ABSTRACT
Topic models are a useful and popular method to find latent topics of documents. However, the short and sparse texts in social media micro-blogs such as Twitter are challenging for the most commonly used Latent Dirichlet Allocation (LDA) topic model. We compare the performance of the standard LDA topic model with the Gibbs Sampler Dirichlet Multinomial Model (GSDMM) and the Gamma Poisson Mixture Model (GPM), which are specifically designed for sparse data. To compare the performance of the three models, we propose the simulation of pseudo-documents as a novel evaluation method. In a case study with short and sparse text, the models are evaluated on tweets filtered by keywords relating to the Covid-19 pandemic. We find that standard coherence scores that are often used for the evaluation of topic models perform poorly as an evaluation metric. The results of our simulation-based approach suggest that the GSDMM and GPM topic models may generate better topics than the standard LDA model.
ABSTRACT
BACKGROUND/AIM: In prostate cancer (PC), the formation of new blood vessels is stimulated by hypoxic conditions, androgens, and a number of molecular factors including microRNAs. MicroRNA-1 (miR-1) has been characterized in some tumor entities as anti-angiogenic, but this has not yet been investigated in PC. MATERIALS AND METHODS: PC cells stably overexpressing miR-1 (LNCaP-miR-1) were incubated on an in vivo hen's egg test-chorioallantoic membrane (HET-CAM) model and compared to maternal LNCaP cells. Cell growth, blood vessel organisation, and total blood vessel area were analysed. RESULTS: Both matrigel-embedded LNCaP and LNCaP-miR-1 cells formed compact tumor-like cell aggregates on the CAM of the HET-CAM model. Although not quantifiable, bleeding of the CAM and remodelling of the blood vessel network in the CAM indicated an influence of miR-1 on the vascular system. The statistically significant decrease in the total surface area of blood vessels in the visible CAM section to 79.4% of control cells demonstrated the antiangiogenic properties of miR-1 for the first time. CONCLUSION: MiR-1 had a tumor-suppressive and anti-angiogenic effect in an in vivo PC model. In the clinic, miR-1-mediated anti-angiogenesis would result in reduced tumor supply and increased hypoxic stress inside the tumor. Thus, miR-1 restoration by nucleic acid-based miR-1 mimetics would represent a promising option for future PC therapy.
