Publications by authors named "N Meyers"

Objective: Using health literacy informed communication strategies can mitigate health inequities. Despite the high prevalence of limited health literacy among parents and children, pediatricians infrequently use clear communication techniques and further education is imperative. There is minimal literature exploring health literacy curricula in pediatric residencies.

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Computational models are complex scientific constructs that have become essential for us to better understand the world. Many models are valuable for peers within and beyond disciplinary boundaries. However, there are no widely agreed-upon standards for sharing models.

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Peripheral nerve damage can cause debilitating symptoms ranging from numbness and pain to sensory loss and atrophy. To uncover the underlying mechanisms of peripheral nerve injury, our research aims to develop a relationship between biomechanical peripheral nerve damage and function through finite element modeling. A noncontact, ex vivo electrophysiology chamber, capable of axially stretching explanted nerves while recording electrical signals, was used to investigate peripheral nerve injury.

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Article Synopsis
  • The study highlights the challenges in accurately analyzing microplastics in marine environments, particularly regarding smaller sizes and the effects of environmental weathering on plastic reliability.
  • It tests two automated analysis techniques—decision tree (DT) and random forest (RF)—that use machine learning and fluorescent staining to improve detection and identification of various weathered microplastic types.
  • While both models showed high accuracy for pristine plastics, RF models outperformed in distinguishing weathered microplastics, though results varied by lab, indicating the method's adaptability for future research.
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Microplastic (MP) research faces challenges due to costly, time-consuming, and error-prone analysis techniques. Additionally, the variability in data quality across studies limits their comparability. This study addresses the critical need for reliable and cost-effective MP analysis methods through validation of a semi-automated workflow, where environmentally relevant MP were spiked into and recovered from marine fish gastrointestinal tracts (GITs) and blue mussel tissue, using Nile red staining and machine learning automated analysis of different polymers.

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