School Of Health Sciences

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    Opportunities and challenges in application of artificial intelligence in pharmacology
    (Springer Science and Business Media Deutschland GmbH, 2023-01-09T00:00:00) Kumar, Mandeep; Nguyen, T. P. Nhung; Kaur, Jasleen; Singh, Thakur Gurjeet; Soni, Divya; Singh, Randhir; Kumar, Puneet
    Artificial intelligence (AI) is a machine science that can mimic human behaviour like intelligent analysis of data. AI functions with specialized algorithms and integrates with deep and machine learning. Living in the digital world can generate a huge amount of medical data every day. Therefore, we need an automated and reliable evaluation tool that can make decisions more accurately and faster. Machine learning has the potential to learn, understand and analyse the data used in healthcare systems. In the last few years, AI is known to be employed in various fields in pharmaceutical science especially in pharmacological research. It helps in the analysis of preclinical (laboratory animals) and clinical (in human) trial data. AI also plays important role in various processes such as drug discovery/manufacturing, diagnosis of big data for disease identification, personalized treatment, clinical trial research, radiotherapy, surgical robotics, smart electronic health records, and epidemic outbreak prediction. Moreover, AI has been used in the evaluation of biomarkers and diseases. In this review, we explain various models and general processes of machine learning and their role in pharmacological science. Therefore, AI with deep learning and machine learning could be relevant in pharmacological research. � 2023, The Author(s) under exclusive licence to Maj Institute of Pharmacology Polish Academy of Sciences.
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    Prognostic significance of CHAC1 expression in breast cancer
    (Springer Science and Business Media B.V., 2022-06-21T00:00:00) Mehta, Vikrant; Meena, Jaipal; Kasana, Harit; Munshi, Anjana; Chander, Harish
    Background: An emerging component of Unfolded Protein Response (UPR) pathway, cation transport regulator homolog 1 (CHAC1) has been conferred with the ability to degrade intracellular glutathione and induce apoptosis, however, many reports have suggested a role of CHAC1 in cancer progression. Our study aimed to investigate CHAC1 mRNA levels in large breast cancer datasets using online tools and both mRNA and protein levels in different breast cancer cell lines. Methods and results: Analysis of clinical information from various online tools (UALCAN, GEPIA2, TIMER2, GENT2, UCSCXena, bcGenExMiner 4.8, Km Plotter, and Enrichr) was done to elucidate the CHAC1 mRNA expression in large breast cancer patient dataset and its correlation with disease progression. Later, in vitro techniques were employed to explore the mRNA and protein expression of CHAC1 in breast cancer cell lines. Evidence from bioinformatics analysis as well as in vitro studies indicated a high overall expression of CHAC1 in breast tumor samples and had a significant impact on the prognosis and survival of patients. Enhanced CHAC1 levels in the aggressive breast tumor subtypes such as Human Epidermal growth factor receptor 2 (HER2) and Triple Negative Breast Cancer (TNBC) were evident. Our findings hint toward the possible role of CHAC1 in facilitating the aggressiveness of breast cancer and the disease outcome. Conclusion: In summary, CHAC1 is constantly up-regulated in breast cancer leading to a poor prognosis. CHAC1, therefore, could be a promising candidate in the analysis of breast cancer diagnosis and prognosis. � 2022, The Author(s), under exclusive licence to Springer Nature B.V.