Cell phenotype classification is a critical task in many medical applications, such as protein localization, gene effect identification, and cancer diagnosis in some types. Fluorescence imaging is the most efficient tool to analyze the biological characteristics of cells. So cell phenotype classification in fluorescence microscopy images has received increased attention from scientists in the last decade. The visible structures of cells are usually different in terms of shape, texture, relationship between intensities, etc. In this scope, most of the presented approaches use one type or joint of low-level and high-level features. In this paper, a new approach is proposed based on a combination of low-level and high-level features. An improved version of local quinary patterns is used to extract low-level texture features. Also, an innovative multilayer deep feature extraction method is performed to extract high-level features from DenseNet. In this respect, an output feature map of dense blocks is entered in a separate way to pooling and flatten layers, and finally, feature vectors are concatenated. The performance of the proposed approach is evaluated on the benchmark dataset 2D-HeLa in terms of accuracy. Also, the proposed approach is compared with state-of-the-art methods in terms of classification accuracy. Comparison of results demonstrates higher performance of the proposed approach in comparison with some efficient methods.
This study was conducted to evaluate the occurrence of microbial contamination in the environment of some hospitals and to identify its source in Babil Governorate, during the period between 24/10/2021 to 16/12/2021, (133) samples were collected from different models of samples in Al-Hilla Surgical Hospital, maternity and Children Hospital, Al-Musayyib general Hospital, Marjan Teaching Hospital and Imam Al-Sadiq Hospital. The results of the study was showed the emergence of positive and negative bacteria in the hospital environment from a total of 186 isolates, where the numbers of negative bacteria were higher than positive bacteria (130, 56 isolates, respectively). Also results was revealed the widespread of gram-negative and gram-positive bacteria in emergency wards, especially in Hilla Teaching Hospital, Marjan Hospital, and Musayyib general Hospital, compared to other corridors, which amounted to (21, 9, 15 isolates), respectively.
Diabetes mellitus type 2 (DMT2) is one of the modern societies’ highest public health threats. For a while, it was believed that DM had no impact on male reproductive function; however, new research has cast doubt on that assumption. To find out whether repaglinide and metformin may improve sperm motility and testosterone levels in diabetic and non-diabetic albino rats, researchers in this study used these two drugs to treat diabetes. Methods: Alloxan injections at three dosages of 120 mg/kg intraperitoneal produced type 2 diabetes in male rats. Experimental rats were classified into two main groups. The first group included four subgroups of male rats treated with alloxan (DM inducer). Each subgroup contained seven rats “1. Control without any treatment (positive control), 2. treated by 500 mg/kg metformin, 3. treated by 4 mg/kg repaglinide, and 4. treated by 500 mg/kg metformin and 4 mg/kg repaglinide”. The second group also includes four subgroups but without alloxan treated. Each subgroup has seven rats; all are categorized in the same initial group and receive identical treatment dosages.
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