The field of cryptocurrency and blockchain research is rapidly evolving, with a focus on improving the security, efficiency, and value formation of these systems. Recent studies have explored the use of machine learning and probabilistic models to predict beneficialness and volatility in cryptocurrency networks. Additionally, research has investigated the impact of virtual environments on human exceptionalism and the role of informational attributes in Bitcoin's value formation. Notably, innovative solutions such as MAD-DAG have been proposed to protect blockchain consensus from selfish mining and MEV. Overall, the field is moving towards a more nuanced understanding of the complex interactions between technological, social, and economic factors in cryptocurrency and blockchain systems. Noteworthy papers include: DyPBP, which introduces a novel approach to predicting peer beneficialness in Bitcoin networks. MAD-DAG, which presents a practical protocol to counter selfish mining under adverse conditions.