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Invasive ductal carcinoma (IDC) breast cancer is a significant health concern for women all around the world and early detection of the disease may increase the survival rate in patients. Therefore, Computer-Aided Diagnosis (CAD) based systems can assist pathologists to detect the disease early. In this study, we present an ensemble model to detect IDC using DenseNet-121 and DenseNet-169 followed by test time augmentation (TTA). The model achieved a balanced accuracy of 92.70% and an F1-score of 95.70% outperforming the current state-of-the-art. Comparative analysis against various pre-trained deep learning models and preprocessing methods have been carried out. Qualitative analysis has also been conducted on the test dataset. After the detection of IDC breast cancer, it is important to grade it for further treatment. In our study, we also propose an ensemble model for the grading of IDC using the pre-trained DenseNet-121, DenseNet-201, ResNet-101v2, and ResNet-50 architectures. The model is inferred from two validation cohorts. For the patch-level classification, the model yielded an overall accuracy of 69.31%, 75.07%, 61.85%, and 60.50% on one validation cohort and 62.44%, 79.14%, 76.62%, and 71.05% on the second validation cohort for 4×, 10×, 20×, and 40× magnified images respectively. The same architecture is further validated using a different IDC dataset where it achieved an overall accuracy of 90.07%. The performance of the models on the detection and grading of IDC shows that they can be useful to help pathologists detect and grade the disease., (Copyright © 2021 Elsevier Ltd. All rights reserved.)

Background: AP2 is a clathrin-based endocytic adaptor complex comprising α, β2, μ2 and σ2 subunits. μ2 regulates CFTR endocytosis. The α subunit interacts with CFTR in the intestine but its physiologic significance is unclear., Methods: CFTR short circuit current was measured in intestinal T84 cells following shRNA knock down of AP2α (AP2αKD). Clathrin-coated structures (CCS) were immunolabeled and quantified in AP2αKD intestinal Caco2BBe (C2BBe) cells. GST tagged human AP2α appendage domain was cloned and its interaction with CFTR determined by GST pull down assay., Result: AP2αKD in T84 cells resulted in higher CFTR current (57%) compared to control, consistent with increased functional CFTR and delayed endocytosis. Depletion of AP2α reduced CCS in C2BBe cells. Pull down assays revealed an interaction between human AP2α appendage domain and CFTR., Conclusion: AP2 α interacts with and modulates CFTR function in the intestine by participating in clathrin assembly and recruitment of CFTR to CCS., (Copyright © 2017 European Cystic Fibrosis Society. Published by Elsevier B.V. All rights reserved.)