Enhancement of Annexin V in response to combination of epigallocatechin gallate and quercetin as a potent arrest the cell cycle of colorectal cancer

Colorectal cancer (CRC) is one of the most common cancers leading to comorbidities and mortalities globally. The rational of current study was to evaluate the combined epigallocatechin gallate and quercetin as a potent antitumor agent as commentary agent for therapeutic protocol. The present study investigated the effect of epigallocatechin Gallate (EGCG) (150mg) and quercetin (200mg) at different proportions on proliferation and induction of apoptosis in human colon cancer cells (HCT-116). Cell growth, colonogenic, Annexin V in addition cell cycle were detected in response to phytomolecules. Data obtained showed that, the colony formation was inhibited significantly in CRC starting from the lowest concentration tested of 10 µg/mL resulting in no colonies as visualized by a phase-contrast microscope. Data showed a significant elevation in the annexin V at 100 µg/mL EGCG(25.85%) and 150 µg/mL quercetin (48.35%). Moreover, cell cycle analysis showed that this combination caused cell cycle arrest at the G1 phase at concentration of 100 µg/mL (72.7%) and 150 µg/mL (75.25%). The combined effect of epigallocatechin Gallate and quercetin exert antiproliferative activity against CRC, it is promising in alternative conventional chemotherapeutic agent.

Intelligent recognition of colorectal cancer combining application of computer-assisted diagnosis with deep learning approaches

<span>The malignancy of the colorectal testing methods has been exposed triumph to decrease the occurrence and death rate; this cancer is the relatively sluggish rising and has an extremely peculiar to develop the premalignant lesions. Now, many patients are not going to colorectal cancer screening, and people who do, are able to diagnose existing tests and screening methods. The most important concept of this motivation for this research idea is to evaluate the recognized data from the immediately available colorectal cancer screening methods. The data provided to laboratory technologists is important in the formulation of appropriate recommendations that will reduce colorectal cancer. With all standard colon cancer tests can be recognized agitatedly, the treatment of colorectal cancer is more efficient. The intelligent computer assisted diagnosis (CAD) is the most powerful technique for recognition of colorectal cancer in recent advances. It is a lot to reduce the level of interference nature has contributed considerably to the advancement of the quality of cancer treatment. To enhance diagnostic accuracy intelligent CAD has a research always active, ongoing with the deep learning and machine learning approaches with the associated convolutional neural network (CNN) scheme.</span>