Effects of Carcinogen Dosage on Experimental Colonic Carcinogenesis by Azoxymethane: An Ultrastructural Study of Grossly Normal Colonic Mucosa23

1985 ◽  
Keyword(s):  
Ultrastructural Study ◽  
Colonic Mucosa ◽  
Normal Colonic Mucosa ◽  
Colonic Carcinogenesis

Polyamines and colon cancer

2003 ◽  
Vol 31 (2) ◽  
pp. 381-383 ◽  
Author(s):  
V. Milovic ◽  
L. Turchanowa
Keyword(s):  
Colon Cancer ◽  
Colonic Mucosa ◽  
The Body ◽  
Normal Colonic Mucosa ◽  
Polyamine Synthesis ◽  
Colonic Carcinogenesis ◽  
Polyamine Content ◽  
High Concentrations ◽  
Mucosal Growth

In colon cancer, the activities of polyamine-synthesizing enzymes and polyamine content are increased 3–4-fold over that found in the equivalent normal colonic mucosa, and polyamines have even been attributed as markers of neoplastic proliferation in the colon. Furthermore, and in contrast with all other cell systems in the body, normal and neoplastic cells in the colon are exposed to high concentrations of putrescine from the lumen, synthesized by colonic microflora. While such a high polyamine supply may be of benefit in non-neoplastic colonic mucosal growth, the role of luminal polyamines in colon cancer is a clear concern. Luminal polyamines are readily taken up by neoplastic colonocytes, they are utilized in full to support neoplastic growth, and their uptake is strongly up-regulated by the mitogens known to play an important role in colonic carcinogenesis. Inhibition of polyamine synthesis and their uptake, impaired utilization of exogenous polyamines, and enhanced catabolism of polyamines in neoplastic colonocytes are therefore logical approaches in the chemoprevention of colorectal cancer.

An Ultrastructural Study of the “Extraneous Coat” of Human Colonic Mucosa

1965 ◽  
Vol 48 (5) ◽  
pp. 593-601 ◽  
Author(s):  
Monira K. Rifaat ◽  
Oscar A. Iseri ◽  
Leonard S. Gottlieb
Keyword(s):  
Ultrastructural Study ◽  
Colonic Mucosa

Tumor-Infiltrating FOXP3+ T Regulatory Cells Show Strong Prognostic Significance in Colorectal Cancer

2009 ◽  
Vol 27 (2) ◽  
pp. 186-192 ◽  
Author(s):  
Paul Salama ◽  
Michael Phillips ◽  
Fabienne Grieu ◽  
Melinda Morris ◽  
Nik Zeps ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Colonic Mucosa ◽  
Tumor Tissue ◽  
Early Stage ◽  
Prognostic Significance ◽  
High Density ◽  
Prognostic Indicators ◽  
Normal Colonic Mucosa ◽  
Solid Cancer ◽  
Histopathologic Features

Purpose To determine the prognostic significance of FOXP3+ lymphocyte (Treg) density in colorectal cancer compared with conventional histopathologic features and with CD8+ and CD45RO+ lymphocyte densities. Patients and Methods Tissue microarrays and immunohistochemistry were used to assess the densities of CD8+, CD45RO+, and FOXP3+ lymphocytes in tumor tissue and normal colonic mucosa from 967 stage II and stage III colorectal cancers. These were evaluated for associations with histopathologic features and patient survival. Results FOXP3+ Treg density was higher in tumor tissue compared with normal colonic mucosa, whereas CD8+ and CD45RO+ cell densities were lower. FOXP3+ Tregs were not associated with any histopathologic features, with the exception of tumor stage. Multivariate analysis showed that stage, vascular invasion, and FOXP3+ Treg density in normal and tumor tissue were independent prognostic indicators, but not CD8+ and CD45RO+. High FOXP3+ Treg density in normal mucosa was associated with worse prognosis (hazard ratio [HR] = 1.51; 95% CI, 1.07 to 2.13; P = .019). In contrast, a high density of FOXP3+ Tregs in tumor tissue was associated with improved survival (HR = 0.54; 95% CI, 0.38 to 0.77; P = .001). Conclusion FOXP3+ Treg density in normal and tumor tissue had stronger prognostic significance in colorectal cancer compared with CD8+ and CD45RO+ lymphocytes. The finding of improved survival associated with a high density of tumor-infiltrating FOXP3+ Tregs in colorectal cancer contrasts with several other solid cancer types. The inclusion of FOXP3+ Treg density may help to improve the prognostication of early-stage colorectal cancer.

scholarly journals Deep Learning Algorithm for the Confirmation of Mucosal Healing in Crohn’s Disease, Based on Confocal Laser Endomicroscopy Images

2021 ◽  
Vol 30 (1) ◽  
pp. 59-65
Author(s):  
Anca Loredana Udristoiu ◽  
Daniela Stefanescu ◽  
Gabriel Gruionu ◽  
Lucian Gheorghe Gruionu ◽  
Andreea Valentina Iacob ◽  
...  
Keyword(s):  
Crohn’S Disease ◽  
Deep Learning ◽  
Crohn's Disease ◽  
Colonic Mucosa ◽  
Mucosal Healing ◽  
Machine Learning Algorithms ◽  
Confocal Laser Endomicroscopy ◽  
Confocal Laser ◽  
Normal Colonic Mucosa ◽  
Test Accuracy

Background and Aims: Mucosal healing (MH) is associated with a stable course of Crohn’s disease (CD) which can be assessed by confocal laser endomicroscopy (CLE). To minimize the operator’s errors and automate assessment of CLE images, we used a deep learning (DL) model for image analysis. We hypothesized that DL combined with convolutional neural networks (CNNs) and long short-term memory (LSTM) can distinguish between normal and inflamed colonic mucosa from CLE images. Methods: The study included 54 patients, 32 with known active CD, and 22 control patients (18 CD patients with MH and four normal mucosa patients with no history of inflammatory bowel diseases). We designed and trained a deep convolutional neural network to detect active CD using 6,205 endomicroscopy images classified as active CD inflammation (3,672 images) and control mucosal healing or no inflammation (2,533 images). CLE imaging was performed on four colorectal areas and the terminal ileum. Gold standard was represented by the histopathological evaluation. The dataset was randomly split in two distinct training and testing datasets: 80% data from each patient were used for training and the remaining 20% for testing. The training dataset consists of 2,892 images with inflammation and 2,189 control images. The testing dataset consists of 780 images with inflammation and 344 control images of the colon. We used a CNN-LSTM model with four convolution layers and one LSTM layer for automatic detection of MH and CD diagnosis from CLE images. Results: CLE investigation reveals normal colonic mucosa with round crypts and inflamed mucosa with irregular crypts and tortuous and dilated blood vessels. Our method obtained a 95.3% test accuracy with a specificity of 92.78% and a sensitivity of 94.6%, with an area under each receiver operating characteristic curves of 0.98. Conclusions: Using machine learning algorithms on CLE images can successfully differentiate between inflammation and normal ileocolonic mucosa and can be used as a computer aided diagnosis for CD. Future clinical studies with a larger patient spectrum will validate our results and improve the CNN-SSTM model.

Can a Normal Colonic Mucosa Harbor an Aggressive Underlying Lymphoma?

2010 ◽  
Vol 103 (6) ◽  
pp. 595-596 ◽  
Author(s):  
Divey Manocha ◽  
Savio John ◽  
Philip Holtzapple
Keyword(s):  
Colonic Mucosa ◽  
Normal Colonic Mucosa

Antioxidant Agents and Colorectal Carcinogenesis: Role of β-Carotene, Vitamin E and Vitamin C

1996 ◽  
Vol 82 (1) ◽  
pp. 6-11 ◽  
Author(s):  
Giuseppe Pappalardo ◽  
Antonio Guadalaxara ◽  
Giuseppe Maiani ◽  
Giovanni Illomei ◽  
Mauro Trifero ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Vitamin E ◽  
Vitamin C ◽  
Colonic Mucosa ◽  
Genetic Alterations ◽  
Colorectal Carcinogenesis ◽  
Normal Colonic Mucosa ◽  
Antioxidant Agents ◽  
Β Carotene

In consideration of findings reported in the literature and of our study, we examined the correlation between antioxidants (β-carotene, vitamin C, vitamin E) and colorectal carcinogenesis. Although diagnostic progress has been made in the last decades, no significant improvements in death rates have been achieved in the western world. Exogenous factors might be responsible for a complex alteration process of normal colonic mucosa into adenoma and carcinoma. Free radicals and reactive oxygen metabolites, due to increased production or to reduced inactivation, following a decrease in the antioxidant burden in the mucosa, might cause damage to DNA, thereby resulting in genetic alterations. This might represent the cause of the transformation process: normal mucosa→ adenoma→ carcinoma. In a prospective study, we observed a reduction of β-carotene levels in normal colonic mucosa in patients with polyps and colorectal cancer. We also showed that β-carotene supplementation raises levels of this micronutrient in the colonic mucosa of these patients. Findings from the literature and our trials show a significant decrease in the antioxidant capacity of colorectal mucosa in patients affected by colorectal cancer, although there is a significant interindividual variability. Such results suggest a possible chemopreventive role of antioxidant agents in colorectal cancer.

Versatility of biotin-labeled lectins and avidin-biotin-peroxidase complex for localization of carbohydrate in tissue sections.

1982 ◽  
Vol 30 (2) ◽  
pp. 157-161 ◽  
Author(s):  
S M Hsu ◽  
L Raine
Keyword(s):  
Colonic Mucosa ◽  
Simple Technique ◽  
Medullary Carcinoma ◽  
Normal Breast ◽  
Normal Colonic Mucosa ◽  
Colonic Adenocarcinoma ◽  
Carcinoma Of The Breast ◽  
Cytoplasmic Staining ◽  
Tissue Sections ◽  
Membranous Staining

Carbohydrate residues in tissue can be localized by a very sensitive, specific, and simple technique, utilizing a biotin-labeled lectin followed by an avidin-biotin-peroxidase complex (ABC). Distribution of peanut receptors in benign and malignant tissues was found to be quite different. Normal colonic mucosa occasionally shows small dot staining in the supranuclear cytoplasm, while the tumor cells of colonic adenocarcinoma tend to show diffuse cytoplasmic or membranous staining. Normal breast ductal epithelium shows membranous staining at luminal borders, while medullary carcinoma of the breast shows distinct membranous and cytoplasmic staining. The use of this avidin-biotin-peroxidase complex technique may contribute to understanding the process of tumorigenesis as well as providing a sensitive method to determine early stages of malignant transformation.

Sign in / Sign up

Export Citation Format

Share Document