Oxygenation in the rabbit myocardium: assessment with susceptibility-dependent MR imaging

PURPOSE: To determine the feasibility of using hemoglobin (Hb) desaturation as an indicator of myocardial oxygenation. MATERIALS AND METHODS: High-resolution gradient-echo nuclear magnetic resonance (MR) images of isolated, blood-perfused rabbit hearts were obtained at various blood oxygenation levels. The hearts were perfused at 37 degrees C with a Langendorff apparatus modified for nuclear MR imaging. The perfusate contained bovine red blood cells in a cardioplegic solution that eliminated motion artifacts and minimized arteriovenous oxygenation differences. Hb saturation was varied (7%-100%) randomly. Perfusion pressure was continuously monitored, and blood samples were obtained. RESULTS: There was a substantial correlation between image signal intensity in the myocardium and Hb saturation in the blood, believed to be due to susceptibility effects of the paramagnetic species deoxyhemoglobin. CONCLUSION: Direct and noninvasive determination of regional Hb saturation with susceptibility-dependent MR imaging may provide information regarding regional myocardial O2 content.     

Effect of the sulfonylurea glyburide on glycogen synthase activity in alloxan-induced diabetic rat adipocytes

1. The effect of glyburide (glibenclamide) treatment in vivo on the adipose tissue glycogen synthase activity of type II diabetic rats has been studied. 2. Three week treatment of diabetic animals with glyburide (5 mg/kg orally, in saline) increased adipose glycogen synthase activity and decreased blood glucose levels. 3. These results demonstrate that the sulfonylurea glyburide is capable of exerting direct insulin-like effect on adipose glycogen-synthase activity of type II diabetic rats in vivo.     

Ensemble of multiple instance classifiers for image re-ranking

Text-based image retrieval may perform poorly due to the irrelevant and/or incomplete text surrounding the images in the web pages. In such situations, visual content of the images can be leveraged to improve the image ranking performance. In this paper, we look into this problem of image re-ranking and propose a system that automatically constructs multiple candidate “multi-instance bags (MI-bags)”, which are likely to contain relevant images. These automatically constructed bags are then utilized by ensembles of Multiple Instance Learning (MIL) classifiers and the images are re-ranked according to the final classification responses. Our method is unsupervised in the sense that, the only input to the system is the text query itself, without any user feedback or annotation. The experimental results demonstrate that constructing multiple instance bags based on the retrieval order and utilizing ensembles of MIL classifiers greatly enhance the retrieval performance, achieving on par or better results compared to the state-of-the-art.     

Graphene oxide-containing isocyanate-based polyimide foams: Enhanced thermal stability and flame retardancy

Isocyanate-based graphene oxide-containing polyimide foams were synthesized by a semi-prepolymer method. In this method, while the first solution containing pre-polymer was derived from pyromellitic dianhydride and excess polymethylene polyphenylene isocyanate (PM200), the second solution contains dianhydride derivatives, water, catalysts, surfactants, and graphene oxide. PIFs were prepared with 0%, 0.25%, 0.50%, 0.75%, and 1% graphene oxide by weight, respectively. PIFs exhibited a minimum side reaction and urea generation was not seen for all PIFs instead of imide bonding. The addition of graphene oxide (GO) leads to a more close-packed structure. Therefore, crosslinking density and thermal stability of graphene oxide-containing polyimide foams increased. Upon the addition of 1% GO, almost seven times higher compression strength was obtained compared to neat PIFs. Also, LOI values supported the theory that thermally stable and flame retardant PIFs can be synthesized via the isocyanate-based process with GO.     

Use of center of gravity with the common vector approach in isolated word recognition

In this paper, the subspace based classifier, common vector approach (CVA), with the center of gravity (COG) method is used for isolated word recognition. Since the CVA classifier is sensitive to shifts through the time axis, endpoint detection becomes extremely important for the recognition of isolated words. The COG method eliminates the need for endpoint detection. The effects of the COG method and a classical endpoint detection algorithm on the recognition rates of isolated words are investigated. The experimental results show that the COG method yields slightly higher recognition rates than the endpoint detection method in the TI-digit database when CVA is used.     

Design optimization of an enzymatic assay in an electrokinetically-driven microfluidic device

Microfluidic systems are increasingly popular for rapid and cheap determinations of enzyme assays and other biochemical analysis. In this study reduced order models (ROM) were developed for the optimization of enzymatic assays performed in a microchip. The model enzyme assay used was β-galactosidase (β-Gal) that catalyzes the conversion of Resorufin β-d-galactopyranoside (RBG) to a fluorescent product as previously reported by Hadd et al. (Anal Chem 69(17): 3407–3412, 1997). The assay was implemented in a microfluidic device as a continuous flow system controlled electrokinetically and with a fluorescence detection device. The results from ROM agreed well with both computational fluid dynamic (CFD) simulations and experimental values. While the CFD model allowed for assessment of local transport phenomena, the CPU time was significantly reduced by the ROM approach. The operational parameters of the assay were optimized using the validated ROM to significantly reduce the amount of reagents consumed and the total biochip assay time. After optimization the analysis time would be reduced from 20 to 5.25 min which would also resulted in 50% reduction in reagent consumption.     

Quadrilateral meshes with provable angle bounds

In this paper, we present an algorithm that utilizes a quadtree data structure to construct a quadrilateral mesh for a simple polygonal region in which no newly created angle is smaller than 18.43^° (=arctan(\frac13)){{18.43}}^{\circ} ({=}\hbox{arctan}(\frac{1}{3})) or greater than 171.86^° (=135^° + 2arctan(\frac13)){{171.86}}^{\circ} ({=}{{135}}^{\circ} + 2\hbox{arctan}(\frac{1}{3})). This is the first known result, to the best of our knowledge, on a direct quadrilateral mesh generation algorithm with a provable guarantee on the angles.     

Sodium and ultrafiltration profiling in hemodialysis: A long-forgotten issue revisited

Sodium and ultrafiltration profiling are method of dialysis in which dialysate sodium concentration and ultrafiltration rate are altered during the course of the dialysis session. Sodium and ultrafiltration profiling have been used, commonly simultaneously, to improve hemodynamic stability during hemodialysis. Sodium profiling is particularly effective in decreasing the incidence of intradialytic hypotension, while ultrafiltration profiling is suggested to decrease subclinical repeated end organ ischemia during dialysis. However, complications such as increased interdialytic weight gain and thirst due to sodium excess have prevented widespread use of sodium profiling. Evidence suggest that different sodium profiling techniques may lead to different clinical results, and preferring sodium balance neutral sodium profiling may mitigate adverse effects related to sodium overload. However, evidence is lacking on the long-term clinical outcomes of different sodium profiling methods. Optimal method of sodium profiling as well as the utility of sodium/ultrafiltration profiling in routine practice await further clinical investigation.     

A three-way clusterwise multidimensional unfolding procedure for the spatial representation of context dependent preferences

Various deterministic and latent structure approaches for combining forms of multidimensional scaling and cluster analysis have been previously discussed. A new clusterwise three-way unfolding methodology for the analysis of two-way or three-way metric dominance/preference data is proposed. The purpose of this proposed methodology is to simultaneously estimate a joint space of stimuli and cluster ideal point representations, as well as the clusters themselves, such that the geometry underlying the clusterwise model renders some indication of the underlying structure in the data. In the three-way case, it is shown how multiple ideal points can represent preference change over contexts or situations. Partitions, overlapping clusters, stationary and context dependent preference representations are allowed. After a literature review of related methodological research, the technical details of the proposed three-way clusterwise spatial unfolding model are presented in terms of modeling context/situational dependent preferences (i.e., preferences for various stimuli collected over the same set of subjects over time, situation, etc.). The psychological basis for the models is provided in terms of the extensive behavioral decision theory and consumer psychology literature on contextual preferences and situational effects. An application to a data set exploring preferences for breakfast/snack food data over a number of different usage situations is then presented, followed by a discussion on future potential research directions.