Background And Objectives: Despite growing interest in how patient frailty affects outcomes (eg, in neuro-oncology), its role after transsphenoidal surgery for Cushing disease (CD) remains unclear. We evaluated the effect of frailty on CD outcomes using the Registry of Adenomas of the Pituitary and Related Disorders (RAPID) data set from a collaboration of US academic pituitary centers.
Methods: Data on consecutive surgically treated patients with CD (2011-2023) were compiled using the 11-factor modified frailty index.
Integrating multi-omics data may help researchers understand the genetic underpinnings of complex traits and diseases. However, the best ways to integrate multi-omics data and use them to address pressing scientific questions remain a challenge. One important and topical problem is how to assess the aggregate effect of multiple genomic data types (e.
View Article and Find Full Text PDFPhenotypic plasticity can represent a vital adaptive response to environmental stressors, including those associated with climate change. Despite its evolutionary advantages, the expression of plasticity varies significantly within and among species, and is likely to be influenced by local environmental conditions. This variability in plasticity has important implications for evolutionary biology and conservation physiology.
View Article and Find Full Text PDFThe burden of cancer remains elevated for American Indian/Alaska Natives (AI/AN) in the United States, particularly urban communities. Urban Indian Organizations (UIOs) are part of the Indian health care system for urban AI/AN populations to receive culturally competent care; therefore, it is important that UIOs convey the importance of cancer preventive and treatment options through their websites. The purpose of this study was to utilize the Indian Health Service (IHS) Office of Urban Indian Health Programs' official website to identify, analyze, and describe IHS funded UIOs offering cancer-related services.
View Article and Find Full Text PDFNovel multiplexed spatial proteomics imaging platforms expose the spatial architecture of cells in the tumor microenvironment (TME). The diverse cell population in the TME, including its spatial context, has been shown to have important clinical implications, correlating with disease prognosis and treatment response. The accelerating implementation of spatial proteomic technologies motivates new statistical models to test if cell-level images associate with patient-level endpoints.
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