Faculty Publications

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Segmentation and classification of white blood cancer cells from bone marrow microscopic images using duplet-convolutional neural network design
(Springer, 2023) Devi, T.G.; Patil, N.; Rai, S.; Philipose, C.P.
Cancer is a disease linked to the untamed and rapid division of cells in the body. Cancer detection through conventional methods like complete blood count is a tedious and time-consuming task prone to human errors. The introduction of image processing techniques and computer-aided diagnostics is beneficial to this field as the results obtained by utilizing these methods are quick and accurate. The proposed method in this paper uses a design Convolutional Leaky RELU with CatBoost and XGBoost (CLR-CXG) to segment the images and extract the important features that help in classification. The binary classification algorithm and gradient boosting algorithm CatBoost (Categorical Boost) and XGBoost (Extreme Gradient Boost) are implemented individually. Moreover, Convolutional Leaky RELU with CatBoost (CLRC) is designed to decrease bias and provide high accuracy, while Convolutional Leaky RELU with XGBoost (CLRXG) is designed for classification or regression prediction problems which will increase the speed of executing the algorithm and improve its performance. Thus the CLR-CXG classifies the test images into Acute Lymphoblastic Leukemia (ALL) or Multiple Myeloma (MM). Finally, the CLRC algorithm achieved 100% accuracy in classifying cancer cells, and the recorded run time is 10s. Moreover, the CLRXG algorithm has gained an accuracy of 97.12% for classifying cancer cells and 12 s for executing the process. © 2023, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.
Design, synthesis and molecular docking of 5-fluoro indole derivatives as inhibitors of PI3K/Akt signalling pathway in cervical cancer
(Elsevier B.V., 2024) Etikyala, U.; Reddyrajula, R.; Pasha, A.; Udayakumar, U.; Pawar, S.C.; Vijjulatha, V.
The PI3K/Akt signalling pathway promotes variety of cellular processes and the inhibition of PI3K/Akt signalling pathway could lead to decrease in tumour growth effectively in cancer cells. AD412, an indole derivative, is a potent immunosuppressive agent which also reported as an anticancer agent through significant inhibition of PI3K/Akt signalling pathway. In this current work, we designed and synthesized the two diverse lead series of 5-fluoro indole derivatives (6a-l and 11a-l) by specific structural modifications of AD412. In total, 24 new derivatives were evaluated for their antiproliferative activity against two cervical cancer cell lines (HeLa and SiHa) and a normal cell line (HEK 293). Among them, 6e exhibited excellent antiproliferative activity against HeLa and SiHa cells with IC50 values of 9.366 and 8.475 µM respectively, as well displayed a low toxicity profile. Further, 6e inhibited the migration and invasion of HeLa cells in a dose-dependent manner by affecting the synthesis of DNA. Moreover, the Western blot analysis revealed that 6e could inhibit cervical cancer progression by downregulating the PI3K-p85 and phosphorylation of Akt in Hela cells. In vitro mechanism studies demonstrated that 6e could significantly increase apoptosis in HeLa cells by upregulating the expression of proapoptosis related protein Bax. The binding mechanism and the activity profile of 5-fluoro indole derivatives were validated by employing molecular docking studies against the active sites of Akt and PI3K enzymes. In addition, in silico ADME and pharmacokinetic parameters prediction of compound 6e resulted in good oral bioavailability. Therefore, compound 6e could be a lead compound for further development of PI3K/Akt inhibitors and anticancer agents. © 2024

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