Establishment of a novel model of peritoneal carcinomatosis of the peritoneal extension type.

作者
Motohiro Imano,Tatsuki Itoh,Takao Satou,Akira Kido,Masahiro Tsubaki,Atsushi Yasuda,Hiroaki Kato,Haruhiko Imamoto,Shozo Nishida,Hiroshi Furukawa,Yoshifumi Takeyama,Kiyokata Okuno,Hitoshi Shiozaki
出处
期刊:PubMed [National Institutes of Health]
卷期号:33 (4): 1439-46 被引量:2
链接
标识
摘要

AIM: Patients with scirrhous carcinoma of the gastrointestinal tract frequently develop peritoneal carcinomatosis-particularly of the peritoneal extension type (PET), which has a bad prognosis. We developed a novel animal model, suitable for testing treatments for PET. MATERIAL AND METHODS: In order to develop the model, we scraped the entire peritoneum of Fischer 344 rats with sterile cotton swabs and injected 1 × 10(6) cells of the RCN-9 cell type into the peritoneal cavity. RESULTS: In the novel experimental model, RCN-9 cells adhered only to the exposed basement membrane. The submesothelial layer and fibroblasts in the submesothelial layer grew and increased to a maximum at day 7, then decreased during late-phase peritoneal carcinomatosis. At day 14, RCN-9 cells coated the peritoneum in a manner similar to PET. CONCLUSION: We successfully established a novel animal model of peritoneal carcinomatosis that mimics clinicopathological features of PET. Fibroblasts in the submesothelial layer potentially play an important role in peritoneal carcinomatosis.

科研通智能强力驱动
Strongly Powered by AbleSci AI
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
赘婿应助Lan采纳,获得10
刚刚
yjh123应助缓慢鹏笑采纳,获得30
1秒前
Nole应助虚幻立诚采纳,获得10
1秒前
1秒前
刘子田完成签到,获得积分10
2秒前
3秒前
冷傲板栗完成签到,获得积分10
3秒前
Dong发布了新的文献求助10
3秒前
小和完成签到,获得积分10
3秒前
3秒前
aaa发布了新的文献求助10
4秒前
1222完成签到,获得积分10
4秒前
大魔王发布了新的文献求助30
4秒前
5秒前
6秒前
隐形曼青应助kaka采纳,获得10
6秒前
Kao应助怕黑岱周采纳,获得10
6秒前
Kao应助怕黑岱周采纳,获得10
7秒前
Kao应助怕黑岱周采纳,获得10
7秒前
Kao应助怕黑岱周采纳,获得10
7秒前
Summertrain完成签到,获得积分10
7秒前
程11发布了新的文献求助10
7秒前
Kao应助怕黑岱周采纳,获得10
7秒前
7秒前
上官若男应助直率的衫采纳,获得10
7秒前
7秒前
小二郎应助初景采纳,获得10
9秒前
苏州河发布了新的文献求助10
9秒前
9秒前
Owen应助金磊采纳,获得10
9秒前
wy完成签到,获得积分10
9秒前
优秀健柏发布了新的文献求助20
10秒前
JasmineJiang完成签到,获得积分10
10秒前
11秒前
乐乐应助qiwei采纳,获得10
11秒前
CC发布了新的文献求助10
11秒前
aaa完成签到,获得积分10
11秒前
打打应助Panjiao采纳,获得10
11秒前
wey完成签到,获得积分10
12秒前
yzy应助mmyhn采纳,获得10
12秒前
高分求助中
Markov Chain Monte Carlo 10000
(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
Common Foundations of American and East Asian Modernisation: From Alexander Hamilton to Junichero Koizumi 5000
How to Use Machine Learning in Chemistry: An Introduction 1000
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
Discerning Saints: Moralization of Intrinsic Motivation and Selective Prosociality at Work 500
Handbuch Trainingswissenschaft – Trainingslehre 500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7582558
求助须知:如何正确求助?哪些是违规求助? 9161515
关于积分的说明 19603606
捐赠科研通 7164763
什么是DOI,文献DOI怎么找? 3266162
关于科研通互助平台的介绍 2431036
邀请新用户注册赠送积分活动 2257436