Flow-related Variables Research Articles

Airflow analysis of pediatric upper airway following maxillary expansion using computational fluid dynamics

Purpose: The objective of this study is to numerically analyze and visualize changes in airflow characteristics due to maxillary expansion in pediatric patients using computational fluid dynamics (CFD).Materials and Methods: CBCT data from pediatric patients with an apnea-hypopnea index of over 1, habitual mouth breathing, and a constricted maxilla were used. For orthodontic treatment, maxillary expansion was conducted, and CBCT scans were taken before and after expansion. 3D models of the nasal airway, created from CBCT data, were converted into smoothed, mesh-divided models. CFD analysis was conducted and various parameters which can be used to evaluate flow obstruction, including pressure, velocity, and wall shear stress, were analyzed.Results: In the patient with rapid expansion, constriction sites with high pressure, velocity, and wall shear stress distribution were identified in the anterior and posterior regions of the nasal cavity, while in the slow expansion patient, these high pressure, velocity, and wall shear stress distributed constriction sites were found in the anterior and mid-inferior regions of the nasal cavity. In both patients, after expansion, the flow-related variables that were highly distributed prior to expansion decreased, and their maximum values were also reduced.Conclusion: CFD analysis enabled the identification of constriction sites within upper airway before undergoing expansion, and improvement in airflow was confirmed after both rapid and slow maxillary expansion in pediatric patients. CFD analysis on patient-specific upper airway models is expected to aid in precisely identifying the problematic areas of respiratory obstruction, thereby assisting in the selection of personalized treatment methods.

Prediction and analysis of likelihood of freeway crash occurrence considering risky driving behavior

The prediction of the likelihood of vehicle crashes constitutes an indispensable component of freeway safety management. Due to data collection limitations, studies have used mainly traffic flow-related variables to develop freeway crash prediction models but rarely have considered the effect of risky driving behavior on the likelihood of crashes. This study employed navigation software to collect driving behavior data and integrated multi-source data that include vehicle speed, traffic volume, and congestion index values. The study also employed the ‘synthesizing minority oversampling technique and edited nearest neighbor’ (SMOTE + ENN) coupled method for data balance processing. Three freeway crash likelihood prediction models were built based on the binomial logit, eXtreme Gradient Boosting (XGBoost), and support vector machine algorithms, respectively. The Shapley additive explanation (SHAP) algorithm was utilized to explore the effect of each feature variable on the likelihood of crashes. The results show that the prediction accuracy of the XGBoost model is the best of the three compared models. Under the optimal control-to-case ratio (1:1), the prediction accuracy of the XGBoost model reached 0.96 in this study, and the recall rate, specificity, and area-under-the-curve values were 0.86, 0.96, and 0.907, respectively. Comparative test results demonstrate that ranking risky driving behavior into three levels of intensity can effectively enhance the predictive accuracy of the XGBoost model. Moreover, the XGBoost model with its ten-minute time step outperformed the XGBoost model with its five-minute time step in terms of prediction accuracy. The results of the SHAP-based analysis show that the likelihood of highway crashes is high when the traffic congestion level is high and the distribution of the vehicle speed in the upstream roadway section is significant. Also, both sharp acceleration and sharp deceleration lead to greater likelihood of crashes. This paper aims to provide an effective framework for predicting and interpreting the likelihood of freeway crashes, thereby providing guidance for crash prevention, driver training, and the development of traffic regulations.

MHD mixed convection flow for Maxwell Hybrid nanofluid with Soret, Dufour and Morphology effects

We have investigated the two-dimensional mixed convective Maxwell hybrid nanofluid boundary layer mass and heat flows over a linearly stretching porous surface with the applied external magnetic flux. Thermal radiations along with the Dufour and Soret effects are also incorporated. The governing model of partial differential equations (PDE) is altered into ordinary differential equations (ODE) with an appropriate similarity transformation. The finite difference-based numerical method BVP4c is applied to solve the system of nonlinear ODEs. The flow features and the heat transfer characteristics have been illustrated with graphical representations and a numerical table. For varied values of the flow-related variables, organized and graphical data for the Nusselt number and skin friction coefficient are indicated. In most cases, spherical-shaped nanoparticles have a better influence on stream function, velocity and temperature distributions. This behavior is the opposite of the mass concentration profile. It has been observed that stream function decreases as increase the value of the magnetic field but opposite for mass concentration distribution and temperature profile. The temperature gradient is enhanced as a result of stronger convective flow when Soret number Sr values increase, which causes the boundary layer thickness to grow. A comparative study of hybrid nanofluid and nanofluid showed that the hybrid nanofluid has superior shear stress/skin friction and Sherwood number/surface mass flux than nanofluid flow.

Magnetized Tri-hybrid Nanofluids flow with binary Chemical Reaction and activation Energy through the porous Surfaces

Hybrid nanofluids are important to researchers because of their industrial applications due to their high heat transfer rates. Tri hybrid different types of nanoparticles are discussed here with Newtonian fluids under the effect of MHD. The most important chemical reaction associated with mass transfer and activation energy parameters hasbeen discussed in detail. The current research focuses on two-dimensional fluids with heat transfer enhancement flowing over a porous surface. The mathematical modeling of the problem, as well as empirical relations for nanoparticle materials, is expressed as PDEs, which are then translated into ODEs using appropriate variables. The Runge–Kutta and shooting methods are combined to solve the problems of the created coupled differential system. Variations in nanoparticle volume fraction at the lower and upper walls of porous plates, as well as heat transfer rate measurements, are computed using controlling physical factors. The impact of flow-related variables on the axial, radial, and temperature components of velocity and temperature distribution is also assessed.

Insight into Dynamic of Mono and Hybrid Nanofluids Subject to Binary Chemical Reaction, Activation Energy, and Magnetic Field through the Porous Surfaces

The mathematical modeling of the activation energy and binary chemical reaction system with six distinct types of nanoparticles, along with the magnetohydrodynamic effect, is studied in this paper. Different types of hybrid nanofluids flowing over porous surfaces with heat and mass transfer aspects are examined here. The empirical relations for nanoparticle materials associated with thermophysical properties are expressed as partial differential equations, which are then interpreted into ordinary differential expressions using appropriate variables. The initial shooting method converts the boundary condition into the initial condition with an appropriate guess and finally finds out an accurate numerical solution by using the Runge–Kutta method with numerical stability. Variations in nanoparticle volume fraction at the lower and upper walls of porous surfaces, as well as the heat transfer rate measurements, are computed using the controlling physical factors. The effects of the flow-related variables on the axial velocity, radial velocity, temperature, and concentration profile dispersion are also investigated. The Permeable Reynolds number is directly proportional to the regression parameter. The injection/suction phenomenon associated with the expanding/contracting cases, respectively, have been described with engineering parameters. The hybrid nanoparticle volume fraction (1–5%) has a significant effect on the thermal system and radial velocity.

68 Late Gestational Nutrient Restriction Decreases Blood Flow to the Mammary Gland in Lactating Primiparous Beef Females

Abstract To determine the effects of late gestational nutrient restriction on mammary blood flow during lactation, fall-calving Hereford-SimAngus heifers (single-sired; BW: 451 ± 28 [SD] kg; BCS: 5.4 ± 0.7) bred to a single sire were individually-fed 100% (control; CON; n = 10) or 70% (NR; n = 13) of NASEM net energy and metabolizable protein requirements for maintenance, pregnancy, and growth from d 160 of gestation to calving. Post-calving, all females were individually fed chopped tall fescue hay supplemented to meet lactational nutrient requirements in Calan gates. Transrectal color Doppler ultrasonography of both external pudendal arteries was conducted every 21 d from d 23 to 107 of lactation. Total mammary blood flow was calculated and hemodynamics from both sides averaged. Data were analyzed with fixed effects of nutritional plane, day of lactation, and their interaction, using repeated measures. Calving date and calf sex (if P < 0.25) were fixed effects, and Doppler angle of insonation was included in the model for flow-related variables. We have previously reported that CON cows had greater (P ≤ 0.003) BW, BCS, and backfat from calving to d 147 of lactation, and NR cows had 15% less (P < 0.04) milk yield. External pudendal artery pulsatility index tended to be greater (P = 0.06) and resistance index, peak systolic velocity, and cross-sectional area were greater (P ≤ 0.04) in CON cows. Heart rate was greater (P = 0.008), yet mammary blood flow was 19% less (P = 0.004) in NR cows. Mammary blood flow/cow BW and blood flow/milk yield were not affected (P ≥ 0.13) by nutritional plane. All hemodynamic variables were affected by day (P ≤ 0.04) except resistance index (P = 0.11). In summary, late gestational nutrient restriction decreased mammary blood flow similarly to the reduction observed in milk yield.

Real-Time Pedestrian Conflict Prediction Model at the Signal Cycle Level Using Machine Learning Models

Compared with traditional traffic studies, real-time safety analyses can be better incorporated into proactive traffic management strategies to improve traffic safety. However, few studies have investigated the real-time pedestrian safety model. Intersections usually have mixed traffic conditions with more pedestrian-vehicle interactions. This paper uses conflict indicators, PET (Post Encroachment Time) and TTC (Time to Collision) to identify pedestrians’ conflicts from CCTV (closed-circuit television) videos. The high-resolution traffic data from the Automated Traffic Signal Performance Measures (ATSPM) system are used to derive traffic flow-related variables. The pedestrian exposure is also estimated. Pedestrians’ conflicts are predicted using multiple machine learning models and Logistic Regression. The resampling methods, random over-sampling, and random under-sampling are compared. The best model, Extreme Gradient Boosting (XGBT) with random over-sampling method can achieve AUC (area under the ROC curve) value of 0.841 and recall value of 0.739 on the test data set. The proposed model can predict pedestrians’ conflicts one cycle ahead, which can be 2–3 min. The proposed model has the potential to be implemented in the Connected and Automated Vehicles (CAV) environment to adjust signal timing accordingly and enhance traffic safety.

River Flow Monitoring by Sentinel-3 OLCI and MODIS: Comparison and Combination

The monitoring of rivers by satellite is an up-to-date subject in hydrological studies as confirmed by the interest of space agencies to finance specific missions that respond to the quantification of surface water flows. We address the problem by using multi-spectral sensors, in the near-infrared (NIR) band, correlating the reflectance ratio between a dry and a wet pixel extracted from a time series of images, the C/M ratio, with five river flow-related variables: water level, river discharge, flow area, mean flow velocity and surface width. The innovative aspect of this study is the use of the Ocean and Land Colour Instrument (OLCI) on board Sentinel-3 satellites, compared to the Moderate Resolution Imaging Spectroradiometer (MODIS) used in previous studies. Our results show that the C/M ratio from OLCI and MODIS is more correlated with the mean flow velocity than with other variables. To improve the number of observations, OLCI and MODIS products are combined into multi-mission time series. The integration provides good quality data at around daily resolution, appropriate for the analysis of the Po River investigated in this study. Finally, the combination of only MODIS products outperforms the other configurations with a frequency slightly lower (~1.8 days).

Improved model and optimization for the energy performance of chiller system with diverse component staging

Accurate data-driven models are required to optimize the energy performance of chiller systems with individual configurations and control strategies. This study develops stepwise regression models at successive time steps to estimate accurately the coefficient of performance (COP) of a system with diverse component staging. Comprehensive trend logging data were collected at 15-min intervals year-round for a system with five chillers of two capacities. Data at two successive time points were compiled into 19 input variables relating to the components’ operating statuses, load sharing variation, temperature-related and flow-related variables and weather conditions. Stepwise regression with the Akaike information criterion was performed to select the predictor variables and time points giving the highest achievable coefficient of determination R2. The developed system COP models with different numbers of operating chillers and multiple time points has an increased R2 of 0.75–0.94 compared with 0.37–0.89 for a conventional model with the chiller part load ratio (PLR) only. The model coefficients help prioritize variables to be optimized. The L-BFGS-B optimization algorithm with operating constraints was applied to predict the maximum system COP for the system operating for the cooling load profile of an educational building. A reduction of 9.14–16.67% was estimated in the annual electricity consumption when compared with the existing operation. The optimal control involves implementing pair-up operation of chillers, pumps and cooling towers, and resetting the temperature of water leaving the condensers at specific ranges based on the number of operating chillers.

Studying the impact of different body positioning, squatting, and unipodal flexion on perfusion in the lower limb – an exploratory approach complemented with optical spectroscopy (TiVi)

Body posture and movement seem to be responsible for multiple variations of microcirculation in the foot, although difficulties associated with measurement during movement have limited their characterization. This pilot study sought to explore a new non-invasive instrument based on polarized light spectroscopy – the TiVi system, under orthostatic and dynamic conditions. Five healthy participants (duly informed, 26.0 ± 6.5 years of age) of both genders were selected. The protocol involved sequential posture changes (orthostatic variation) and dynamic movements (squatting and unipodal flexion). Perfusion variations were evaluated in both feet by laser-Doppler flowmetry (LDF) and polarized spectroscopy (TiVi). Both systems revealed the same type of modification of these flow-related variables. The most pronounced changes were obtained with exercise, especially with squatting, which caused a marked increase in foot perfusion. Less dramatic but in the same direction, the increased perfusion with unipodal flexion was also observed in the contralateral limb. This study confirmed the interest in using the TiVi system in these domains, as well as the appropriateness of this experimental design to look deeper into the impact of lower limb movement on the functional dynamics of the foot.

Perioperative hemodynamic monitoring: Still a place for cardiac filling pressures?

The clinical usefulness of the so-called "static" cardiac filling pressures - central (CVP) and pulmonary-artery-occlusion-pressure (PAOP) - has come into question for guiding hemodynamic therapy due to their poor ability to predict fluid responsiveness in comparison with other monitoring modalities such as transpulmonary thermodilution-derived volumetric measurements, dynamic variables for assessing fluid responsiveness, and the potential risks associated with pulmonary artery catheterization. This contrasts with observations in multiple patient populations showing a clear association between increased CVP and PAOP levels and poor outcomes, probably due to a reduction in effective perfusion pressure (mean arterial pressure minus CVP) and their role as effectiveness parameters of the cardiovascular system. Furthermore, clinical studies have revealed beneficial effects when interpreting CVP and PAOP dynamically and combining them with flow-related hemodynamic variables. Taking into account the additional information derived from bedside CVP and PAOP pulse curve interpretation, cardiac filling pressures remain an important hemodynamic monitoring tool.

Perioperative goal-directed therapy - What is the evidence?

Perioperative goal-directed therapy aims at optimizing global hemodynamics during the perioperative period by titrating fluids, vasopressors, and/or inotropes to predefined hemodynamic goals. There is evidence on the benefit of perioperative goal-directed therapy, but its adoption into clinical practice is slow and incomprehensive. Current evidence indicates that treating patients according to perioperative goal-directed therapy protocols reduces morbidity and mortality, particularly in patients having high-risk surgery. Perioperative goal-directed therapy protocols need to be started early, should include vasoactive agents in addition to fluids, and should target blood flow related variables. Future promising developments in the field of perioperative goal-directed therapy include personalized hemodynamic management and closed-loop system management.

Differences in Particle Deposition Between Members of Imaging-Based Asthma Clusters.

Background: Four computed tomography (CT) imaging-based clusters have been identified in a study of the Severe Asthma Research Program (SARP) cohort and have been significantly correlated with clinical and demographic metrics (J Allergy Clin Immunol 2017; 140:690-700.e8). We used a computational fluid dynamics (CFD) model to investigate air flow and aerosol deposition within imaging archetypes representative of the four clusters. Methods: CFD simulations for air flow and 1-8 μm particle transport were performed using CT-based airway models from two healthy subjects and eight asthma subjects. The subject selection criterion was based on the discriminant imaging-based flow-related variables of J(Total) (average local volume expansion in the total lung) and Dh*(sLLL) (normalized airway hydraulic diameter in the left lower lobe), where reduced J(Total) and Dh*(sLLL) indicate reduced regional ventilation and airway constriction, respectively. The analysis focused on the comparisons between all clusters with respect to healthy subjects, between cluster 2 and cluster 4 (nonsevere and severe asthma clusters with airway constriction) and between cluster 3 and cluster 4 (two severe asthma clusters characterized by normal and constricted airways, respectively). Results: Nonsevere asthma cluster 2 and severe asthma cluster 4 subjects characterized by airway constriction had an increase in the deposition fraction (DF) in the left lower lobe. Constricted flows impinged on distal bifurcations resulting in large depositions. Although both cluster 3 (without constriction) and cluster 4 (with constriction) were severe asthma, they exhibited different particle deposition patterns with increasing particle size. The statistical analysis showed that Dh*(sLLL) plays a more important role in particle deposition than J(Total), and regional flow fraction is correlated with DF among lobes for smaller particles. Conclusions: We demonstrated particle deposition characteristics associated with cluster-specific imaging-based metrics such as airway constriction, which could pertain to the design of future drug delivery improvements.

Understanding the Effect of Statins and Patient Adherence in Atherosclerosis via a Quantitative Systems Pharmacology Model Using a Novel, Hybrid, and Multi-Scale Approach.

Background and Objective: Statins are one of the most prescribed drugs to treat atherosclerosis. They inhibit the hepatic HMG-CoA reductase, causing a reduction of circulating cholesterol and LDL levels. Statins have had undeniable success; however, the benefits of statin therapy crystallize only if patients adhere to the prescribed treatment, which is far away from reality since adherence decreases with time with around half of patients discontinue statin therapy within the first year. The objective of this work is to; firstly, demonstrate a formal in-silico methodology based on a hybrid, multiscale mathematical model used to study the effect of statin treatment on atherosclerosis under different patient scenarios, including cases where the influence of medication adherence is examined and secondly, to propose a flexible simulation framework that allows extensions or simplifications, allowing the possibility to design other complex simulation strategies, both interesting features for software development.Methods: Different mathematical modeling paradigms are used to present the relevant dynamic behavior observed in biological/physiological data and clinical trials. A combination of continuous and discrete event models are coupled to simulate the pharmacokinetics (PK) of statins, their pharmacodynamic (PD) effect on lipoproteins levels (e.g., LDL) and relevant inflammatory pathways whilst simultaneously studying the dynamic effect of flow-related variables on atherosclerosis progression.Results: Different scenarios were tested showing the impact of: (1) patient variability: a virtual population shows differences in plaque growth for different individuals could be as high as 100%; (2) statin effect on atherosclerosis: it is shown how a patient with a 1-year statin treatment will reduce his plaque growth by 2–3% in a 2-year period; (3) medical adherence: we show that a patient missing 10% of the total number of doses could increase the plaque growth by ~1% (after 2 years) compared to the same “regular” patient under a 1-year treatment with statins.Conclusions: The results in this paper describe the effect of pharmacological intervention combined with biological/physiological or behavioral factors in atherosclerosis progression and treatment in specific patients. It also provides an exemplar of basic research that can be practically developed into an application software.

Spatial scale effect on sediment dynamics in basin-wide floods within a typical agro-watershed: A case study in the hilly loess region of the Chinese Loess Plateau

Scale issues, which have been extensively studied in the domain of soil erosion, are considerably significant in geomorphologic processes and hydrologic modelling. However, relatively scarce efforts have been made to quantify the spatial scale effect on event-based sediment dynamics in basin-wide floods. To address this issue, sediment-runoff yield data of 44 basin-wide flood events were collected from gauging stations at the Chabagou river basin, a typical agro-basin (unmanaged) in the hilly loess region of the Chinese Loess Plateau. Thus, the spatial scale effect on event-based sediment dynamics was investigated in the basin system across three different spatial scales from sublateral to basin outlet. Results showed that the event-based suspended sediment concentration, as well as the intra- and inter-scale flow–sediment relationships remained spatially constant. Hence, almost all the sediment-laden flows can reach at the detachment-limited maximum concentration across scales, specifically for hyperconcentrated flows. Consequently, limited influence was exerted by upstream sediment-laden flow on downstream sediment output, particularly for major sediment-producing events. However, flood peak discharge instead of total flood runoff amount can better interpret the dynamics of sediment yield across scales. As a composite parameter, the proposed stream energy factor combines flood runoff depth and flood peak discharge, thereby showing more advantages to describe the event-based inter-scale flow–sediment relationship than other flow-related variables. Overall, this study demonstrates the process-specific characteristics of soil erosion by water flows in the basin system. Therefore, event-based sediment control should be oriented by the process to cut off the connectivity of hyperconcentrated flows and redistribute the erosive energy of flowing water in terms of temporality and spatiality. Furthermore, evaluation of soil conservation benefits should be based on the process of runoff regulation to comprehensively assess the efficiency of anti-erosion strategies in sediment control at the basin scale.

Calcium desensitizer catechin reverses diastolic dysfunction in mice with restrictive cardiomyopathy

Diastolic dysfunction refers to an impaired relaxation and an abnormality in ventricular blood filling during diastole while systolic function is preserved. Cardiac myofibril hypersensitivity to Ca2+ is a major factor that causes impaired relaxation of myocardial cells. The present study investigates the effect of the green tea extract catechins on myofibril calcium desensitization and restoration of diastolic function in a restrictive cardiomyopathy (RCM) mouse model with cardiac troponin mutations. Wild type (WT) and RCM mice were treated daily with catechin (epigallocatechin-3-gallate, EGCg, 50mg/kg body weight) for 3months. Echocardiography and cell based assays were performed to measure cardiac structure and flow-related variables including chamber dimensions, fraction shortening, trans-mitral flow patterns in the experimental mice. In addition, myocyte contractility and calcium dynamics were measured in WT and RCM cardiomyocytes treated in vitro with 5μM EGCg. Our data indicated that RCM mice treated with EGCg showed an improved diastolic function while systolic function remained unchanged. At the cellular level, sarcomere relaxation and calcium decay were accelerated in RCM myocardial cells treated with EGCg. These results suggest that catechin is effective in reversing the impaired relaxation in RCM myocardial cells and rescuing the RCM mice with diastolic dysfunction.

Using a Systems Pharmacology Approach to Study the Effect of Statins on the Early Stage of Atherosclerosis in Humans.

More than 100,000 people have participated in controlled trials of statins (lowering cholesterol drugs) since the introduction of lovastatin in the 1980s. Meta-analyses of this data have shown that statins have a beneficial effect on treated groups compared to control groups, reducing cardiovascular risk. Inhibiting the HMG-CoA reductase in the liver, statins can reduce cholesterol levels, thus reducing LDL levels in circulation. Published data from intravascular ultrasound studies (IVUS) was used in this work to develop and validate a unique integrative system model; this consisted of analyzing control groups from two randomized controlled statins trials (24/97 subjects respectively), one treated group (40 subjects, simvastatin trial), and 27 male subjects (simvastatin, pharmacokinetic study). The model allows to simulate the pharmacokinetics of statins and its effect on the dynamics of lipoproteins (e.g., LDL) and the inflammatory pathway while simultaneously exploring the effect of flow-related variables (e.g., wall shear stress) on atherosclerosis progression.

Algogenic substances and metabolic status in work-related Trapezius Myalgia: a multivariate explorative study.

BackgroundThis study compares the levels of algesic substances between subjects with trapezius myalgia (TM) and healthy controls (CON) and explores the multivariate correlation pattern between these substances, pain, and metabolic status together with relative blood flow changes reported in our previous paper (Eur J Appl Physiol 108:657–669, 2010).Methods43 female workers with (TM) and 19 females without (CON) trapezius myalgia were – using microdialysis - compared for differences in interstitial concentrations of interleukin-6 (IL-6), bradykinin (BKN), serotonin (5-HT), lactate dehydrogenas (LDH), substance P, and N-terminal propeptide of procollagen type I (PINP) in the trapezius muscle at rest and during repetitive/stressful work. These data were also used in multivariate analyses together with previously presented data (Eur J Appl Physiol 108:657–669, 2010): trapezius muscle blood flow, metabolite accumulation, oxygenation, and pain development and sensitivity.ResultsSubstance P was significantly elevated in TM (p=0.0068). No significant differences were found in the classical algesic substances (p: 0.432-0.926). The multivariate analysis showed that blood flow related variables, interstitial concentrations of metabolic (pyruvate), and algesic (BKN and K+) substances were important for the discrimination of the subjects to one of the two groups (R2: 0.19-0.31, p<0.05). Pain intensity was positively associated with levels of 5-HT and K+ and negatively associated with oxygenation indicators and IL-6 in TM (R2: 0.24, p<0.05). A negative correlation existed in TM between mechanical pain sensitivity of trapezius and BKN and IL-6 (R2: 0.26-0.39, p<0.05).ConclusionThe present study increased understanding alterations in the myalgic muscle. When considering the system-wide aspects, increased concentrations of lactate, pyruvate and K+ and decreased oxygenation characterized TM compared to CON. There are three major possible explanations for this finding: the workers with pain had relatively low severity of myalgia, metabolic alterations preceded detectable alterations in levels of algesics, or peripheral sensitization and other muscle alterations existed in TM. Only SP of the investigated algesic substances was elevated in TM. Several of the algesics were of importance for the levels of pain intensity and mechanical pain sensitivity in TM. These results indicate peripheral contribution to maintenance of central nociceptive and pain mechanisms and may be important to consider when designing treatments.Electronic supplementary materialThe online version of this article (doi:10.1186/1471-2474-15-357) contains supplementary material, which is available to authorized users.

Acoustical detection of coronary stenosis: a double-blinded angiographic comparison in a clinically relevant cohort

Background: Hemodynamically significant coronary stenosis generates local blood flow turbulence. In a prior study, we demonstrated feasibility of acoustical detection (AD) to identify this turbulence using a specialized microphone that detects acoustical pressure waves from the chest wall and analyzes signals using a modified form of fast Fourier transform (FFT). We have expanded our study to include analysis in the setting of clinically relevant variables including age, sex, body mass index (BMI), hemoglobin (Hgb), and left ventricular ejection fraction (EF). We hypothesize that this AD modality will remain validated in a clinically relevant cohort of patients, including those with potential confounding variables. Methods: We prospectively studied 199 consecutive patients who underwent elective coronary angiography. Patients with history of valvular disease or prior thoracic surgery of any kind were excluded. AD data were collected prior to angiography at predetermined anterior thoracic auscultation sites. An experienced cardiologist blinded to clinical and acoustic data recorded the maximal percent diameter stenosis in each of 16 coronary segments. Acoustic data were analyzed by an acoustical engineer blinded to clinical and angiographic data. AD analysis results were graded as "Normal" or "Diseased." Results: All pts had analyzable acoustic recordings. Prevalence of significant CAD (>50% stenosis in any segment) at angiography was 51.8% (n=106; 22%, 19%, 9% with 1, 2, 3-vessel disease). Four patients had a total occlusion of a single vessel and no other significant disease. The sensitivity and specificity for AD of a coronary stenosis >50% in any vessel were 0.64 and 0.75 (NPV 0.66 and PPV 0.73). AD had maximal accuracy in detecting a >50% stenosis with an area under the ROC curve of 0.69 (p<0.0001). When coronary stenosis was defined as 70% rather than 50%, the sensitivity and specificity of AD were 0.65 and 0.69. When pts with isolated total occlusions were excluded, the area under the ROC curve was essentially unchanged (0.67). Multivariable logistic regression of age, sex, BMI, Hgb, and EF demonstrated no significant correlation. Conclusion: These data support our hypothesis that AD remains a validated screening modality to detect coronary stenosis independent of theorized confounding mechanical and flow-related variables. The reduced economic cost, potential widespread use, and lack of risk altogether make this method a practical and potentially transformative technology to detect significant coronary stenosis in a clinically relevant patient population.

Uncertainty quantification for data assimilation in a steady incompressible Navier-Stokes problem

The reliable and effective assimilation of measurements and numerical simulations in engineering applications involving computational fluid dynamics is an emerging problem as soon as new devices provide more data. In this paper we are mainly driven by hemodynamics applications, a field where the progressive increment of measures and numerical tools makes this problem particularly up-to-date. We adopt a Bayesian approach to the inclusion of noisy data in the incompressible steady Navier-Stokes equations (NSE). The purpose is the quantification of uncertainty affecting velocity and flow related variables of interest, all treated as random variables. The method consists in the solution of an optimization problem where the misfit between data and velocity - in a convenient norm - is minimized under the constraint of the NSE. We derive classical point estimators, namely the maximum a posteriori – MAP – and the maximum likelihood – ML – ones. In addition, we obtain confidence regions for velocity and wall shear stress, a flow related variable of medical relevance. Numerical simulations in 2-dimensional and axisymmetric 3-dimensional domains show the gain yielded by the introduction of a complete statistical knowledge in the assimilation process.