Publications by authors named "K C Cuneo"

Purpose: Electrodiagnostic (EDX) testing is commonly used in conjunction with symptoms and physical examination findings to diagnose cubital tunnel syndrome (CuTS). The purpose of this study was to investigate the relationship between preoperative EDX diagnosis and the degree of Disabilities of the Arm, Shoulder, and Hand (DASH) improvement after surgery within the CuTS patient population.

Methods: A retrospective review was designed to analyze patients from a single institution who underwent a cubital tunnel release.

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End-stage liver disease is marked by portal hypertension, systemic elevations in ammonia, and development of hepatocellular carcinoma (HCC). While these clinical consequences of cirrhosis are well described, it remains poorly understood whether hepatic insufficiency and the accompanying elevations in ammonia contribute to HCC carcinogenesis. Using preclinical models, we discovered that ammonia entered the cell through the transporter SLC4A11 and served as a nitrogen source for amino acid and nucleotide biosynthesis.

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Up to 10% of patients with locally advanced rectal cancer will experience locoregional recurrence. In the setting of prior surgery and often radiation and chemotherapy, these represent uniquely challenging cases. When feasible, surgical resection offers the best chance for oncologic control yet risks significant morbidity.

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Functional liver parenchyma can be damaged from treatment of liver malignancies with Y selective internal radiation therapy (SIRT). Evaluating functional parenchymal changes and developing an absorbed dose (AD)-toxicity model can assist the clinical management of patients receiving SIRT. We aimed to determine whether there is a correlation between Y PET AD voxel maps and spatial changes in the nontumoral liver (NTL) function derived from dynamic gadoxetic acid-enhanced MRI before and after SIRT.

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Background: Adaptive treatment strategies that can dynamically react to individual cancer progression can provide effective personalized care. Longitudinal multi-omics information, paired with an artificially intelligent clinical decision support system (AI-CDSS) can assist clinicians in determining optimal therapeutic options and treatment adaptations. However, AI-CDSS is not perfectly accurate, as such, clinicians' over/under reliance on AI may lead to unintended consequences, ultimately failing to develop optimal strategies.

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