Publications by authors named "J Daniel Young"
Introduction: The gastrointestinal microbiota profoundly influences the health and productivity of animals. This study aimed to characterize microbial community structures of the mouth, gastrointestinal tract (GIT), and feces of cattle.
Methods: Samples were collected from 18 Akaushi crossbred steers at harvest from multiple locations, including the oral cavity, rumen, abomasum, duodenum, jejunum, ileum, cecum, spiral colon, distal colon, and feces.
Objective: The authors compared the performance of a novel self-collect device with clinician-collected samples for detection of high-risk human papillomavirus (hrHPV).
Materials And Methods: Eighty-two (82) participants were recruited from 5 clinical sites in the United States. Each participant performed self-collect sampling using the self-collect device followed by a standard of care clinician-collected sample.
Background: We evaluated letermovir (LTV) for secondary prophylaxis for cytomegalovirus (CMV) in allogeneic hematopoietic cell transplant recipients (HCT) at high-risk for CMV recurrence.
Methods: Open-label study conducted at Memorial Sloan Kettering Cancer Center and the University of Minnesota. Patients with clinically significant CMV infection (cs-CMVi) and ≥1 high-risk criteria for CMV who achieved viral suppression with standard CMV antivirals, received letermovir (LTV) secondary prophylaxis for up to 14 weeks.
Yield validation of dinitrogen reduction reaction (NRR) catalysts with N isotope labeling experiments is frustrated by the high cost of N and the frequent occurrence of NH and NO impurities in commercial N sources. Also, gas diffusion electrode (GDE) cell architectures are relevant to scaling NRR but underexplored and limited by ex situ product analysis methods. To overcome these obstacles, we develop and demonstrate a protocol for NRR catalyst testing using a scalable GDE cell architecture and specialized test station that facilitates in-line product analysis with multiturn time-of-flight mass spectrometry.
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- A mixed integer programming model was developed to prioritize fuel treatments in a fuel break network, aiming to reduce wildfire size and protect Wildland Urban Interface areas.
- The model utilizes simulated wildfire data from a large landscape to inform effective fuel treatment decisions while maintaining computational efficiency and customization options.
- Testing in Southern California showed that the optimization model outperforms traditional rule-based approaches, providing better solutions for fuel break management and planning within a reasonable timeframe.