Chronic and acute kidney injury are on the rise due to increased use of prescription drugs3,4,5. While roughly 25% of acute renal failure is drug induced4, predicting nephrotoxicity in preclinical in vitro human models or animal studies remains difficult. Currently, renal toxicity accounts for ...
(B) Tumor cells in a major vessel of the kidney at week 6. Note infiltration of tumor cells into kidney parenchyma (arrowhead, left panel). (C) Tumor-laden adrenal gland at 6 weeks with multiple spherically-shaped metastases. (D) Large metastasis on the surface of the liver at week 6....
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Modulation of reconstituted pig kidney Na+/K+-ATPase activity by cholesterol in endogenous lipid vesicles: role of lipid domains Biochemistry, 45 (2006), pp. 13855-13868 CrossrefView in ScopusGoogle Scholar [66] B. Cannon, M. Hermansson, S. Gyorke, P. Somerharju, J.A. Virtanen, K.H....
kidney tumor segmentationKiTSAN-NetMTANsemi-supervised learningSEMANTIC SEGMENTATIONU-NETBACKGROUND: Medical image segmentation is crucial in disease diagnosis and treatment planning. Deep learning (DL) techniques have shown promise. However, optimizing DL models requires setting numerous parameters, and ...
ability to investigate the evolution of this phenotype in a progressive manner. We describe the development of a new canine kidney cell line, CKB1-3T7, which permits a prospective investigation of emerging neoplastic events in vitro and overcomes many of the limitations of earlier studies. We ...
Briefly, spot slides were prepared by incubating virus in Green Monkey Kidney cells for 8-10 days. At signs of discrete cytopathic effects (CPE), cells were removed from the flask with a rubber policeman and applied onto microscope slides, air dried, fixed in cold (4° C.) acetone and ...
In recent years, exploring natural compounds with functional properties to ameliorate aging-associated cognitive decline has become a research priority to
Using the integrated clusters as labeled data, deep learning models to classify the tiles into pathological findings were created by transfer-learning the feature extractors. We developed three models for different magnifications. Using these extracted findings, our model was able to predict the ...
fibrillation and chronic kidney disease, and less likely to have hypertension, obesity, diabetes, and coronary artery disease. The total number of healthcare encounters and total duration of diagnostic history information in the datasets were similar across Cohorts 1–4 (IQVIA and Optum). The NME...