In patients with non-small-cell lung carcinoma (NSCLC), the analysis of BRAF V600E mutation has become more and more applied since the introduction of many mutation-targeted medications. In this regard, the advantage of immunohistochemistry (IHC) as a reliable diagnostic test substitute to other molecular studies has not been approved yet. Objective. To examine the dependability of using immunohistochemical method utilizing monoclonal VE1 antibody in the detection of BRAF V600 E mutation in patients with non-small-cell lung carcinoma and compare the results there with that of polymerase chain reaction (SSCP-PCR). Materials and Methods. We retrospectively identified 53 patients of whom their histopathological diagnosis was non-small-cell carcinoma of different types. Evaluation of BRAF V600E mutation was assessed using polymerase chain reaction (SSCP-PCR) and IHC using VE1 antibody. This approach was applied to all cases under the study. Results. Among the 53 NSCLC samples, only 5 (9.3%) cases harbored BRAF V600E mutation, 80% were of adenocarcinoma type, and the rest (20%) was of squamous cell carcinoma. IHC analysis for VE1 was positive in 4 out of 5 (80%) BRAF-mutated tumors and negative in all nonmutated BRAF V600 E NSCLC. Conclusion. Our results revealed that VE1 antibody IHC analysis is a promising technique that can be used to detect BRAF V600-mutated NSCLC with relatively high specificity and sensitivity and might become a potential alternative to the current molecular biological methods that are in use for this purpose.
Nowadays, classification of imbalanced data is a major challenge in the machine learning (ML) algorithms, especially in medical data analysis, In this paper, deep learning algorithm which is the advance artificial neural network (ANN) is used for classifying five white blood cells (WBCs). Different preprocessing image techniques and algorithms are applied to isolate WBCs and segment the nucleus for the cytoplasm. Geometric, statistical and color features are extracted, the principal component analysis technique is applied to select the optimal features. The classification process has been repeated several times to tune the algorithm parameters and to find the best pattrens match through the training data in the learning process until achieve best classification accuracy. Multi-class classification results show high accuracy of more than 94% for the five types of WBCs. We evaluate the classification model using the geometric mean, Cohen’s Kappa, Receiver operating characteristic curve, Root mean squared error, relative absolute error and cross-validation techniques. The algorithm model achieves high accuracy and can conduct a multi-class classification of imbalanced datasets in terms of the above-mentioned metrics.
Objectives:The main targets is evaluate clinicopathological distribution and comparison of immunohistochemical (IHC) expression of GATA 3 between in adenoid cystic carcinoma (ACC) and pleomorphic adenoma (PA) of salivary . Design and Methods: This retrospective analysis, open surgical specimens of salivary gland that were done , and consisting of 150 cases that divided into three groups: normal salivary gland tissues (n=50), adenoid cystic carcinoma(n=50), and pleomorphic adenoma(n=50). Clinical data (age, sex, previous diseases ), physical examination, and investigations are done for all patients. In addition.These 150 cases of paraffin embedding blocks of salivary tissue were stained by ordinary stained (hematoxylin and eosin staining ). Manual IHC staining of GATA 3 was done. Results: Age groups is younger for normal salivary gland tissues than PA, and ACC . Sex distribution was slightly increase in male in comparison to female in normal salivary gland tissues and PA. GATA 3 staining was showing more positivity in normal salivary gland tissues (43/50 patients) than PA (27/50 patients) and ACC (14/50 patients). This positivity in GATA 3 IHC staining were more in male sex, regarding 55.8% in normal salivary gland tissues than ACC50% and PA 51.9% . Age group 31-40, 40-50 and 61-70 years were showing more positive GATA 3 IHC staining in normal salivary gland tissues, PA, and ACC respectively. there was insignificant association between GATA 3 IHC staining with either age groups or sex groups distribution .Conclusion: GATA3 IHC is good marker and can used for searching salivary gland tumor origin, assisting in diagnosis Salivary gland tumors subtypes but GATA3 IHC staining has no association to specific sex or age groups in Salivary gland tumors. Usage of surgical operations for histopathological specimens preparation are better and give good efficiency for IHC markers staining.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.