Ultrasound Methods for Quantitative Edema Monitoring

Patients with end stage renal disease typically must undergo regular dialysis treatments to replace the loss of kidney function. A critical part of these dialysis treatments is the careful management of fluid status, as these patients are at an increased risk for developing fluid overload, a condition that poses a number of dangers to their health and quality of life. Current clinical methods are lacking in their ability to accurately provide a quantitative metric for grading edema and fluid overload. In this dissertation, I explore a number of methods based on ultrasound strain imaging, ultrasound viscoelastography, and ultrasound poroelastography to address this clinical need. The practical and theoretical aspects of the measurement process and parameter estimation methods are explored, and new methods are proposed and evaluated to overcome common difficulties. Chiefly, the experiments and simulations described in this work aim to highlight the role of assumptions in visco- and poroelastic imaging, to explore how these assumptions can hinder accurate parameter estimation, and to develop methods that are less assumption-dependent. First, I evaluate a point-of-care ultrasound viscoelastography system and use it to estimate the viscoelastic properties of a tissue-mimicking material. The strain and material properties are observed to be depth dependent, highlighting possible breaks with the viscoelastic model assumptions and possible poroelastic behavior. Next, I analyze the role of model assumptions on poroelastography measurements using both finite element models and benchtop experiments. Strain magnitudes and loading geometries that differ from the model assumptions used in most poroelastography studies are shown to produce large differences in poroelastic parameter estimates. Furthermore, they can lead to lateral-to-axial strain ratio measurements that do not converge to the true Poisson's ratio of the material, thus highlighting the need for more careful interpretation of standard effective Poisson's ratio (EPR) poroelastograms. Finally, I develop and evaluate a new approach to poroelastography by posing the poroelastic imaging as an inverse problem. This allows for the quantitative imaging of spatial variations. This method is shown to produce more accurate poroelastic images in simulations with ideal, Gaussian corrupted data. In addition, the method shows promise in reconstructions based on simulated ultrasound images, though some difficulties remain. Possible improvements and recommendations for future poroelastography studies are discussed.PHDBiomedical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/136977/1/jpitre_1.pd

Progesterone metabolites regulate induction, growth, and suppression of estrogen- and progesterone receptor-negative human breast cell tumors

INTRODUCTION: Of the nearly 1.4 million new cases of breast cancer diagnosed each year, a large proportion is characterized as hormone receptor negative, lacking estrogen receptors (ER) and/or progesterone receptors (PR). Patients with receptor-negative tumors do not respond to current steroid hormone-based therapies and generally have significantly higher risk of recurrence and mortality compared with patients with tumors that are ER- and/or PR-positive. Previous in vitro studies had shown that the progesterone metabolites, 5α-dihydroprogesterone (5αP) and 3α-dihydroprogesterone (3αHP), respectively, exhibit procancer and anticancer effects on receptor-negative human breast cell lines. Here in vivo studies were conducted to investigate the ability of 5αP and 3αHP to control initiation, growth, and regression of ER/PR-negative human breast cell tumors. METHODS: ER/PR-negative human breast cells (MDA-MB-231) were implanted into mammary fat pads of immunosuppressed mice, and the effects of 5αP and 3αHP treatments on tumor initiation, growth, suppression/regression, and histopathology were assessed in five separate experiments. Specific radioimmunoassays and gas chromatography-mass spectrometry were used to measure 5αP, 3αHP, and progesterone in mouse serum and tumors. RESULTS: Onset and growth of ER/PR-negative human breast cell tumors were significantly stimulated by 5αP and inhibited by 3αHP. When both hormones were applied simultaneously, the stimulatory effects of 5αP were abrogated by the inhibitory effects of 3αHP and vice versa. Treatment with 3αHP subsequent to 5αP-induced tumor initiation resulted in suppression of further tumorigenesis and regression of existing tumors. The levels of 5αP in tumors, regardless of treatment, were about 10-fold higher than the levels of 3αHP, and the 5αP:3αHP ratios were about fivefold higher than in serum, indicating significant changes in endogenous synthesis of these hormones in tumorous breast tissues. CONCLUSIONS: The studies showed that estrogen/progesterone-insensitive breast tumors are sensitive to, and controlled by, the progesterone metabolites 5αP and 3αHP. Tumorigenesis of ER/PR-negative breast cells is significantly enhanced by 5αP and suppressed by 3αHP, the outcome depending on the relative concentrations of these two hormones in the microenvironment in the breast regions. The findings show that the production of 5αP greatly exceeds that of 3αHP in ER/PR-negative tumors and that treatment with 3αHP can effectively block tumorigenesis and cause existing tumors to regress. The results provide the first hormonal theory to explain tumorigenesis of ER/PR-negative breast tissues and support the hypothesis that a high 3αHP-to-5αP concentration ratio in the microenvironment may foster normalcy in noncancerous breast regions. The findings suggest new diagnostics based on the relative levels of these hormones and new approaches to prevention and treatment of breast cancers based on regulating the levels and action mechanisms of anti- and pro-cancer progesterone metabolites

Serial team teaching and the evolving scholarship of learning: Students’ perspective

Faculty and students at the University of Toronto were surveyed and interviewed to form a case study of serial team teaching, in which multiple instructors take turns teaching a segment of the same course in sequence. Student opinions ranged from slightly opposed to slightly in favour of team teaching overall. When asked about specific aspects of team teaching, students who liked it overall tended to like all aspects of it, and did not identify those disadvantages in student experience anticipated by the faculty. In general, students in upper years were less supportive of team teaching than were students in their first and second years

Prediction of human-Bacillus anthracis protein–protein interactions using multi-layer neural network

Triplet amino acids have successfully been included in feature selection to predict human-HPV protein-protein interactions (PPI). The utility of supervised learning methods is curtailed due to experimental data not being available in sufficient quantities. Improvements in machine learning techniques and features selection will enhance the study of PPI between host and pathogen.We present a comparison of a neural network model versus SVM for prediction of hostpathogen PPI based on a combination of features including: amino acid quadruplets, pairwise sequence similarity, and human interactome properties. The neural network and SVM were implemented using Python Sklearn library. The neural network model using quadruplet features and other network features outperformance the SVM model. The models are tested against published predictors and then applied to the human-B.anthracis case. Gene ontology term enrichment analysis identifies immunology response and regulation as functions of interacting proteins. For prediction of Human-viral PPI, our model (neural network) is a significant improvement in overall performance compared to a predictor using the triplets feature and achieves a good accuracy in predicting human-B.anthracis PPI

Future Fitness of Female Insect Pests in Temporally Stable and Unstable Habitats and Its Impact on Habitat Utility as Refuges for Insect Resistance Management

The long-term fitness of individuals is examined in complex and temporally dynamic ecosystems. We call this multigeneration fitness measure “future fitness”. Helicoverpa zea (Boddie) (Lepidoptera: Noctuidae) is a polyphagous insect that feeds on many wild and cultivated hosts. While four generations of H. zea occur during the cropping season in the U.S. Mid Southern agroecosysem, the latter two generations were of most interest, as corn (which has been largely nontransgenic in the Mid-South) dominates the first two generations in the cropping system. In simulations of the evolution of resistance to Bt-transgenic crops, cotton refuge areas were found to be significantly more effective than similar soybean acreages at delaying the evolution of resistance. Cotton is a suitable host for H. zea during two late summer generations, while a soybean field is suitable for only one of these generations, therefore soybean fields of other maturity groups were simulated as being attractive during the alternative generation. A hypothetical soybean variety was tested in which a single field would be attractive over both generations and it was found to be significantly more effective at delaying resistance than simulated conventional soybean varieties. Finally, the placement of individuals emerging at the start of the 3rd (first without corn) generation was simulated in either refuge cotton, conventional soybean and the hypothetical long attractive soybean and the mean number of offspring produced was measured at the end of the season. Although females in conventional and long soybean crops had the same expected fecundity, because of differences in temporal stability of the two crops, the long soybean simulations had significantly more H. zea individuals at the end of the season than the conventional soybean simulations. These simulations demonstrate that the long-term fecundity associated with an individual is dependent not only on the fecundity of that individual in its current habitat, but also the temporal stability of habitats, the ecosystem at large and the likelihood that the individual's offspring will move into different habitats

Metabolic engineering of novel lignin in biomass crops

Lignin, a phenolic polymer in the secondary wall, is the major cause of lignocellulosic biomass recalcitrance to efficient industrial processing. From an applications perspective, it is desirable that second-generation bioenergy crops have lignin that is readily degraded by chemical pretreatments but still fulfill its biological role in plants. Because plants can tolerate large variations in lignin composition, often without apparent adverse effects, substitution of some fraction of the traditional monolignols by alternative monomers through genetic engineering is a promising strategy to tailor lignin in bioenergy crops. However, successful engineering of lignin incorporating alternative monomers requires knowledge about phenolic metabolism in plants and about the coupling properties of these alternative monomers. Here, we review the current knowledge about lignin biosynthesis and the pathways towards the main phenolic classes. In addition, the minimal requirements are defined for molecules that, upon incorporation into the lignin polymer, make the latter more susceptible to biomass pretreatment. Numerous metabolites made by plants meet these requirements, and several have already been tested as monolignol substitutes in biomimetic systems. Finally, the status of detection and identification of compounds by phenolic profiling is discussed, as phenolic profiling serves in pathway elucidation and for the detection of incorporation of alternative lignin monomers

Pharmacokinetics of ibuprofen in man IV: Absorption and disposition

Fifteen normal male volunters received 400, 800, and 1200 mg doses of ibuprofen as 1, 2, or 3 tablets, respectively, in crossover fashion, then 420 mg in solution form during the fourth week. Plasma concentration of ibuprofen was measured by an HPLC method. Individual subject concentration-time (C,t) data following the solution were analyzed by two different methods, and results unequivocally indicated the open two compartment model with first order absorption. However, the computer fitting of both arithmetic and geometric mean concentrations led to a different model. A method was developed to obtain absorption data (fraction of drug absorbed , F a , versus time) for a multicompartmental system from oral data alone, without intravenous data. The method assumes that V p is constant intrasubject and that absorption is complete following administration of both the solution and tablets. The method was successfully applied to the ibuprofen tablet data. It was shown also that such a method is necessary to obtain ibuprofen absorption data since intrasubject variation of the microscopic rate constants k 12 , k a21 , and k el ( as reflected by the intrasubject variation of the hybrid rate parameters λ 1 and λ 2 or Β and a) is of the same order of magnitude as intersubject variation. Absorption of ibuprofen from tablets was shown not to be simple first order as for the solution. The absorption profiles following one tablet were S- shaped, while those following 2 or 3 tablets had partial linear segments indicating zero order absorption .Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/45032/1/10928_2005_Article_BF01062664.pd