Background: Preventative medication (PM) uptake is low among patients at an elevated risk of breast cancer, largely due to fears of intolerance. This study aimed to investigate whether a new, surgical advanced practice provider (APP)-run clinic was effectively prescribing PM. We hypothesized equivalent rates of PM uptake compared to consultation with medical oncologists (MD).
View Article and Find Full Text PDFBackground: The WHO states that antivenom is the only safe and effective treatment to neutralize snake venom. Snakebite antivenom typically involves horse hyperimmunization with crude venom and Freund's adjuvant.
Methods: In the current work, we analyzed the ascorbyl palmitate liquid crystal structure with snake protein or PLA2, the carrier charge capacity, and we evaluated the immune response induced by the enzyme P9a(Cdt-PLA2) formulated in a nanostructure using CpG-ODN, determining the titer of IgG antibodies.
Introduction: Secondary forests and coffee cultivation systems with shade trees might have great potential for carbon sequestration as a means of climate change adaptation and mitigation. This study aimed to measure carbon stocks in coffee plantations under different managements and secondary forest systems in the Peruvian Amazon rainforest (San Martín Region).
Methods: The carbon stock in secondary forest trees was estimated using allometric equations, while carbon stocks in soil, herbaceous biomass, and leaf litter were determined through sampling and laboratory analysis.
The antiferromagnetic structure of Yb_{3}Ga_{5}O_{12} is identified by neutron diffraction experiments below the previously known transition at T_{λ}=54 mK. The magnetic propagation vector is found to be k=(1/2,1/2,0), an unusual wave vector in the garnet structure. The associated complex magnetic structure highlights the role of exchange interactions in a nearly isotropic system dominated by dipolar interactions and finds echoes with exotic structures theoretically proposed.
View Article and Find Full Text PDFBackground: The identification of predictors of treatment response is crucial for improving treatment outcome for children with anxiety disorders. Machine learning methods provide opportunities to identify combinations of factors that contribute to risk prediction models.
Methods: A machine learning approach was applied to predict anxiety disorder remission in a large sample of 2114 anxious youth (5-18 years).