Nanoindentation study of the viscoelastic properties of human triple negative breast cancer tissues: Implications for mechanical biomarkers

纳米压痕 乳腺癌 三阴性乳腺癌 粘弹性 材料科学 生物医学工程 癌症 人体乳房 病理 医学 内科学 复合材料
作者
Theresa C. Ezenwafor,Vitalis C. Anye,Jonathan Madukwe,Said Amin,John D. Obayemi,Olushola S. Odusanya,Winston O. Soboyejo
出处
期刊:Acta Biomaterialia [Elsevier]
卷期号:158: 374-392 被引量:11
标识
DOI:10.1016/j.actbio.2023.01.011
摘要

This paper presents the results of a combined experimental and theoretical study of the structure and viscoelastic properties of human non-tumorigenic mammary breast tissues and triple negative breast cancer (TNBC) tissues of different histological grades. A combination of immunofluorescence and confocal microscopy, and atomic force microscopy is used to study the actin cytoskeletal structures of non-tumorigenic and tumorigenic breast tissues (grade I to grade III). A combination of nanoindentation and statistical techniques is then used to measure viscoelastic properties of non-tumorigenic and human TNBC of different histological grades. A Standard Fluid Model/Anti-Zener Model II is also used to characterize the viscoelastic properties of the non-tumorigenic and tumorigenic TNBC tissues of different grades. The implications of the results are discussed for the potential application of nanoindentation and statistical deconvolution techniques to the development of mechanical biomarkers for TNBC detection/cancer diagnosis. STATEMENT OF SIGNIFICANCE: There is increasing interest in the development of mechanical biomarkers for cancer diagnosis. Here, we show that nanoindentation techniques can be used to characterize the viscoelastic properties of normal breast tissue and TNBC tissues of different histological grades. The Standard Fluid Model (Anti-Zener Model II) is used to classify the viscoelastic properties of breast tissues of different TNBC histological grades. Our results suggest that breast tissue and TNBC tissue viscoelastic properties can be used as mechanical biomarkers for the detection of TNBC at different stages.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
更新
PDF的下载单位、IP信息已删除 (2025-6-4)

科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
平淡凝雁完成签到,获得积分10
刚刚
小肚肚完成签到,获得积分10
1秒前
1秒前
luxian发布了新的文献求助10
1秒前
1秒前
深情安青应助minnie采纳,获得10
2秒前
jam完成签到,获得积分10
2秒前
王子完成签到,获得积分10
3秒前
Stella应助Dante采纳,获得30
3秒前
4秒前
Stella应助long采纳,获得30
4秒前
Chenziqing完成签到,获得积分10
4秒前
4秒前
知秋发布了新的文献求助10
5秒前
邪恶洋葱完成签到,获得积分20
5秒前
5秒前
zhun发布了新的文献求助10
5秒前
共享精神应助辛夷采纳,获得10
6秒前
6秒前
领导范儿应助犯困采纳,获得10
6秒前
6秒前
7秒前
eric888应助mathmotive采纳,获得310
7秒前
爆米花应助BINGBING1230采纳,获得10
7秒前
7秒前
起名太难了完成签到,获得积分20
8秒前
冷傲的大树完成签到,获得积分20
8秒前
Jasper应助西灵壹采纳,获得10
9秒前
FashionBoy应助邪恶洋葱采纳,获得10
9秒前
9秒前
10秒前
Miukoo发布了新的文献求助10
11秒前
张德帅完成签到,获得积分10
11秒前
残剑月发布了新的文献求助10
11秒前
whatever举报求助违规成功
12秒前
坦率耳机举报求助违规成功
12秒前
Smar_zcl举报求助违规成功
12秒前
12秒前
suyou发布了新的文献求助10
12秒前
qiang发布了新的文献求助10
13秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Bandwidth Choice for Bias Estimators in Dynamic Nonlinear Panel Models 2000
HIGH DYNAMIC RANGE CMOS IMAGE SENSORS FOR LOW LIGHT APPLICATIONS 1500
茶艺师试题库(初级、中级、高级、技师、高级技师) 1000
Constitutional and Administrative Law 1000
The Social Work Ethics Casebook: Cases and Commentary (revised 2nd ed.). Frederic G. Reamer 800
Vertebrate Palaeontology, 5th Edition 560
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 有机化学 生物化学 物理 纳米技术 计算机科学 内科学 化学工程 复合材料 物理化学 基因 遗传学 催化作用 冶金 量子力学 光电子学
热门帖子
关注 科研通微信公众号,转发送积分 5361763
求助须知:如何正确求助?哪些是违规求助? 4491873
关于积分的说明 13984270
捐赠科研通 4394835
什么是DOI,文献DOI怎么找? 2414190
邀请新用户注册赠送积分活动 1406961
关于科研通互助平台的介绍 1381610