Modelling in Synthesis and Optimization of Active Vaccinal Components
Cancer is the second leading cause of mortality worldwide, behind heart diseases, accounting for 10 million deaths each year. This study focusses on adenocarcinoma, which is a target of a number of anticancer therapies presently being tested in medical and pharmaceutical studies. The innovative stud...
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-11-01
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| Series: | Nanomaterials |
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| Online Access: | https://www.mdpi.com/2079-4991/11/11/3001 |
| _version_ | 1797509099660771328 |
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| author | Oana-Constantina Margin Eva-Henrietta Dulf Teodora Mocan Lucian Mocan |
| author_facet | Oana-Constantina Margin Eva-Henrietta Dulf Teodora Mocan Lucian Mocan |
| author_sort | Oana-Constantina Margin |
| collection | DOAJ |
| description | Cancer is the second leading cause of mortality worldwide, behind heart diseases, accounting for 10 million deaths each year. This study focusses on adenocarcinoma, which is a target of a number of anticancer therapies presently being tested in medical and pharmaceutical studies. The innovative study for a therapeutic vaccine comprises the investigation of gold nanoparticles and their influence on the immune response for the annihilation of cancer cells. The model is intended to be realized using Quantitative-Structure Activity Relationship (QSAR) methods, explicitly artificial neural networks combined with fuzzy rules, to enhance automated properties of neural nets with human perception characteristics. Image processing techniques such as morphological transformations and watershed segmentation are used to extract and calculate certain molecular characteristics from hyperspectral images. The quantification of single-cell properties is one of the key resolutions, representing the treatment efficiency in therapy of colon and rectum cancerous conditions. This was accomplished by using manually counted cells as a reference point for comparing segmentation results. The early findings acquired are conclusive for further study; thus, the extracted features will be used in the feature optimization process first, followed by neural network building of the required model. |
| first_indexed | 2024-03-10T05:13:04Z |
| format | Article |
| id | doaj.art-959b00de32964c4b964ba9f103cb9f53 |
| institution | Directory Open Access Journal |
| issn | 2079-4991 |
| language | English |
| last_indexed | 2024-03-10T05:13:04Z |
| publishDate | 2021-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Nanomaterials |
| spelling | doaj.art-959b00de32964c4b964ba9f103cb9f532023-11-23T00:41:42ZengMDPI AGNanomaterials2079-49912021-11-011111300110.3390/nano11113001Modelling in Synthesis and Optimization of Active Vaccinal ComponentsOana-Constantina Margin0Eva-Henrietta Dulf1Teodora Mocan2Lucian Mocan3Department of Automation, Faculty of Automation and Computer Science, Technical University of Cluj-Napoca, Str. Memorandumului 28, 400114 Cluj-Napoca, RomaniaDepartment of Automation, Faculty of Automation and Computer Science, Technical University of Cluj-Napoca, Str. Memorandumului 28, 400114 Cluj-Napoca, RomaniaDepartment of Physiology, Iuliu Hațieganu University of Medicine and Pharmacy, 400000 Cluj-Napoca, RomaniaDepartment of Surgery, 3-rd Surgery Clinic, Iuliu Hatieganu University of Medicine and Pharmacy, 400000 Cluj-Napoca, RomaniaCancer is the second leading cause of mortality worldwide, behind heart diseases, accounting for 10 million deaths each year. This study focusses on adenocarcinoma, which is a target of a number of anticancer therapies presently being tested in medical and pharmaceutical studies. The innovative study for a therapeutic vaccine comprises the investigation of gold nanoparticles and their influence on the immune response for the annihilation of cancer cells. The model is intended to be realized using Quantitative-Structure Activity Relationship (QSAR) methods, explicitly artificial neural networks combined with fuzzy rules, to enhance automated properties of neural nets with human perception characteristics. Image processing techniques such as morphological transformations and watershed segmentation are used to extract and calculate certain molecular characteristics from hyperspectral images. The quantification of single-cell properties is one of the key resolutions, representing the treatment efficiency in therapy of colon and rectum cancerous conditions. This was accomplished by using manually counted cells as a reference point for comparing segmentation results. The early findings acquired are conclusive for further study; thus, the extracted features will be used in the feature optimization process first, followed by neural network building of the required model.https://www.mdpi.com/2079-4991/11/11/3001QSARALOANFISwatershed segmentationnanomaterials vaccineanticancer physiology |
| spellingShingle | Oana-Constantina Margin Eva-Henrietta Dulf Teodora Mocan Lucian Mocan Modelling in Synthesis and Optimization of Active Vaccinal Components Nanomaterials QSAR ALO ANFIS watershed segmentation nanomaterials vaccine anticancer physiology |
| title | Modelling in Synthesis and Optimization of Active Vaccinal Components |
| title_full | Modelling in Synthesis and Optimization of Active Vaccinal Components |
| title_fullStr | Modelling in Synthesis and Optimization of Active Vaccinal Components |
| title_full_unstemmed | Modelling in Synthesis and Optimization of Active Vaccinal Components |
| title_short | Modelling in Synthesis and Optimization of Active Vaccinal Components |
| title_sort | modelling in synthesis and optimization of active vaccinal components |
| topic | QSAR ALO ANFIS watershed segmentation nanomaterials vaccine anticancer physiology |
| url | https://www.mdpi.com/2079-4991/11/11/3001 |
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