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Related Concept Videos

Interference and Diffraction02:18

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Interference is a characteristic phenomenon exhibited by waves. When two electromagnetic waves interact with their peaks and troughs coinciding, a resulting wave with enhanced amplitude is produced. This is known as constructive interference. In this case, the two waves interacting are in phase with each other.
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Phase Contrast and Differential Interference Contrast Microscopy01:26

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Phase-Contrast Microscopes
In-phase-contrast microscopes, interference between light directly passing through a cell and light refracted by cellular components is used to create high-contrast, high-resolution images without staining. It is the oldest and simplest type of microscope that creates an image by altering the wavelengths of light rays passing through the specimen. Altered wavelength paths are created using an annular stop in the condenser. The annular stop produces a hollow cone of...
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RNA Interference01:23

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RNA interference (RNAi) is a process in which a small non-coding RNA molecule blocks the post-transcriptional expression of a gene by binding to its messenger RNA (mRNA) and preventing the protein from being translated.
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Forgetting is a complex cognitive phenomenon influenced by several factors, among which interference and decay are particularly prominent. These processes explain why individuals often struggle to retrieve specific information from memory, leading to lapses in recall that can be observed in everyday situations.
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Sound Waves: Interference00:53

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Sound waves can be modeled either as longitudinal waves, wherein the molecules of the medium oscillate around an equilibrium position, or as pressure waves. When two identical waves from the same source superimpose on each other, the combination of two crests or two troughs results in amplitude reinforcement known as constructive interference. If two identical waves, that are initially in phase, become out of phase because of different path lengths, the combination of crests with troughs...
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Interference and Superposition of Waves01:07

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When two waves of the same nature occur in the same region simultaneously, they result in interference. Interference of waves implies that the net effect of the waves is the sum of the individual waves' effects. However, it does not imply that the individual waves affect the propagation of other waves.
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Label-free quantitative evaluation of breast tissue using Spatial Light Interference Microscopy (SLIM).

Hassaan Majeed1, Tan Huu Nguyen1, Mikhail Eugene Kandel1

  • 1Quantitative Light Imaging (QLI) Lab, Beckman Institute of Advanced Science and Technology, University of Illinois at Urbana Champaign, 405 N Matthews, Urbana, IL 61801, USA.

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Summary

A new quantitative method using Spatial Light Interference Microscopy (SLIM) offers objective, label-free breast cancer diagnosis. This approach analyzes tissue nanostructure for improved accuracy in histopathology, potentially reducing diagnostic variability.

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Area of Science:

  • Biomedical Engineering
  • Optical Microscopy
  • Cancer Diagnostics

Background:

  • Breast cancer diagnosis relies on manual histopathology, which can be subjective and vary between observers.
  • Difficult cases may require additional markers, highlighting a need for more objective diagnostic tools.
  • Current methods are often dependent on tissue staining, which can introduce variability.

Purpose of the Study:

  • To develop and validate a quantitative, label-free method for breast tissue evaluation using Spatial Light Interference Microscopy (SLIM).
  • To extract objective tissue markers of malignancy based on nanostructure and optical path-length.
  • To provide a potentially automatable and standardized approach to breast histopathology.

Main Methods:

  • Spatial Light Interference Microscopy (SLIM) was employed for label-free imaging of breast tissue microarrays.
  • Quantitative analysis extracted tissue markers related to nanostructure and optical path-length.
  • Machine learning algorithms were utilized for classification based on extracted disease signatures.

Main Results:

  • The method achieved 94% sensitivity and 85% specificity in detecting breast cancer in a cohort of 68 subjects (34 malignant, 34 benign).
  • Disease signatures were found to be intrinsic physical attributes, independent of staining quality.
  • Images generated were consistent across different scans and instruments, facilitating machine learning integration.

Conclusions:

  • SLIM offers a robust, quantitative, and label-free approach for breast cancer histopathology.
  • The method provides objective diagnostic markers, potentially reducing inter-observer variability.
  • This technique shows promise for automated and reliable cancer diagnosis.