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Related Concept Videos

Atomic Force Microscopy01:08

Atomic Force Microscopy

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Atomic force microscopy (AFM) is a type of scanning probe microscopy that can analyze topographic details of various specimens like ceramics, glass, polymers, and biological samples. AFM offers over 1000 times more resolution than the optical imaging system. Images generated from AFM are three-dimensional surface profiles, offering an advantage over the flat, two-dimensional images from other imaging techniques.
The AFM Probe
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When an oscillator is forced with a periodic driving force, the motion may seem chaotic. The motions of such oscillators are known as transients. After the transients die out, the oscillator reaches a steady state, where the motion is periodic, and the displacement is determined.
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Spontaneity

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A spontaneous process is one that occurs naturally under certain conditions. A nonspontaneous process, on the other hand, will not take place unless it is “driven” by the continual input of energy from an external source. Processes have a natural tendency to occur in one direction under a given set of conditions. Water will naturally flow downhill (spontaneous process), but uphill flow (nonspontaneous process) requires outside intervention such as the use of a pump. Iron exposed to...
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Adhesion01:14

Adhesion

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Adhesion occurs when one type of molecule is attracted to a different molecule. Water exhibits adhesive properties in the presence of polar surfaces, such as glass or cellulose in plants. For instance, when water is poured into a glass, the positively charged hydrogen molecules of water are more attracted to the negatively charged oxygen molecules in the silica than to the oxygen in neighboring water molecules.
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Atomic Orbitals02:44

Atomic Orbitals

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An atomic orbital represents the three-dimensional regions in an atom where an electron has the highest probability to reside. The radial distribution function indicates the total probability of finding an electron within the thin shell at a distance r from the nucleus. The atomic orbitals have distinct shapes which are determined by l, the angular momentum quantum number. The orbitals are often drawn with a boundary surface, enclosing densest regions of the cloud.
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Intermolecular Forces03:13

Intermolecular Forces

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Atoms and molecules interact through bonds (or forces): intramolecular and intermolecular. The forces are electrostatic as they arise from interactions (attractive or repulsive) between charged species (permanent, partial, or temporary charges) and exist with varying strengths between ions, polar, nonpolar, and neutral molecules. The different types of intermolecular forces are ion–dipole, dipole–dipole, hydrogen bonds, and dispersion; among these, dipole–dipole, hydrogen...
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Measuring the Stiffness of Ex Vivo Mouse Aortas Using Atomic Force Microscopy
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Spontaneous oscillation in cell adhesion and stiffness measured using atomic force microscopy.

Hanna Sanyour1,2, Josh Childs1,2, Gerald A Meininger3

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This study introduces a new method using singular spectrum analysis (SSA) and fast Fourier transform (FFT) to analyze atomic force microscopy (AFM) data, enabling quantitative investigation of live cell dynamics.

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Area of Science:

  • Biophysics
  • Cell Biology
  • Materials Science

Background:

  • Atomic force microscopy (AFM) is valuable for studying live cell biomechanics and morphology.
  • Real-time AFM reveals spontaneous oscillations in cell stiffness and adhesion to the extracellular matrix (ECM).
  • Current limitations include a lack of automated methods for analyzing oscillatory signals and filtering noise in large AFM datasets.

Purpose of the Study:

  • To develop an automated analytical method for quantitative investigation of live cell dynamics using AFM.
  • To address the challenge of extracting oscillatory signals and filtering noise from AFM data.
  • To enhance the interpretation of dynamic characteristics in live cells.

Main Methods:

  • Singular Spectrum Analysis (SSA) was employed for filtering time-series cell adhesion and stiffness data.
  • Principal oscillatory components were isolated from noise using eigenvalues from the lagged-covariance matrix.
  • Fast Fourier Transform (FFT) was used to detect oscillatory parameters from noise-reduced data and construct sinusoidal components.

Main Results:

  • The developed method successfully filtered real-time AFM data, isolating key oscillatory signals.
  • Singular Spectrum Analysis effectively reduced noise, allowing for clearer identification of dynamic cellular behaviors.
  • Fast Fourier Transform accurately detected oscillatory parameters, enabling the construction of sinusoidal components.

Conclusions:

  • The combined SSA and FFT approach provides a robust method for quantitative analysis of live cell dynamics via AFM.
  • This technique overcomes limitations in automated signal extraction and noise filtering for AFM data.
  • The findings facilitate a deeper understanding of the dynamic mechanical properties of live cells.