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Related Concept Videos

Classification of Epithelial Tissues: Overview01:22

Classification of Epithelial Tissues: Overview

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Epithelial tissues are classified according to the shape of the cells and the number of cell layers formed. Cell shapes can be squamous (flattened and thin), cuboidal (square-like, as wide as it is tall), or columnar (rectangular, taller than it is wide). Additionally, the nucleus shape helps identify the type of epithelial cells. Squamous cells have flattened disc-shaped nuclei, cuboidal cells have spherical nuclei, and columnar cells have elongated nuclei.
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Stratified epithelium consists of several stacked layers of cells. They provide the durability to withstand constant physical and chemical attacks. Stratified epithelium is named after the shape of the most apical layer of cells. Stratified squamous epithelium is the most common type found in the human body. In this tissue, the apical cells are squamous, whereas the basal layer contains either columnar or cuboidal cells. The basal cells divide to form new daughter cells, which gradually become...
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Classification of Epithelial Tissues: Simple Epithelium01:30

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Simple epithelium consists of a single layer of cells that lines body cavities and blood vessels. The shape of the cells in the epithelium reflects the function of the tissue. Cells in simple squamous epithelium appear as thin scales with flat, elliptical nuclei that mirror the form of the cell.
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The glandular epithelium is made of one or more epithelial cells modified to synthesize and secrete chemical substances. Glandular epithelia can be classified based on cell number. Unicellular glands have individual secretory cells scattered across the epithelial monolayer. In contrast, multicellular glands consist of a hollow tubular duct attached to the cluster of secretory cells located in the deep pockets.
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Correction: Adeluola et al. Chemoprevention of 4-NQO-Induced Oral Cancer by the Combination of Resveratrol and EGCG: In Vivo, In Silico and In Vitro Studies. <i>Cancers</i> 2026, <i>18</i>, 1098.

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Automated Raman Micro-Spectroscopy of Epithelial Cell Nuclei for High-Throughput Classification.

Kevin O'Dwyer1, Katarina Domijan2, Adam Dignam3

  • 1Department of Electronic Engineering, Maynooth University, Maynooth, Ireland.

Cancers
|October 13, 2021
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Summary
This summary is machine-generated.

This study introduces an automated Raman cytology system to improve cancer detection speed and accuracy. The freely available system enhances reproducibility for clinical pathology applications.

Keywords:
Raman spectroscopyThinPrepautomated cytologycellular classificationhigh-throughput classificationscreening

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Area of Science:

  • Biomedical Engineering
  • Optical Spectroscopy
  • Cancer Diagnostics

Background:

  • Raman micro-spectroscopy offers high accuracy for cancer cell identification.
  • Current limitations include slow recording times and poor reproducibility, hindering clinical use.

Purpose of the Study:

  • To develop an automated Raman cytology system for high-throughput screening.
  • To enhance the reproducibility of Raman spectroscopy in clinical pathology settings.

Main Methods:

  • An automated system integrating hardware and software was developed.
  • Image processing algorithms and the open-source Micro-Manager platform were employed.
  • Testing was performed using the ThinPrep standard and bladder cancer cell lines.

Main Results:

  • The automated system demonstrates potential for high-throughput screening.
  • The system addresses reproducibility issues in Raman spectroscopy.
  • The developed automation process is compatible with standard pathology workflows.

Conclusions:

  • The automated Raman cytology system can be integrated into clinical pathology.
  • The freely available code facilitates wider adoption of Raman spectroscopy.
  • This technology promises to improve cancer diagnostics through enhanced efficiency and reliability.