Nephrolithiasis is common, affecting up to 10% of the population. Symptomatic stone episodes produce significant pain and suffering, as well as great individual and societal economic costs. Much effort has been directed towards understanding metabolic abnormalities that can increase urinary supersaturation, which is clearly one key factor that initiates and favors stone growth. However, crystal-crystal and crystal-cell interactions also appear to be critical events during the early stages of stone formation. Therefore, increased understanding of the factors that modulate the interface of urinary proteins and crystals, and hence their subsequent interaction with other crystals or cells, is a necessary prerequisite for identifying new therapeutic targets. Such knowledge will in turn enable development of new strategies for the treatment and prevention of renal stone disease. Therefore, the urinary phenotyping core will serve 4 key functions in support of this Urology O'Brien Center: 1) Quantification of urinary components of the supersaturation profile 2) Quantification of urinary inhibitor activity 3) Renal biopsy processing, including staining of sections, and quantification of calcifications 3) Biobanking of urine, blood, renal tissues, and stones The Urinary Phenotyping Core will directly support Projects 2 and 3, and it will likely be of value for pilot projects initiated during the Center's activities that require biobanked samples or urinary assays.
The Urinary Phenotyping Core will coordinate measurement of all urine parameters that influence kidney stone formation including supersaturation profiles, quantitative crystallization assays, and maintain the biobank of these fully phenotyped patients.
|Ferrero, A; Gutjahr, R; Henning, A et al. (2017) Renal Stone Characterization using High Resolution Imaging Mode on a Photon Counting Detector CT System. Proc SPIE Int Soc Opt Eng 10132:|
|Huang, Alice E; Montoya, Juan C; Shiung, Maria et al. (2017) Consistency of Renal Stone Volume Measurements Across CT Scanner Model and Reconstruction Algorithm Configurations. AJR Am J Roentgenol 209:116-121|
|Perinpam, Majuran; Enders, Felicity T; Mara, Kristin C et al. (2017) Plasma oxalate in relation to eGFR in patients with primary hyperoxaluria, enteric hyperoxaluria and urinary stone disease. Clin Biochem 50:1014-1019|
|Rossano, Adam J; Romero, Michael F (2017) Optical Quantification of Intracellular pH in Drosophila melanogaster Malpighian Tubule Epithelia with a Fluorescent Genetically-encoded pH Indicator. J Vis Exp :|
|Lieske, John C (2017) Probiotics for prevention of urinary stones. Ann Transl Med 5:29|
|Ferrero, Andrea; Chen, Baiyu; Li, Zhoubo et al. (2017) Technical Note: Insertion of digital lesions in the projection domain for dual-source, dual-energy CT. Med Phys 44:1655-1660|
|Pottel, Hans; Dubourg, Laurence; Schaeffner, Elke et al. (2017) Data on the relation between renal biomarkers and measured glomerular filtration rate. Data Brief 14:763-772|
|Kittanamongkolchai, Wonngarm; Mara, Kristin C; Mehta, Ramila A et al. (2017) Risk of Hypertension among First-Time Symptomatic Kidney Stone Formers. Clin J Am Soc Nephrol 12:476-482|
|Gutjahr, R; Polster, C; Henning, A et al. (2017) Dual Energy CT Kidney Stone Differentiation in Photon Counting Computed Tomography. Proc SPIE Int Soc Opt Eng 10132:|
|Canales, Benjamin K; Smith, Jennifer A; Weiner, I David et al. (2017) Polymorphisms in Renal Ammonia Metabolism Genes Correlate With 24-Hour Urine pH. Kidney Int Rep 2:1111-1121|
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