Publications by authors named "A Forte"

The budding yeast Xrn1 protein shuttles between the nucleus, where it stimulates transcription, and the cytoplasm, where it executes the major cytoplasmic mRNA decay. In the cytoplasm, apart from catalyzing 5'→3' decay onto non translated mRNAs, Xrn1 can follow the last translating ribosome to degrade the decapped mRNA template, a process known as "cotranslational mRNA decay". We have previously observed that the import of Xrn1 to the nucleus is required for efficient cytoplasmic mRNA decay.

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Background: Addressing language barriers through accurate interpretation is crucial for providing quality care and establishing trust. While the ability of artificial intelligence (AI) to translate medical documentation has been studied, its role for patient-provider communication is less explored. This review evaluates AI's effectiveness in clinical translation by assessing accuracy, usability, satisfaction, and feedback on its use.

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Effective pain management is crucial for both comfort and outcomes, yet predicting and managing this pain is difficult. This study aimed to analyze postoperative pain in patients undergoing hand surgery at the Mayo Clinic Florida, examining how patient characteristics and anxiety affect pain outcomes. We conducted a single-arm clinical trial at Mayo Clinic Florida, recruiting patients undergoing hand surgery.

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This study aimed to evaluate the effectiveness of bioactive toothpastes in remineralizing eroded enamel surfaces in vitro. Bovine enamel blocks (n = 48) were obtained and classified into untreated, demineralized, and treated areas. Specimens were randomly classified into six groups (n = 8 each): fluoride-free toothpaste (NCT), Colgate Total 12 (PCT), Sensodyne Repair and Protect (SRP), Sensodyne Pronamel (SPE), Regenerador + Sensitive (RGS), and RGS/calcium booster (RCB).

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Introduction: As artificial intelligence (AI) continues to permeate various sectors, concerns about disparities arising from its deployment have surfaced. AI's effectiveness correlates not only with the algorithm's quality but also with its training data's integrity. This systematic review investigates the racial disparities perpetuated by AI systems across diverse medical domains and the implications of deploying them, particularly in healthcare.

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