein. Molecular mechanics/Poisson–Boltzmann (generalized-Born) surface area [MM/PB (GB) SA] methods were used for predicting free energy of interactions of the fusion proteins. Protein–protein docking studies based on the number of hydrogen bonds, hydrophobic interactions, aromatic–aromatic, aromatic–sulphur, cation–pi interactions and binding energy of Cry1Ac/fusion proteins with the aminopeptidase N (APN) of Manduca sexta rationalised the higher binding affinity of the fusion protein with the APN receptor compared to that of the Cry1Ac–APN complex, as predicted by ZDOCK, Rosetta and ClusPro analysis. The molecular binding interface between the fusion protein and the APN receptor is well packed, analogously to that of the Cry1Ac–APN complex. These findings offer scope for the design and development of customized fusion molecules for improved pest management in crop plants.