Transcatheter Atrial Septal Defect Closure: Preliminary Experience with the Rashkind Occluder Device

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/72836/1/j.1540-8183.1989.tb00751.x.pd

Serial Changes in Norepinephrine Kinetics Associated With Feeding Dogs a High-Fat Diet

J Clin Hypertens (Greenwich). 2010;12:117–124. © 2009 Wiley Periodicals, Inc. The role of increased sympathetic nervous system (SNS) activity in the pathogenesis of obesity hypertension and insulin resistance is controversial. Eight dogs were instrumented and fed a high-fat diet (HFD) for 6 weeks. Dogs were evaluated for changes in weight, blood pressure, insulin resistance, and norepinephrine (NE) kinetics using a two-compartment model. The HFD resulted in weight gain, hypertension, and insulin resistance. During the 6 weeks of the HFD, although plasma NE concentration trended toward increasing ( P =.09), SNS, assessed by NE kinetic studies, significantly increased ( P =.009). Within 1 week of starting the HFD, NE release into the extravascular compartment (NE 2 ) increased from 3.44±0.59 μg/mL to 4.87±0.80 μg/mL ( P <.01) and this increase was maintained over the next 5 weeks of the HFD (NE 2 at week 6 was 4.66±0.97 μg/mL). In addition to the increased NE 2 there was also a significant increase in NE clearance ( P =.04). There were significant correlations between the increase in NE 2 and both the development of insulin resistance and hypertension. This study supports the hypothesis that activation of the SNS plays a pivotal role in the metabolic and hemodynamic changes that occur with weight gain induced by HFD.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/78633/1/j.1751-7176.2009.00230.x.pd

Fluorescence spectroscopy of normal and follicular cancer samples from human thyroid

An autofluorescence analysis has been performed on healthy as well as tumour thyroid tissue samples to distinguish follicular cancer from normal thyroid. Complete spectra and synchronous spectra have been recordered from properly stored samples. Fluorescence bands located at 350 nm and 400 nm has been observed in the analysed cancer samples

Volumetric real-time particle-based representation of large unstructured tetrahedral polygon meshes

In this paper we propose a particle-based volume rendering approach for unstructured, three-dimensional, tetrahedral polygon meshes. We stochastically generate millions of particles per second and project them on the screen in real-time. In contrast to previous rendering techniques of tetrahedral volume meshes, our method does not need a prior depth sorting of geometry. Instead, the rendered image is generated by choosing particles closest to the camera. Furthermore, we use spatial superimposing. Each pixel is constructed from multiple subpixels. This approach not only increases projection accuracy, but allows also a combination of subpixels into one superpixel that creates the well-known translucency effect of volume rendering. We show that our method is fast enough for the visualization of unstructured three-dimensional grids with hard real-time constraints and that it scales well for a high number of particles

Using spectral diversity and heterogeneity measures to map habitat mosaics: An example from the Classical Karst

Questions: Can we map complex habitat mosaics from remote-­sensing data? In doing this, are measures of spectral heterogeneity useful to improve image classification performance? Which measures are the most important? How can multitemporal data be integrated in a robust framework? Location: Classical Karst (NE Italy). Methods: First, a habitat map was produced from field surveys. Then, a collection of 12 monthly Sentinel-­2 images was retrieved. Vegetation and spectral heterogeneity (SH) indices were computed and aggregated in four combinations: (1) monthly layers of vegetation and SH indices; (2) seasonal layers of vegetation and SH indices; (3) yearly layers of SH indices computed across the months; and (4) yearly layers of SH indices computed across the seasons. For each combination, a Random Forest clas- sification was performed, first with the complete set of input layers and then with a subset obtained by recursive feature elimination. Training and validation points were independently extracted from field data. Results: The maximum overall accuracy (0.72) was achieved by using seasonally ag- gregated vegetation and SH indices, after the number of vegetation types was re- duced by aggregation from 26 to 11. The use of SH measures significantly increased the overall accuracy of the classification. The spectral β-­diversity was the most im- portant variable in most cases, while the spectral α-­diversity and Rao's Q had a low relative importance, possibly because some habitat patches were small compared to the window used to compute the indices. Conclusions: The results are promising and suggest that image classification frame- works could benefit from the inclusion of SH measures, rarely included before. Habitat mapping in complex landscapes can thus be improved in a cost-­and time-­effective way, suitable for monitoring applications

Clinical and hemodynamic follow-up of left ventricular to aortic conduits in patients with aortic stenosis

To assess the long-term results of left ventricular outflow tract reconstruction utilizing an apical left ventricular to aortic valved (porcine) conduit the clinical and hemodynamic data were reviewed from 24 patients who had placement of an apico-aortic conduit. Eighteen of the patients are asymptomatic and taking no cardiac medications. Three patients were reoperated on, one patient 1.5 years after his original operation for subacute bacterial endocarditis and two patients 3 to 4 years after their original operation for severe conduit valve insufficiency. None of the patients is taking anticoagulants and no thromboembolic events have occurred. Postoperative catheterization has been performed 1 to 1.5 years (mean 1.2) after repair in 15 of 21 patients. The rest left ventricular outflow tract gradient has decreased from 102.5 ± 20 mm Hg preoperatively to 14.8 ± 9.9 mm Hg postoperatively (probability [p] < 0.001). Some degree of conduit obstruction was demonstrated by catheter passage in 11 of the 15 patients. In these 11 patients, the obstruction occurred at three distant sites: at the egress of the left ventricle in 9, at the porcine valve in 5 and at the aortic to conduit junction in 1. Isometric exercise in five and supine bicycle exercise in six patients increased the left ventricular outflow tract gradient by 2.5 ± 1.1 and 20.8 ± 11.8 mm Hg, respectively, despite an increase in cardiac index of 1 ± 0.3 and 3.7 ± 0.4 liters/min per m2, respectively. The data suggest that a left ventricular to aortic conduit is an effective form of therapy for severe left ventricular outflow tract obstruction

Temporal relationship between instantaneous pressure gradients and peak‐to‐peak systolic ejection gradient in congenital aortic stenosis

ObjectiveWe sought to identify a time during cardiac ejection when the instantaneous pressure gradient (IPG) correlated best, and near unity, with peak‐to‐peak systolic ejection gradient (PPSG) in patients with congenital aortic stenosis. Noninvasive echocardiographic measurement of IPG has limited correlation with cardiac catheterization measured PPSG across the spectrum of disease severity of congenital aortic stenosis. A major contributor is the observation that these measures are inherently different with a variable relationship dependent on the degree of stenosis.DesignHemodynamic data from cardiac catheterizations utilizing simultaneous pressure measurements from the left ventricle (LV) and ascending aorta (AAo) in patients with congenital valvar aortic stenosis was retrospectively reviewed over the past 5 years. The cardiac cycle was standardized for all patients using the percentage of total LV ejection time (ET). Instantaneous gradient at 5% intervals of ET were compared to PPSG using linear regression and Bland‐Altman analysis.ResultsA total of 22 patients underwent catheterization at a median age of 13.7 years (interquartile range [IQR] 10.3‐18.0) and median weight of 51.1 kg (IQR 34.2‐71.6). The PPSG was 46.5 ± 12.6 mm Hg (mean ± SD) and correlated suboptimally with the maximum and mean IPG. The midsystolic IPG (occurring at 50% of ET) had the strongest correlation with the PPSG (PPSG = 0.97(IPG50%)–1.12, R2 = 0.88), while the IPG at 55% of ET was closest to unity (PPSG = 0.997(IPG55%)–1.17, R2 = 0.87).ConclusionsThe commonly measured maximum and mean IPG are suboptimal estimates of the PPSG in congenital aortic stenosis. Using catheter‐based data, IPG at 50%–55% of ejection correlates well with PPSG. This may allow for a more accurate estimation of PPSG via noninvasive assessment of IPG.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/140042/1/chd12514.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/140042/2/chd12514_am.pd

Positional errors in species distribution modelling are not overcome by the coarser grains of analysis

The performance of species distribution models (SDMs) is known to be affected by analysis grain and positional error of species occurrences. Coarsening of the analysis grain has been suggested to compensate for positional errors. Nevertheless, this way of dealing with positional errors has never been thoroughly tested. With increasing use of fine-scale environmental data in SDMs, it is important to test this assumption. Models using fine-scale environmental data are more likely to be negatively affected by positional error as the inaccurate occurrences might easier end up in unsuitable environment. This can result in inappropriate conservation actions. Here, we examined the trade-offs between positional error and analysis grain and provide recommendations for best practice. We generated narrow niche virtual species using environmental variables derived from LiDAR point clouds at 5 x 5 m fine-scale. We simulated the positional error in the range of 5 m to 99 m and evaluated the effects of several spatial grains in the range of 5 m to 500 m. In total, we assessed 49 combinations of positional accuracy and analysis grain. We used three modelling techniques (MaxEnt, BRT and GLM) and evaluated their discrimination ability, niche overlap with virtual species and change in realized niche. We found that model performance decreased with increasing positional error in species occurrences and coarsening of the analysis grain. Most importantly, we showed that coarsening the analysis grain to compensate for positional error did not improve model performance. Our results reject coarsening of the analysis grain as a solution to address the negative effects of positional error on model performance. We recommend fitting models with the finest possible analysis grain and as close to the response grain as possible even when available species occurrences suffer from positional errors. If there are significant positional errors in species occurrences, users are unlikely to benefit from making additional efforts to obtain higher resolution environmental data unless they also minimize the positional errors of species occurrences. Our findings are also applicable to coarse analysis grain, especially for fragmented habitats, and for species with narrow niche breadth