The role of artificial intelligence (AI) in material science and engineering (MSE) is becoming increasingly important as AI technology advances. The development of high‐performance computing has made it possible to test deep learning (DL) models with significant parameters, providing an opportunity to overcome the limitation of traditional computational methods, such as density functional theory (DFT), in property prediction. Machine learning (ML)‐based methods are faster and more accurate than DFT‐based methods. Furthermore, the generative adversarial networks (GANs) have facilitated the generation of chemical compositions of inorganic materials without using crystal structure information. These developments have significantly impacted material engineering (ME) and research. Some of the latest developments in AI in ME herein are reviewed. First, the development of AI in the critical areas of ME, such as in material processing, the study of structure and material property, and measuring the performance of materials in various aspects, is discussed. Then, the significant methods of AI and their uses in MSE, such as graph neural network, generative models, transfer of learning, etc. are discussed. The use of AI to analyze the results from existing analytical instruments is also discussed. Finally, AI's advantages, disadvantages, and future in ME are discussed.
Background: Globally Bone tumors constitute 0.5% of the total World Cancer Incidence. In addition to benign and malignant bone tumors there are a number of nonneoplastic lesions that present in a manner similar to neoplastic conditions. Relevant demographic features such as age, sex and skeletal site are important to come to a conclusive diagnosis. The present study aims to show the prevalence and demography of bone tumors and tumor like lesions.Methods: A total of 76 cases of Bone Tumors and Tumor like Lesions were studied. They were reviewed and analyzed for age, gender, site of tumor and histologic types. Classification was done according to WHO histologic Classification of Bone Tumors.Results: There were 49 cases of primary bone tumors and tumor Like lesions with a median age of 22 years and 27 cases of metastatic bone tumors with a median age of 56 years. Males are more commonly affected. Osteosarcomas and Chondrosarcomas are the most common primary malignant Bone Tumors.Conclusions: Metastatic bone tumors constitute the highest number of bone tumors occurring at an older age group. Maximum numbers of bone tumors are found in the age range 11-20 years and all are primary bone tumor and tumor like lesions.
The present investigation aimed to find the in vitro antioxidant and anti-inflammatory potential of fractions of methanol extract of Alangium chinense (Lour.) Harms leaves followed by isolation and identification bioactive molecule and evaluate its possible mechanism through in silico study. A methanol extract of Alangium chinense (Lour.) Harms leaves subjected for chromatographic fractionation and pure isolates (F1-F8) were evaluated for their in vitro anti-inflammatory activity using albumin denaturation inhibition assay and in vitro antioxidant activity. Fraction F4 showed highest in vitro anti-inflammatory activity (IC50 = 70.02 μg/mL), whereas fractions F3, F4, F7 showed better in vitro antioxidant activity compare to other fractions. F4 fraction was screened for its tentative structure using FTIR, 1H and 13C NMR. The spectral analysis showed that the fraction F4 has a tentative structure of olean 19-ene-1yl-acetate. The molecular docking studies showed that test ligand significantly interact with different key active sites of amino acids and thus confirm possible COX-2 inhibitory activity of fraction F4. In vitro and in silico study confirmed the isolation of possible anti-inflammatory from Alangium chinense (Lour.) Harms leaves, which may further used as lead to a development of a new therapeutic agent.
Background: Soft tissue tumors are defined as mesenchymal proliferations which occur in the extraskeletal non-epithelial tissues of the body, excluding the viscera, coverings of brain and lymphoreticular system. The objective of this study was to study the histopathological features of soft tissue tumors and to study the occurrence of soft tissue tumors in relation to age, sex and anatomical site.Methods: This study comprised of 89 cases studied over a period of two years. All soft tissue tumors, their gross features, microscopic findings were analysed in detail. Soft tissue tumors were divided into benign and malignant categories and further sub typing were done according to World Health Organization (WHO) classification. The distribution of soft tissue tumors according to the age, sex and site of occurrence was studied.Results: Out of 89 cases of soft tissue tumors, 76 cases were benign, 4 cases belonged to intermediate category and 9 cases were malignant. Adipocytic tumors formed the largest group constituting 39 cases. Vascular tumors were the second commonest (26 cases) followed by peripheral nerve sheath tumors (11 cases). The benign tumors were seen in younger age as compared to malignant tumors. Malignant soft tissue tumors was seen to be more common in male than female and pleomorphic sarcoma and liposarcoma was commonest (3 cases each).Conclusions: Benign tumors were more common than malignant. The most common benign tumors were lipoma followed by hemangioma and schwannoma. The most common malignant tumor was pleomorphic sarcoma. The benign tumors were seen in younger age as compared to malignant tumors.
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