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活性疫苗成分的合成与优化建模

Modelling in Synthesis and Optimization of Active Vaccinal Components.

作者信息

Margin Oana-Constantina, Dulf Eva-Henrietta, Mocan Teodora, Mocan Lucian

机构信息

Department of Automation, Faculty of Automation and Computer Science, Technical University of Cluj-Napoca, Str. Memorandumului 28, 400114 Cluj-Napoca, Romania.

Department of Physiology, Iuliu Hațieganu University of Medicine and Pharmacy, 400000 Cluj-Napoca, Romania.

出版信息

Nanomaterials (Basel). 2021 Nov 8;11(11):3001. doi: 10.3390/nano11113001.

DOI:10.3390/nano11113001
PMID:34835765
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8625944/
Abstract

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.

摘要

癌症是全球第二大致死原因，仅次于心脏病，每年导致1000万人死亡。本研究聚焦于腺癌，腺癌是目前医学和制药研究中多种抗癌疗法的靶点。一项关于治疗性疫苗的创新性研究包括对金纳米颗粒及其对癌细胞消灭免疫反应影响的研究。该模型旨在使用定量构效关系（QSAR）方法实现，特别是结合模糊规则的人工神经网络，以增强具有人类感知特征的神经网络的自动化特性。形态变换和分水岭分割等图像处理技术用于从高光谱图像中提取和计算某些分子特征。单细胞特性的量化是关键解决方案之一，代表了结肠癌和直肠癌治疗的效率。这是通过将手动计数的细胞作为比较分割结果的参考点来实现的。早期获得的发现对进一步研究具有决定性意义；因此，提取的特征将首先用于特征优化过程，随后构建所需模型的神经网络。

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