Publications by authors named "R H Sample"

Animal activity reflects behavioral decisions that depend upon environmental context. Prior studies typically estimated activity distributions within few areas, which has limited quantitative assessment of activity changes across environmental gradients. We examined relationships between two response variables, activity level (fraction of each day spent active) and pattern (distribution of activity across a diel cycle) of white-tailed deer (Odocoileus virginianus), with four predictors-deer density, anthropogenic development, and food availability from woody twigs and agriculture.

View Article and Find Full Text PDF

The pre-mRNA life cycle requires intron processing; yet, how intron-processing defects influence splicing and gene expression is unclear. Here, we find that TTDN1/MPLKIP, which is encoded by a gene implicated in non-photosensitive trichothiodystrophy (NP-TTD), functionally links intron lariat processing to spliceosomal function. The conserved TTDN1 C-terminal region directly binds lariat debranching enzyme DBR1, whereas its N-terminal intrinsically disordered region (IDR) binds the intron-binding complex (IBC).

View Article and Find Full Text PDF

Epithelial-to-mesenchymal transition (EMT) is a process by which cells lose their epithelial characteristics and gain mesenchymal phenotypes. In cancer, EMT is thought to drive tumor invasion and metastasis. Recent efforts to understand EMT biology have uncovered that cells undergoing EMT attain a spectrum of intermediate "hybrid E/M" states, which exist along an epithelial-mesenchymal continuum.

View Article and Find Full Text PDF

Unlabelled: Novel preventive interventions are needed to address the rising incidence of human papillomavirus (HPV)-mediated oropharyngeal cancer (HPV+ OPC). This pilot study evaluated the feasibility of a stepped, behavioral and biological screening program for oral oncogenic HPV infection, an intermediate HPV+ OPC outcome. This was a cross-sectional, feasibility study.

View Article and Find Full Text PDF

Complexities in cell-type composition have rightfully led to skepticism and caution in the interpretation of bulk transcriptomic analyses. Recent studies have shown that deconvolution algorithms can be utilized to computationally estimate cell-type proportions from the gene expression data of bulk blood samples, but their performance when applied to tumor tissues, including those from head and neck, remains poorly characterized. Here, we use single-cell data (~6000 single cells) collected from 21 head and neck squamous cell carcinoma (HNSCC) samples to generate cell-type-specific gene expression signatures.

View Article and Find Full Text PDF