No abstract

Cancer is one of the highly-rated causes that lead to human mortality. Nowadays with the greater affect of the COVID-19 pandemic, co-morbid patients are at the dual risk of death. Therefore, the main aim of this paper is the specific detection of the cancer cells using nanoparticles further, report analysis using Artificial intelligence, and then the transmission of the medical report is to be done in a neural secured procurement. A simple mechanism to detect cancerous cells through Artificial Neural Networks (ANN) has been proposed here. Moreover, secure attainment of the patients’ medical data has been shown here with the help of Dual Neurons Genetic Key (DNGK). Structural and functionally equivalent ANNs have been iterated to generate the DNGK. In addition, genetic operations were included to make the session key more secured from the opponents. Nanoparticles are frequently used for specific cancer detection on the human body. A revolution in the form of telemedicine in the advanced medical sciences has emerged with the cameo of novel coronavirus things (IoT). It has helped to curtail the coronavirus chain through remote treatments. An Artificial Neural Network will be trained to detect the cancerous cells of the human body. The decision generated by ANN would be encrypted through the AES algorithm and DHNK before procured to the network. The Artificial Neural Network had been trained on different bio-images so that it generates an automated decision. Thus, prompt, safe, and automated cancer detection may be done using this proposed technique. Results derived from different tests on the proposed technique were evaluated and thus, validating the entire proposed technique. Thus, loads of societal development would happen in the fields of Medical Sciences, especially during these post-COVID-19 crisis hours.

In epithelia, normal cells recognize and extrude out newly emerged transformed cells by competition. This process is the most fundamental epithelial defence against cancer, whose occasional failure promotes oncogenesis. However, little is known about what factors determine the success or failure of this defence. Here we report that mechanical stiffening of extracellular matrix attenuates the epithelial defence against activated HRasV12-transformed cells. Using photoconversion labelling, protein tracking, and loss-of-function mutations, we attribute this attenuation to stiffening-induced perinuclear sequestration of a cytoskeletal protein, filamin. On soft matrix mimicking healthy epithelium, filamin exists as a dynamically single population, which moves to the normal cell-transformed cell interface to initiate transformed cell-extrusion. But, on stiff matrix mimicking fibrotic epithelium, filamin redistributes into two dynamically distinct populations, including a new perinuclear pool, which cannot move to the cell-cell interface. A tug-of-war between filamin-Cdc42 and filamin-perinuclear cytoskeleton interactions controls this differential filamin localization and hence, determines the success or failure of epithelial defence on soft versus stiff matrix. Together, our study reveals how pathological matrix stiffening leads to a failed epithelial defence at the initial stage of oncogenesis.