Machine Learning Identifies Stemness Features Associated with Oncogenic Dedifferentiation.

Cancer progression involves the gradual loss of a differentiated phenotype and acquisition of progenitor and stem-cell-like features. Here, we provide novel stemness indices for assessing the degree of oncogenic dedifferentiation. We used an innovative one-class logistic regression (OCLR) machine-learning algorithm to extract transcriptomic and epigenetic feature sets derived from non-transformed pluripotent stem cells and their differentiated progeny. Using OCLR, we were able to identify previously undiscovered biological mechanisms associated with the dedifferentiated oncogenic state. Analyses of the tumor microenvironment revealed unanticipated correlation of cancer stemness with immune checkpoint expression and infiltrating immune cells. We found that the dedifferentiated oncogenic phenotype was generally most prominent in metastatic tumors. Application of our stemness indices to single-cell data revealed patterns of intra-tumor molecular heterogeneity. Finally, the indices allowed for the identification of novel targets and possible targeted therapies aimed at tumor differentiation

A Lodging Internship Competency Model: Enhancing Educational Outcomes through Work Integrated Learning

This paper examines current views of lodging industry executives as to competencies required of student interns and introduces a model for the development of these competencies through the 'work integrated learning' internship process. The purpose of this study is to gain insight into the intern competencies that are currently considered most necessary by the lodging industry - an area that is under-researched in the lodging internship literature - so as to progress understanding of how lodging management education programs, particularly internships, can improve educational outcomes for all stakeholders to the process - educators, industry and students. The paper first offers an introduction and background on work integrated learning, internships and lodging competencies, before presenting the results of a preliminary survey into lodging executive's views of desired intern competency levels, pre-and post-internships, across 18 core essential competencies (CECs). The results of this preliminary survey indicate that leadership and interpersonal skills are the intern competencies most required by industry and that interns should even display some level of competence in these skills prior to commencing the internship. The Lodging Internship Competency Model proposed is an introductory model designed to highlight potential relationships between key variables in the competency development process of the lodging internship.No Full Tex