Novel 3'-[4-fluoroaryl-(1,2,3-triazol-1-yl)]-3'-deoxythymidine analogues: Design, synthesis, characterization and their potential as anticancer agents.

Novel 3'-[4-fluoroaryl-(1,2,3-triazol-1-yl)]-3'-deoxythymidine analogues (7a-l) were developed by the Cu alkyne-azide cycloaddition (CuAAC) reaction. The obtained lead compounds were confirmed by using 1H NMR, 13C NMR, 2 D NMR, HRMS and their anticancer activities were screened against Huh-7 liver cancer cells and U87MG human glioblastoma cells. Among the synthesized fluorinated 1,2,3-triazolyl nucleosides, three compounds (7i, 7a-b) demonstrated promising anti-proliferative against Huh-7 and U87MG cell lines. Significantly, compound 7i has displayed remarkable promising anticancer activity with IC50 value in the micromole range (22.41-24.92 µM) and (18.12-21.36 µM) against Huh-7 cancer cells and U87MG glioblastoma cells, respectively.

AI-Powered Blockchain Technology for Public Health: A Contemporary Review, Open Challenges, and Future Research Directions.

Blockchain technology has been growing at a substantial growth rate over the last decade. Introduced as the backbone of cryptocurrencies such as Bitcoin, it soon found its application in other fields because of its security and privacy features. Blockchain has been used in the healthcare industry for several purposes including secure data logging, transactions, and maintenance using smart contracts. Great work has been carried out to make blockchain smart, with the integration of Artificial Intelligence (AI) to combine the best features of the two technologies. This review incorporates the conceptual and functional aspects of the individual technologies and innovations in the domains of blockchain and artificial intelligence and lays down a strong foundational understanding of the domains individually and also rigorously discusses the various ways AI has been used along with blockchain to power the healthcare industry including areas of great importance such as electronic health record (EHR) management, distant-patient monitoring and telemedicine, genomics, drug research, and testing, specialized imaging and outbreak prediction. It compiles various algorithms from supervised and unsupervised machine learning problems along with deep learning algorithms such as convolutional/recurrent neural networks and numerous platforms currently being used in AI-powered blockchain systems and discusses their applications. The review also presents the challenges still faced by these systems which they inherit from the AI and blockchain algorithms used at the core of them and the scope of future work.