C38结肠腺癌和B16黑色素瘤肿瘤生长模型的鉴定与分析

Johanna Sápi, D. Drexler, I. Harmati, A. Szeles, B. Kiss, Z. Sápi, L. Kovács
{"title":"C38结肠腺癌和B16黑色素瘤肿瘤生长模型的鉴定与分析","authors":"Johanna Sápi, D. Drexler, I. Harmati, A. Szeles, B. Kiss, Z. Sápi, L. Kovács","doi":"10.1109/SACI.2013.6608987","DOIUrl":null,"url":null,"abstract":"Cancer fighting treatments are expanding, and a promising type, targeted molecular therapies have a new approach. The aim of these therapies is not to eliminate the whole tumor, but to control the tumor into a given state and keep it there. Explicit knowledge of tumor growth dynamics and the effects of targeted molecular therapies is crucial in tumor treatment development. We show the results of mouse experiments where tumor growth was investigated in case of C38 colon adenocarcinoma and B16 melanoma. Several curves were fitted and tumor growth dynamics was examined. Three attributes of tumor were measured: tumor volume, tumor mass and vascularization; and tumor growth dynamics was examined. Tumor volume was measured with digital caliper, vascularization was investigated with CD31 antibody immunohistochemistry staining on frozen sections. The relationship between these tumor attributes were examined with linear regression analysis. The dynamics of tumor growth was identified as a second order linear system.","PeriodicalId":304729,"journal":{"name":"2013 IEEE 8th International Symposium on Applied Computational Intelligence and Informatics (SACI)","volume":"112 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":"{\"title\":\"Tumor growth model identification and analysis in case of C38 colon adenocarcinoma and B16 melanoma\",\"authors\":\"Johanna Sápi, D. Drexler, I. Harmati, A. Szeles, B. Kiss, Z. Sápi, L. Kovács\",\"doi\":\"10.1109/SACI.2013.6608987\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Cancer fighting treatments are expanding, and a promising type, targeted molecular therapies have a new approach. The aim of these therapies is not to eliminate the whole tumor, but to control the tumor into a given state and keep it there. Explicit knowledge of tumor growth dynamics and the effects of targeted molecular therapies is crucial in tumor treatment development. We show the results of mouse experiments where tumor growth was investigated in case of C38 colon adenocarcinoma and B16 melanoma. Several curves were fitted and tumor growth dynamics was examined. Three attributes of tumor were measured: tumor volume, tumor mass and vascularization; and tumor growth dynamics was examined. Tumor volume was measured with digital caliper, vascularization was investigated with CD31 antibody immunohistochemistry staining on frozen sections. The relationship between these tumor attributes were examined with linear regression analysis. The dynamics of tumor growth was identified as a second order linear system.\",\"PeriodicalId\":304729,\"journal\":{\"name\":\"2013 IEEE 8th International Symposium on Applied Computational Intelligence and Informatics (SACI)\",\"volume\":\"112 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-05-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"8\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2013 IEEE 8th International Symposium on Applied Computational Intelligence and Informatics (SACI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SACI.2013.6608987\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 IEEE 8th International Symposium on Applied Computational Intelligence and Informatics (SACI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SACI.2013.6608987","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 8

摘要

抗癌治疗正在扩大,一种有前途的类型,靶向分子治疗有了新的方法。这些疗法的目的不是消灭整个肿瘤,而是将肿瘤控制在一个给定的状态,并使其保持在那里。明确了解肿瘤生长动力学和靶向分子治疗的效果对肿瘤治疗的发展至关重要。我们展示了在C38结肠腺癌和B16黑色素瘤的情况下研究肿瘤生长的小鼠实验结果。拟合了几条曲线,并检查了肿瘤生长动力学。测量肿瘤的三个属性:肿瘤体积、肿瘤质量和血管化;观察肿瘤生长动态。用数字卡尺测量肿瘤体积,冷冻切片用CD31抗体免疫组化染色观察血管形成。用线性回归分析检验这些肿瘤属性之间的关系。肿瘤生长动力学被确定为一个二阶线性系统。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Tumor growth model identification and analysis in case of C38 colon adenocarcinoma and B16 melanoma
Cancer fighting treatments are expanding, and a promising type, targeted molecular therapies have a new approach. The aim of these therapies is not to eliminate the whole tumor, but to control the tumor into a given state and keep it there. Explicit knowledge of tumor growth dynamics and the effects of targeted molecular therapies is crucial in tumor treatment development. We show the results of mouse experiments where tumor growth was investigated in case of C38 colon adenocarcinoma and B16 melanoma. Several curves were fitted and tumor growth dynamics was examined. Three attributes of tumor were measured: tumor volume, tumor mass and vascularization; and tumor growth dynamics was examined. Tumor volume was measured with digital caliper, vascularization was investigated with CD31 antibody immunohistochemistry staining on frozen sections. The relationship between these tumor attributes were examined with linear regression analysis. The dynamics of tumor growth was identified as a second order linear system.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
V/f control strategy with constant power factor for SPMSM drives, with experiments Spline filtering in accordance to ISO/TS 16610: ANSI C-code for engineers HITS based network algorithm for evaluating the professional skills of wine tasters Performance evaluation of a face detection algorithm running on general purpose operating systems Tumor growth model identification and analysis in case of C38 colon adenocarcinoma and B16 melanoma
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1