Prognostic and therapeutic implication of molecular classification including L1CAM expression in high-risk endometrial cancer.

Introduction: The role of molecular classification and L1CAM in high-risk endometrial cancer is uncertain. We aimed to determine the association of molecular profiling and L1CAM with patterns of relapse and survival.

Material And Methods: This retrospective cohort study included patients referred to Department for Gynecologic Oncology, Oslo University Hospital between January 1, 2006 and December 31, 2017.

Mirror, mirror on my screen: Focus on self-presentation on social media is associated with perfectionism and disordered eating among adolescents. Results from the "LifeOnSoMe"-study.

Background: Social media use, perfectionism, and disordered eating have all increased over the last decades. Some studies indicate that there is a relationship between self-presentation behaviors and being exposed to others' self-presentation on social media, and disordered eating. Studies also show that the relationship between focus on self-presentation and highly visual social media is stronger than for non-visual social media, hence facilitating upward social comparison.

Deep learning for automated scoring of immunohistochemically stained tumour tissue sections - Validation across tumour types based on patient outcomes.

We aimed to develop deep learning (DL) models to detect protein expression in immunohistochemically (IHC) stained tissue-sections, and to compare their accuracy and performance with manually scored clinically relevant proteins in common cancer types. Five cancer patient cohorts (colon, two prostate, breast, and endometrial) were included. We developed separate DL models for scoring IHC-stained tissue-sections with nuclear, cytoplasmic, and membranous staining patterns.

DNA ploidy and PTEN as biomarkers for predicting aggressive disease in prostate cancer patients under active surveillance.

Background: Current risk stratification tools for prostate cancer patients under active surveillance (AS) may inadequately identify those needing treatment. We investigated DNA ploidy and PTEN as potential biomarkers to predict aggressive disease in AS patients.

Methods: We assessed DNA ploidy by image cytometry and PTEN protein expression by immunohistochemistry in 3197 tumour-containing tissue blocks from 558 patients followed in AS at a Norwegian local hospital.