Artificial intelligence (AI) is the use of mathematical algorithms to mimic human cognitive abilities and to address difficult healthcare challenges including complex biological abnormalities like cancer. The exponential growth of AI in the last decade is evidenced to be the potential platform for optimal decision-making by super-intelligence, where the human mind is limited to process huge data in a narrow time range. Cancer is a complex and multifaced disorder with thousands of genetic and epigenetic variations. AI-based algorithms hold great promise to pave the way to identify these genetic mutations and aberrant protein interactions at a very early stage. Modern biomedical research is also focused to bring AI technology to the clinics safely and ethically. AI-based assistance to pathologists and physicians could be the great leap forward towards prediction for disease risk, diagnosis, prognosis, and treatments. Clinical applications of AI and Machine Learning (ML) in cancer diagnosis and treatment are the future of medical guidance towards faster mapping of a new treatment for every individual. By using AI base system approach, researchers can collaborate in real-time and share knowledge digitally to potentially heal millions. In this review, we focused to present game-changing technology of the future in clinics, by connecting biology with Artificial Intelligence and explain how AI-based assistance help oncologist for precise treatment.

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Mining operations deal mainly with hard and soft rocks with different mechanical properties and varying strengths. The aim of the slake durability test is to present an index related to degradation resistance of rock when exposed to standard cycles of wetting and drying. Research in geology and rock mechanics is done to explain the influence of the rock index properties in determining the strength, durability and pulse velocity of the rock. This paper enlightens the prediction of the rock’s behavior and nature of the degradation of rocks The index values obtained for sandstone are varying from 97.36 to 99.04% and for shale it ranges from 10.21 to 14.06%. The slake durability index test for sandstone sample indicates that it is high durable and the shale indicates very low durability. The average value of uniaxial compressive strength was calculated to be 83.144 MPa.

Enhanced cellulase production was studied with ultraviolet mutagenesis and the mutated cellulase gene in E. coli DH5α was cloned for production under controlled conditions. Aspergillus niger inoculum was exposed to UV radiation for different time intervals. The UV exposure of 10 min to A. niger yielded 330 μmol/min/mg specific activity. The mRNA of mutant A. niger yielding maximum enzyme activity was isolated and used for the synthesis of cDNA. The cDNA prepared from mRNA was used for the PCR amplification of mutated cellulase gene with primers designed on the basis of a cellulase gene database from A. niger. The amplified cellulase gene was cloned into E. coli DH5α followed by expression in E. coli BL21. The cellulase activity by wild type A. niger, A. niger UVMT-I, and recombinant E. coli was compared by analysis of variance test. The specific activity of cellulase by recombinant E. coli was maximum (441 μmol/min/mg), followed by A. niger UVMT-I (330 μmol/min/mg) and wild type A. niger (96 μmol/min/mg).

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