Publications by authors named "J F Barry"

Pulsed Field Ablation (PFA) is a new ablation method being rapidly adopted for treatment of atrial fibrillation, which shows advantages in safety and efficiency over radiofrequency and cryo-ablation. In this study, we used an in vivo swine model (10 healthy and 5 with chronic myocardial infarct) for ventricular PFA, collecting intracardiac electrograms, electro-anatomical maps, native T1-weighted and late gadolinium enhancement MRI, gross pathology, and histology. We used 1000-1500 V pulses, with 1-16 pulse trains to vary PFA dose.

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Background: The majority of thyroid nodules are benign; however current guidelines suggest that thyroid incidentalomas should be appropriately evaluated to rule out malignancy.

Aims: This study aims to determine the incidence of thyroid incidentalomas and the likelihood that they harbour sinister pathology in the largest Irish cohort studied to-date.

Methods: A retrospective observational chart review was conducted using data from July 2018 to December 2018 using the Radiology Database in use at Cork University Hospital.

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Objective: We aimed to quantify and predict lacosamide exposure during pregnancy by developing a pregnancy physiologically-based pharmacokinetic model, allowing the prediction of potential dose increases to support maintaining a patient's preconception lacosamide concentrations.

Methods: Models for nonpregnant adults and pregnant female patients were constructed using physiochemical and pharmacological parameters identified from literature review. Evaluation of plasma concentration data from human males was digitized from the literature.

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Article Synopsis
  • Artificial intelligence (AI) is increasingly being used in healthcare, particularly in neonatal intensive care units (NICUs), where large data sets can improve the diagnosis and treatment of conditions like sepsis and bronchopulmonary dysplasia.
  • The article discusses various machine learning (ML) models, their development process, and the need for a standardized framework to evaluate their performance in clinical settings, emphasizing how this understanding is key for effective implementation.
  • Challenges such as ensuring model generalizability, ethical issues, and the importance of regular performance monitoring are highlighted, along with future directions calling for collaboration and equitable access to AI technologies in healthcare.
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RNA interference is a natural antiviral mechanism that could be harnessed to combat SARS-CoV-2 infection by targeting and destroying the viral RNA. We identified potent lipophilic small interfering RNA (siRNA) conjugates targeting highly conserved regions of SARS-CoV-2 outside of the spike-encoding region capable of achieving ≥3-log viral reduction. Serial passaging studies demonstrated that a two-siRNA combination prevented development of resistance compared to a single siRNA approach.

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