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Two observational studies were conducted to support an initiative to qualify translational kidney safety biomarkers as clinical drug development tools that identify tubular injury prior to changes in estimated glomerular filtration rate (eGFR). Normal healthy volunteers provided three morning spot urine collections over 4 weeks. Patients undergoing surgical resection and intrathoracic cisplatin for malignant pleural mesothelioma provided urine samples pre- and postoperatively at 4, 8, and 12 hours and daily for 6 days.

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Background: Adult people with cystic fibrosis (PwCF) have a higher risk of end-stage kidney disease than the general population. The nature and mechanism of kidney disease in CF are unknown. This study quantifies urinary kidney injury markers and examines the hypothesis that neutrophil activation and lung infection are associated with early kidney injury in CF.

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The role of the intrarenal renin-angiotensin system (iRAS) in diabetic kidney disease (DKD) progression remains unclear. In this study, we generated mice with renal tubule-specific deletion of angiotensinogen (Agt; RT-Agt-/-) in both Akita and streptozotocin (STZ)-induced mouse model of diabetes. Both Akita RT-Agt-/- and STZ-RT-Agt-/- mice exhibited significant attenuation of glomerular hyperfiltration, urinary albumin/creatinine ratio, glomerulomegaly and tubular injury.

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Objective: Acute kidney injury (AKI) is a frequent complication in critically ill patients, affecting up to 50% of patients in the intensive care units. The lack of standardized and open-source tools for applying the Kidney Disease Improving Global Outcomes (KDIGO) criteria to time series, requires researchers to implement classification algorithms of their own which is resource intensive and might impact study quality by introducing different interpretations of edge cases. This project introduces pyAKI, an open-source pipeline addressing this gap by providing a comprehensive solution for consistent KDIGO criteria implementation.

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