Extinction risk modeling predicts range-wide differences of climate change impact on Karner blue butterfly (Lycaeides melissa samuelis).

The Karner blue butterfly (Lycaeides melissa samuelis, or Kbb), a federally endangered species under the U.S. Endangered Species Act in decline due to habitat loss, can be further threatened by climate change. Evaluating how climate shapes the population trend of the Kbb can help in the development of adaptive management plans. Current demographic models for the Kbb incorporate in either a density-dependent or density-independent manner. We instead created mixed density-dependent and -independent (hereafter "endo-exogenous") models for Kbbs based on long-term count data of five isolated populations in the upper Midwest, United States during two flight periods (May to June and July to August) to understand how the growth rates were related to previous population densities and abiotic environmental conditions, including various macro- and micro-climatic variables. Our endo-exogenous extinction risk models showed that both density-dependent and -independent components were vital drivers of the historical population trends. However, climate change impacts were not always detrimental to Kbbs. Despite the decrease of population growth rate with higher overwinter temperatures and spring precipitations in the first generation, the growth rate increased with higher summer temperatures and precipitations in the second generation. We concluded that finer spatiotemporally scaled models could be more rewarding in guiding the decision-making process of Kbb restoration under climate change.

Linear Support Vector Machine Classification of Plant Stress From Soybean Aphid (Hemiptera: Aphididae) Using Hyperspectral Reflectance.

Spectral remote sensing has the potential to improve scouting and management of soybean aphid (Aphis glycines Matsumura), which can cause yield losses of over 40% in the North Central Region of the United States. We used linear support vector machines (SVMs) to determine 1) whether hyperspectral samples could be classified into treat/no-treat classes based on the economic threshold (250 aphids per plant) and 2) how many wavelengths or features are needed to generate an accurate model without overfitting the data. A range of aphid infestation levels on soybean was created using caged field plots in 2013, 2014, 2017, and 2018 in Minnesota and in 2017 and 2018 in Iowa. Hyperspectral measurements of soybean canopies in each plot were recorded with a spectroradiometer. SVM training and testing were performed using 15 combinations of normalized canopy reflectance at wavelengths of 720, 750, 780, and 1,010 nm. Pairwise Bonferroni-adjusted t-tests of Cohen's kappa values showed four wavelength combinations were optimal, namely model 1 (780 nm), model 2 (780 and 1,010 nm), model 3 (780, 1,010, and 720 nm), and model 4 (780, 1,010, 720, and 750 nm). Model 2 showed the best overall performance, with an accuracy of 89.4%, a sensitivity of 81.2%, and a specificity of 91.6%. The findings from this experiment provide the first documentation of successful classification of remotely sensed spectral data of soybean aphid-induced stress into threshold-based classes.

Modeling land use change and forest carbon stock changes in temperate forests in the United States.

BACKGROUND: Forests provide the largest terrestrial sink of carbon (C). However, these C stocks are threatened by forest land conversion. Land use change has global impacts and is a critical component when studying C fluxes, but it is not always fully considered in C accounting despite being a major contributor to emissions. An urgent need exists among decision-makers to identify the likelihood of forest conversion to other land uses and factors affecting C loss. To help address this issue, we conducted our research in California, Colorado, Georgia, New York, Texas, and Wisconsin. The objectives were to (1) model the probability of forest conversion and C stocks dynamics using USDA Forest Service Forest Inventory and Analysis (FIA) data and (2) create wall-to-wall maps showing estimates of the risk of areas to convert from forest to non-forest. We used two modeling approaches: a machine learning algorithm (random forest) and generalized mixed-effects models. Explanatory variables for the models included ecological attributes, topography, census data, forest disturbances, and forest conditions. Model predictions and Landsat spectral information were used to produce wall-to-wall probability maps of forest change using Google Earth Engine. RESULTS: During the study period (2000-2017), 3.4% of the analyzed FIA plots transitioned from forest to mixed or non-forested conditions. Results indicate that the change in land use from forests is more likely with increasing human population and housing growth rates. Furthermore, non-public forests showed a higher probability of forest change compared to public forests. Areas closer to cities and coastal areas showed a higher risk of transition to non-forests. Out of the six states analyzed, Colorado had the highest risk of conversion and the largest amount of aboveground C lost. Natural forest disturbances were not a major predictor of land use change. CONCLUSIONS: Land use change is accelerating globally, causing a large increase in C emissions. Our results will help policy-makers prioritize forest management activities and land use planning by providing a quantitative framework that can enhance forest health and productivity. This work will also inform climate change mitigation strategies by understanding the role that land use change plays in C emissions.

Analysis and modeling of Blastomyces dermatitidis environmental prevalence in Minnesota using soil collected to compare basal and outbreak levels.

Outbreaks of blastomycosis, caused by the fungus Blastomyces dermatitidis, occur in endemic areas of the United States and Canada but the geographic range of blastomycosis is expanding. Previous studies inferred the location of B. dermatitidis through epidemiologic data associated with outbreaks because culture of B. dermatitidis from the environment is often unsuccessful. In this study, we used a culture-independent, PCR-based method to identify B. dermatitidis DNA in environmental samples using the BAD1 promoter region. We tested 250 environmental samples collected in Minnesota, either associated with blastomycosis outbreaks or environmental samples collected from high- and low-endemic regions to determine basal prevalence of B. dermatitidis in the environment. We identified a fifth BAD1 promoter haplotype of B. dermatitidis prevalent in Minnesota. Ecological niche analysis identified latitude, longitude, elevation, and site classification as environmental parameters associated with the presence of B. dermatitidis Using this analysis, a Random Forest model predicted B. dermatitidis presence in basal environmental samples with 75% accuracy. These data support use of culture-independent, PCR-based environmental sampling to track spread into new regions and to characterize the unknown B. dermatitidis environmental niche.Importance Upon inhalation of spores from the fungus Blastomyces dermatitidis from the environment, humans and animals can develop the disease blastomycosis. Based on disease epidemiology, B. dermatitidis is known to be endemic in the United States and Canada around the Great Lakes and in the Ohio and Mississippi River Valleys but is starting to emerge in other areas. B. dermatitidis is extremely difficult to culture from the environment so little is known about the environmental reservoirs for this pathogen. We used a culture-independent PCR-based assay to identify the presence of B. dermatitidis DNA in soil samples from Minnesota. By combining molecular data with ecological niche modeling, we were able to predict the presence of B. dermatitidis in environmental samples with 75% accuracy and to define characteristics of the B. dermatitidis environmental niche. Importantly, we showed the effectiveness of using a PCR-based assay to identify B. dermatitidis in environmental samples.

An immediate access dialysis graft designed to prevent needle-related complications: Results from the initial pre-clinical studies.

INTRODUCTION: No technology has been specifically developed with the intent to reduce needle-related vascular access injuries; a significant source of complications and abandonment. We present the initial pre-clinical study results of a novel, self-sealing, immediate cannulation dialysis graft that aims to prevent needle-related complications; to promote safe, reliable needle access; to reduce catheter use; and could facilitate home hemodialyisis. METHODS: The innovative graft design consists of two cannulation chambers with self-sealing properties and materials that prevent side and back wall needle puncture. Study and control grafts (expanded polytetrafluoroethylene) were implanted in one pig and 10 sheep in two studies over the course of 1 year. First cannulation occurred immediately post implant for all study grafts. Post-cannulation time to hemostasis, hematoma and seroma formation, infection, and patency were recorded. RESULTS: The two studies account for nearly 60 weeks (average 6.4 weeks/graft) of study graft follow-up. In the ovine study, average study graft time to hemostasis was 27.3 s (standard deviation = 26.3, range = 0-120), and the control averaged 177.2 s (standard deviation = 113.4, range = 60-600), p < 0.0001. Secondary patency was 75% and 67% for the study and control grafts, respectively. Neither study nor control groups experienced seroma, graft infections, or deaths. DISCUSSION: All novel grafts in the studies were implanted successfully and functioned as intended. There were no complications related to tunneling of the study graft and the chamber prevented back/side wall needle injury. This novel technology may help to mitigate these needle-related complications, while allowing for early/immediate cannulation which could also reduce catheter contact time.

Detection of Stress Induced by Soybean Aphid (Hemiptera: Aphididae) Using Multispectral Imagery from Unmanned Aerial Vehicles.

Soybean aphid, Aphis glycines Matsumura (Hemiptera: Aphididae), is a common pest of soybean, Glycine max (L.) Merrill (Fabales: Fabaceae), in North America requiring frequent scouting as part of an integrated pest management plan. Current scouting methods are time consuming and provide incomplete coverage of soybean. Unmanned aerial vehicles (UAVs) are capable of collecting high-resolution imagery that offer more detailed coverage in agricultural fields than traditional scouting methods. Recently, it was documented that changes to the spectral reflectance of soybean canopies caused by aphid-induced stress could be detected from ground-based sensors; however, it remained unknown whether these changes could also be detected from UAV-based sensors. Small-plot trials were conducted in 2017 and 2018 where cages were used to manipulate aphid populations. Additional open-field trials were conducted in 2018 where insecticides were used to create a gradient of aphid pressure. Whole-plant soybean aphid densities were recorded along with UAV-based multispectral imagery. Simple linear regressions were used to determine whether UAV-based multispectral reflectance was associated with aphid populations. Our findings indicate that near-infrared reflectance decreased with increasing soybean aphid populations in caged trials when cumulative aphid days surpassed the economic injury level, and in open-field trials when soybean aphid populations were above the economic threshold. These findings provide the first documentation of soybean aphid-induced stress being detected from UAV-based multispectral imagery and advance the use of UAVs for remote scouting of soybean aphid and other field crop pests.

Spatiotemporal remote sensing of ecosystem change and causation across Alaska.

Contemporary climate change in Alaska has resulted in amplified rates of press and pulse disturbances that drive ecosystem change with significant consequences for socio-environmental systems. Despite the vulnerability of Arctic and boreal landscapes to change, little has been done to characterize landscape change and associated drivers across northern high-latitude ecosystems. Here we characterize the historical sensitivity of Alaska's ecosystems to environmental change and anthropogenic disturbances using expert knowledge, remote sensing data, and spatiotemporal analyses and modeling. Time-series analysis of moderate-and high-resolution imagery was used to characterize land- and water-surface dynamics across Alaska. Some 430,000 interpretations of ecological and geomorphological change were made using historical air photos and satellite imagery, and corroborate land-surface greening, browning, and wetness/moisture trend parameters derived from peak-growing season Landsat imagery acquired from 1984 to 2015. The time series of change metrics, together with climatic data and maps of landscape characteristics, were incorporated into a modeling framework for mapping and understanding of drivers of change throughout Alaska. According to our analysis, approximately 13% (~174,000 ± 8700 km2 ) of Alaska has experienced directional change in the last 32 years (±95% confidence intervals). At the ecoregions level, substantial increases in remotely sensed vegetation productivity were most pronounced in western and northern foothills of Alaska, which is explained by vegetation growth associated with increasing air temperatures. Significant browning trends were largely the result of recent wildfires in interior Alaska, but browning trends are also driven by increases in evaporative demand and surface-water gains that have predominately occurred over warming permafrost landscapes. Increased rates of photosynthetic activity are associated with stabilization and recovery processes following wildfire, timber harvesting, insect damage, thermokarst, glacial retreat, and lake infilling and drainage events. Our results fill a critical gap in the understanding of historical and potential future trajectories of change in northern high-latitude regions.

Shrinkage / stress reduction and mechanical properties improvement in restorative composites formulated with thio-urethane oligomers.

Thio-urethane oligomers (TUs) have been shown to favorably modify methacrylate networks to reduce stress and significantly increase fracture toughness. Since those are very desirable features in dental applications, the objective of this work was to characterize restorative composites formulated with the addition of TUs. TUs were synthesized by combining thiols - pentaerythritol tetra-3-mercaptopropionate (PETMP) or trimethylol-tris-3-mercaptopropionate (TMP) - with isocyanates - 1,6-Hexanediol-diissocyante (HDDI) (aliphatic) or 1,3-bis(1-isocyanato-1-methylethyl)benzene (BDI) (aromatic) or dicyclohexylmethane 4,4'-Diisocyanate (HMDI) (cyclic), at 1:2 isocyanate:thiol, leaving pendant thiols. 20wt% TU were added to BisGMA-TEGDMA (70-30%). To this organic matrix, 70wt% silanated inorganic fillers were added. Near-IR was used to follow methacrylate conversion and rate of polymerization (Rpmax). Mechanical properties were evaluated in three-point bending (ISO 4049) for flexural strength/modulus (FS/FM) and toughness (T), and notched specimens (ASTM Standard E399-90) for fracture toughness (KIC). Polymerization stress (PS) was measured on the Bioman. Volumetric shrinkage (VS) was measured with the bonded disk technique. Glass transition temperature (Tg) and heterogeneity of network were obtained with dynamic mechanical analysis. The addition of TUs led to an increase in mechanical properties (except for Tg and FS). Fracture toughness ranged from 1.6-1.94MPam1/2 for TU-modified groups, an increase of 33-61% in relation to the control (1.21 ± 0.1MPam1/2). Toughness showed a two-fold increase in relation to the control: from 0.91MPa to values ranging from 1.70-1.95MPa. Flexural modulus was statistically higher for the TU-modified groups. The Tg, as expected, decreased for all TU groups due to the greater flexibility imparted to the network (which also explains the increase in toughness and fracture toughness). Narrower tan-delta peaks suggest more homogeneous networks for the TU-modified materials, though differences were marked only for TMP_AL. Degree of conversion was not affected by the addition of TUs. VS was similar for all groups, with one exception where VS dropped (PETMP-cyclic). Finally, PS showed a reduction of 23-57% for TU-modified groups (6.7 ± 1.3 to 11.9 ± 1.0MPa) in relation to the control (15.56 ± 1.4MPa). The addition of thio-urethane oligomers was able to reduce polymerization stress by up to 57% while increasing fracture toughness by up to 61%.

Historical and projected trends in landscape drivers affecting carbon dynamics in Alaska.

Modern climate change in Alaska has resulted in widespread thawing of permafrost, increased fire activity, and extensive changes in vegetation characteristics that have significant consequences for socioecological systems. Despite observations of the heightened sensitivity of these systems to change, there has not been a comprehensive assessment of factors that drive ecosystem changes throughout Alaska. Here we present research that improves our understanding of the main drivers of the spatiotemporal patterns of carbon dynamics using in situ observations, remote sensing data, and an array of modeling techniques. In the last 60 yr, Alaska has seen a large increase in mean annual air temperature (1.7°C), with the greatest warming occurring over winter and spring. Warming trends are projected to continue throughout the 21st century and will likely result in landscape-level changes to ecosystem structure and function. Wetlands, mainly bogs and fens, which are currently estimated to cover 12.5% of the landscape, strongly influence exchange of methane between Alaska's ecosystems and the atmosphere and are expected to be affected by thawing permafrost and shifts in hydrology. Simulations suggest the current proportion of near-surface (within 1 m) and deep (within 5 m) permafrost extent will be reduced by 9-74% and 33-55% by the end of the 21st century, respectively. Since 2000, an average of 678 595 ha/yr was burned, more than twice the annual average during 1950-1999. The largest increase in fire activity is projected for the boreal forest, which could result in a reduction in late-successional spruce forest (8-44%) and an increase in early-successional deciduous forest (25-113%) that would mediate future fire activity and weaken permafrost stability in the region. Climate warming will also affect vegetation communities across arctic regions, where the coverage of deciduous forest could increase (223-620%), shrub tundra may increase (4-21%), and graminoid tundra might decrease (10-24%). This study sheds light on the sensitivity of Alaska's ecosystems to change that has the potential to significantly affect local and regional carbon balance, but more research is needed to improve estimates of land-surface and subsurface properties, and to better account for ecosystem dynamics affected by a myriad of biophysical factors and interactions.

Accurate Ionization Potentials and Electron Affinities of Acceptor Molecules III: A Benchmark of GW Methods.

The performance of different GW methods is assessed for a set of 24 organic acceptors. Errors are evaluated with respect to coupled cluster singles, doubles, and perturbative triples [CCSD(T)] reference data for the vertical ionization potentials (IPs) and electron affinities (EAs), extrapolated to the complete basis set limit. Additional comparisons are made to experimental data, where available. We consider fully self-consistent GW (scGW), partial self-consistency in the Green's function (scGW0), non-self-consistent G0W0 based on several mean-field starting points, and a "beyond GW" second-order screened exchange (SOSEX) correction to G0W0. We also describe the implementation of the self-consistent Coulomb hole with screened exchange method (COHSEX), which serves as one of the mean-field starting points. The best performers overall are G0W0+SOSEX and G0W0 based on an IP-tuned long-range corrected hybrid functional with the former being more accurate for EAs and the latter for IPs. Both provide a balanced treatment of localized vs delocalized states and valence spectra in good agreement with photoemission spectroscopy (PES) experiments.

Applications of very high-resolution imagery in the study and conservation of large predators in the Southern Ocean.

The Southern Ocean is one of the most rapidly changing ecosystems on the planet due to the effects of climate change and commercial fishing for ecologically important krill and fish. Because sea ice loss is expected to be accompanied by declines in krill and fish predators, decoupling the effects of climate and anthropogenic changes on these predator populations is crucial for ecosystem-based management of the Southern Ocean. We reviewed research published from 2007 to 2014 that incorporated very high-resolution satellite imagery to assess distribution, abundance, and effects of climate and other anthropogenic changes on populations of predators in polar regions. Very high-resolution imagery has been used to study 7 species of polar animals in 13 papers, many of which provide methods through which further research can be conducted. Use of very high-resolution imagery in the Southern Ocean can provide a broader understanding of climate and anthropogenic forces on populations and inform management and conservation recommendations. We recommend that conservation biologists continue to integrate high-resolution remote sensing into broad-scale biodiversity and population studies in remote areas, where it can provide much needed detail.

International telemedicine consultations for neurodevelopmental disabilities.

BACKGROUND: A telemedicine program was developed between the Children's National Medical Center (CNMC) in Washington, DC, and the Sheikh Khalifa Bin Zayed Foundation in the United Arab Emirates (UAE). A needs assessment and a curriculum of on-site training conferences were devised preparatory to an ongoing telemedicine consultation program for children with neurodevelopmental disabilities in the underserved eastern region of the UAE. MATERIALS AND METHODS: Weekly telemedicine consultations are provided by a multidisciplinary faculty. Patients are presented in the UAE with their therapists and families. Real-time (video over Internet protocol; average connection, 768 kilobits/s) telemedicine conferences are held weekly following previews of medical records. A full consultation report follows each telemedicine session. RESULTS: Between February 29, 2012 and June 26, 2013, 48 weekly 1-h live interactive telemedicine consultations were conducted on 48 patients (28 males, 20 females; age range, 8 months-22 years; median age, 5.4 years). The primary diagnoses were cerebral palsy, neurogenetic disorders, autism, neuromuscular disorders, congenital anomalies, global developmental delay, systemic disease, and epilepsy. Common comorbidities were cognitive impairment, communication disorders, and behavioral disorders. Specific recommendations included imaging and DNA studies, antiseizure management, spasticity management including botulinum toxin protocols, and specific therapy modalities including taping techniques, customized body vests, and speech/language and behavioral therapy. Improved outcomes reported were in clinician satisfaction, achievement of therapy goals for patients, and requests for ongoing sessions. CONCLUSIONS: Weekly telemedicine sessions coupled with triannual training conferences were successfully implemented in a clinical program dedicated to patients with neurodevelopmental disabilities by the Center for Neuroscience at CNMC and the UAE government. International consultations in neurodevelopmental disabilities utilizing telemedicine services offer a reliable and productive method for joint clinical programs.

Cryptococcal genotype influences immunologic response and human clinical outcome after meningitis.

UNLABELLED: In sub-Saharan Africa, cryptococcal meningitis (CM) continues to be a predominant cause of AIDS-related mortality. Understanding virulence and improving clinical treatments remain important. To characterize the role of the fungal strain genotype in clinical disease, we analyzed 140 Cryptococcus isolates from 111 Ugandans with AIDS and CM. Isolates consisted of 107 nonredundant Cryptococcus neoformans var. grubii strains and 8 C. neoformans var. grubii/neoformans hybrid strains. Multilocus sequence typing (MLST) was used to characterize genotypes, yielding 15 sequence types and 4 clonal clusters. The largest clonal cluster consisted of 74 isolates. The results of Burst and phylogenetic analysis suggested that the C. neoformans var. grubii strains could be separated into three nonredundant evolutionary groups (Burst group 1 to group 3). Patient mortality was differentially associated with the different evolutionary groups (P = 0.04), with the highest mortality observed among Burst group 1, Burst group 2, and hybrid strains. Compared to Burst group 3 strains, Burst group 1 strains were associated with higher mortality (P = 0.02), exhibited increased capsule shedding (P = 0.02), and elicited a more pronounced Th(2) response during ex vivo cytokine release assays with strain-specific capsule stimulation (P = 0.02). The results of these analyses suggest that cryptococcal strain variation can be an important determinant of human immune responses and mortality. IMPORTANCE: Cryptococcus neoformans is a common life-threatening human fungal pathogen that is responsible for an estimated 1 million cases of meningitis in HIV-infected patients annually. Virulence factors that are important in human disease have been identified, yet the impacts of the fungal strain genotype on virulence and outcomes of human infection remain poorly understood. Using an analysis of strain variation based on in vitro assays and clinical data from Ugandans living with AIDS and cryptococcal infection, we report that strain genotype predicts the type of immune response and mortality risk. These studies suggest that knowledge of the strain genotype during human infections could be used to predict disease outcomes and lead to improved treatment approaches aimed at targeting the specific combination of pathogen virulence and host response.

Physical inactivity: associated diseases and disorders.

A sedentary lifestyle is a very serious worldwide problem, especially in North America and Europe. Unfortunately, physical inactivity, which has progressively increased over the past several decades, significantly increases the risk of numerous diseases/disorders, including several forms of cancer, diabetes, hypertension, coronary and cerebrovascular diseases, overweight/obesity, and all-cause mortality, among others. Unless there is a reversal of this sedentary lifestyle, the incidence of these diseases/disorders will increase, life expectancy will decrease, and medical costs will continue to rise.

Choosing the optimal wall shear parameter for the prediction of plaque location-A patient-specific computational study in human left coronary arteries.

OBJECTIVE: While the correlation of atherosclerotic plaque locations with local wall shear stress magnitude has been evaluated previously by other investigators in both right (RCA) and left coronary arteries (LCA), the relative performance of average wall shear stress (AWSS), average wall shear stress gradient (AWSSG), oscillatory shear index (OSI) and relative residence time (RRT) as indicators of potential atherosclerotic plaque locations has not been studied for the LCA. Here we determine the performance of said wall shear parameters in the LCA for the prediction of plaque development locations and compare these results to those previously found in the RCA. METHODS: We obtained 30 patient-specific geometries (mean age 67.1 (± 9.2) years, all with stable angina) of the LCA using dual-source computed tomography and virtually removed any plaque present. We then performed computational fluid dynamics simulations to calculate the wall shear parameters. RESULTS: For the 96 total plaques, AWSS had a higher sensitivity for the prediction of plaque locations (86 ± 25%) than AWSSG (65 ± 37%, p<0.05), OSI (67 ± 32%, p<0.01) or RRT (48 ± 38%, p<0.001). RRT had a higher PPV (49 ± 36%) than AWSS (31 ± 20%, p<0.05) or AWSSG (16 ± 12%, p<0.001). Segment 5 of the LCA presented with overall low values for sensitivity and PPV. Parameter performance in the remainder of the LCA was comparable to that in the RCA. CONCLUSIONS: AWSS features remarkably high sensitivity, but does not reach the PPV of RRT. This may indicate that while low wall shear stress is necessary for plaque formation, its presence alone is not sufficient to predict future plaque locations. Time dependent factors have to be taken into account as well.

Diseases and disorders associated with excess body weight.

Excess body weight is a very serious problem, especially in North America and Europe. It has been referred to as a "pandemic" since it has progressively increased over the past several decades. Moreover, excess body weight significantly increases the risk of numerous diseases and clinical disorders, including all-cause mortality, coronary and cerebrovascular diseases, various cancers, type 2 diabetes mellitus, hypertension, liver disease and asthma, as well as psychopathology, among others. Unfortunately, overweight and obesity are now common in both young children and adolescents. Although the causes of excess body weight are multi-factorial, the most important factors are excess caloric intake coupled with limited energy expenditure. Therefore, lifestyle modification can significantly reduce the risk of morbidity and mortality and thereby increase longevity and improve the quality of life.

Computed high concentrations of low-density lipoprotein correlate with plaque locations in human coronary arteries.

Subendothelial accumulation of low-density lipoprotein (LDL) in arterial walls is an initiator of atherosclerotic plaque formation. We report here on the correlation between healthy state subendothelial LDL concentration distribution and sites of subsequent plaque formation in coronary arteries of patients with coronary artery disease (CAD). We acquired left (LCA) and right coronary artery (RCA) and atherosclerotic plaque geometries of 60 patients with CAD using dual-source computed tomography angiography. After virtually removing all plaques to obtain an approximation of the arteries' healthy state, we calculated LDL concentration in the artery walls as a function of local lumen-side shear stress. We found that maximum subendothelial LDL concentrations at plaque locations were, on average, 45% (RCA) and 187% (LCA) higher than the respective average subendothelial concentration. Our results demonstrate that locally elevated subendothelial LDL concentration correlates with subsequent plaque formation at the same location.

Choosing the optimal wall shear parameter for the prediction of plaque location-A patient-specific computational study in human right coronary arteries.

BACKGROUND: Average wall shear-stress (AWSS), average wall shear-stress gradient (AWSSG), oscillatory shear index (OSI) and relative residence time (RRT) are believed to predict areas vulnerable to plaque formation in the coronary arteries. Our aim was to analyze the correlation of these parameters in patients' vessels before the onset of atherosclerosis to the specific plaque sites thereafter, and to compare the parameters' sensitivity and positive predictive value. METHODS: We obtained 30 patient-specific geometries (mean age 67.1 (+ or - 9.2) years, all with stable angina) of the right coronary artery (RCA) using dual-source computed tomography (CT) and virtually removed any plaque present. We then performed computational fluid dynamics (CFD) simulations to calculate the wall shear parameters. RESULTS: For the 120 total plaques, AWSS had on average a higher sensitivity for the prediction of plaque locations (72 + or - 25%) than AWSSG (68 + or - 36%), OSI (60 + or - 30%, p<0.05), and RRT (69 + or - 59%); while OSI had a higher positive predict value (PPV) (68 + or - 34%) than AWSS (47 + or - 27%, p<0.001), AWSSG (37 + or - 23, p<0.001) and RRT (59 + or - 34%). A significant difference was also found between AWSSG and RRT (p<0.01) concerning PPV. CONCLUSIONS: OSI and RRT are the optimal parameters when the number of false positives is to be minimized. AWSS accurately identifies the largest number of plaques, but produces more false positives than OSI and RRT.

Long-term follow-up, computed tomography, and computational fluid dynamics of the Cabrol procedure.

OBJECTIVES: The Cabrol procedure is characterized by insertion of an ascending aortic composite graft with reimplantation of the coronary arteries by the interposition of a graft tube. Our purpose is to report the clinical long-term follow-up and computed tomographic findings in patients having undergone the Cabrol procedure and to determine blood flow in the Cabrol graft using computational fluid dynamics. METHODS: Clinical follow-up (76.6 +/- 16.6 months) and dual-source computed tomographic angiography data of 7 patients (all men, mean age 54.9 +/- 9.6 years) with 12 Cabrol grafts (left main coronary artery, n = 7; right coronary artery, n = 5) were reviewed. In 2 patients, the right coronary artery was directly reattached to the aortic graft. Computational fluid dynamics were calculated using computed tomographic data of a patient with the Cabrol procedure and compared with those in a Valsalva graft and a healthy aortic root. RESULTS: Computed tomography showed Cabrol graft occlusions to 1 of 7 (14%) left main and of 2 of 5 (40%) right coronary arteries. Six grafts to the left main and 3 to the right coronary artery were fully patent, similar to the 2 directly reattached right coronary arteries to the aortic graft. Computational fluid dynamics results show similar blood flow parameters into the coronaries for the healthy aortic root and Valsalva graft. In the Cabrol graft, a spiraling flow pattern with low flow into the right coronary artery was found (right coronary artery = 1 mL/min at both systole and diastole). CONCLUSIONS: Our study indicates low flow rates particularly in the right Cabrol graft correlating with a higher incidence of occlusions of the right as compared with the left Cabrol graft at long-term follow-up.

Ex vivo and in vivo coronary ostial locations in humans.

PURPOSE: Knowledge of the normal in vivo distribution and variation of coronary ostial locations is essential in the planning of various interventional and surgical procedures. However, all studies to date have reported the distribution of coronary ostia locations only in cadaver hearts. In this study, we sought to assess the distribution of coronary ostial locations in patients using cardiac dual-source computed tomography (CT) and compare these values to those of human cadaveric specimens. METHODS: Measurements of the coronary ostia location were performed in 150 patients undergoing dual-source CT and in 75 cadavers using open measurement techniques. All 150 patients had a normal aortic valve function and no previous cardiac intervention or surgery. The location of the right and left coronary origin in relation to the aortic annulus and the height of the sinus of Valsalva were measured. RESULTS: Mean ostial locations at CT were 17.0 (+/-3.6) mm and 15.3 (+/-3.1) mm for the right and left coronary ostia, with large variations of both sides (right: 10.4-28.5 mm; left: 9.8-29.3 mm). In cadavers, mean locations were 14.9 (+/-4.3) mm [5-24 mm] for right and 16.0 (+/-3.6) mm [9-24 mm] for left coronary ostia. Comparison of CT and cadaver data showed statistically significant differences for right (P < 0.0001) but not left (P = 0.1675) coronary ostia. CONCLUSIONS: This study provides data of normal coronary ostial origins and demonstrates significant differences between in vivo and ex vivo measurements regarding the right coronary ostium. The observed large variations of coronary ostia origins emphasize the importance of considering such anatomic variations in the development of treatments.