Publications by authors named "M E Hammer"
Background: Oncology nurses frequently contend with intense work-related emotions stemming from their roles, which include bearing witness to suffering, managing end-of-life care, and navigating ethical dilemmas. These emotional challenges can lead to burnout, compassion fatigue, and overall psychological distress.
Objective: To determine the feasibility, acceptability, and preliminary effect of implementing Storytelling Through Music (STM) online with oncology nurses.
Key innovations, traits that provide species access to novel niches, are thought to be a major generator of biodiversity. One commonly cited example of key innovation is pharyngognathy, a set of modifications to the pharyngeal jaws found in some highly species-rich fish clades such as cichlids and wrasses. Here, using comparative phylogenomics and phylogenetic comparative methods, we investigate the genomic basis of pharyngognathy and the impact of this innovation on diversification.
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- - The study examines how a monoclonal antibody (bevacizumab) interacts with silicone oils and hydrogels, revealing that exposure to silicone oils significantly decreases the antibody's functionality and causes aggregation.
- - Results show that after 24 hours in silicone oil, bevacizumab retains only 30% of its activity, leading to concerns about its clinical use during procedures that involve silicone oil tamponade.
- - Polysorbate, a common stabilizer, effectively reduces antibody aggregation, while hydrogels do not affect the functionality of the antibodies tested, making them a safer alternative for vitreous body replacement.
Workers regularly using vibrating hand tools may develop a disorder referred to as hand-arm vibration syndrome (HAVS). HAVS is characterized by cold-induced vasospasms in the hands and fingers that result in blanching of the skin, loss of sensory function, pain, and reductions in manual dexterity. Exposure to vibration induces some of these symptoms.
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- The study investigates phenotypic heterogeneity in patients with SCN8A variants, which causes a range of conditions from developmental delays to severe epileptic disorders.
- Researchers used machine learning to identify potential subgroups (U1-U3) based on developmental and seizure onset characteristics.
- Findings suggest that U1 and U2 have delayed and distinct seizure-onset patterns, while U3 patients experience simultaneous delays and seizures, impacting treatment responses and developmental outcomes.