Related Experiment Video

Updated: Jan 31, 2026

Super-Resolution Live Cell Imaging of Subcellular Structures
06:50

Super-Resolution Live Cell Imaging of Subcellular Structures

Published on: January 13, 2021

5.3K

Correlative Live-Cell Imaging and Super-Resolution Microscopy of Autophagy

Eleftherios Karanasios1

  • 1Department of Basic and Clinical Neuroscience, Institute of Psychiatry, Psychology and Neuroscience, King's College London, Maurice Wohl Clinical Neuroscience Institute, London, UK.

Methods in Molecular Biology (Clifton, N.J.)
|January 6, 2019
PubMed

Keywords:
AutophagosomeAutophagyEndoplasmic reticulumHEK293Membrane traffickingSuper-resolution microscopyTime-lapse fluorescence microscopydSTORM

More Related Videos

Correlative Super-resolution and Electron Microscopy to Resolve Protein Localization in Zebrafish Retina12:28

Correlative Super-resolution and Electron Microscopy to Resolve Protein Localization in Zebrafish Retina

Published on: November 10, 2017

9.9K
Conventional BODIPY Conjugates for Live-Cell Super-Resolution Microscopy and Single-Molecule Tracking07:49

Conventional BODIPY Conjugates for Live-Cell Super-Resolution Microscopy and Single-Molecule Tracking

Published on: June 8, 2020

8.8K

Related Concept Videos

Super-resolution Fluorescence Microscopy01:37

Super-resolution Fluorescence Microscopy

Super-resolution fluorescence microscopy (SRFM) provides a better resolution than conventional fluorescence microscopy by reducing the point spread function (PSF). PSF is the light intensity distribution from a point that causes it to appear blurred. Due to PSF, each fluorescing point appears bigger than its actual size, and it is the PSF interference of nearby fluorophores that causes the blurred image. Various approaches to achieving higher resolution through SRFM have recently been...
14.5K
Correlations02:20

Correlations

Correlation means that there is a relationship between two or more variables (such as ice cream consumption and crime), but this relationship does not necessarily imply cause and effect. When two variables are correlated, it simply means that as one variable changes, so does the other. We can measure correlation by calculating a statistic known as a correlation coefficient. A correlation coefficient is a number from -1 to +1 that indicates the strength and direction of the relationship between...
35.9K
Autophagy01:27

Autophagy

Autophagy is a self-digesting process by which a cell protects itself from threats both within and outside the cell, ranging from abnormal proteins to invading bacteria. In this process, obsolete components of the cell and invading microbes are degraded by hydrolytic enzymes active in an acidic environment of the lysosomal lumen.
An autophagic pathway consists of a series of signaling events activated in response to diverse stress and physiological conditions such as food deprivation,...
5.8K
Correlation and Causation01:27

Correlation and Causation

Statistical tests can calculate whether there is a relationship, or correlation, between independent and dependent variables. An indirect relationship of the variables signifies a correlation, while a direct relationship shows causation. If it is determined that no connection exists between the variables, then the correlation is a coincidence.
Correlation versus Causation
If the dependent variable increases or decreases when the independent variable increases, there is a positive or negative...
42.5K
Correlation01:09

Correlation

In statistics, two variables are said to be correlated if the values of one variable are associated with the other variable. Depending on the relationship between two variables, correlation can be of three types– positive correlation, negative correlation, and zero correlation.
Two variables, for example, a and b, are said to be positively correlated if both variables move in the same direction. In other words, a positive correlation exists between two variables, a and b, if:
15.1K
Correlation and Regression00:53

Correlation and Regression

In statistics, correlation describes the degree of association between two variables. In the subfield of linear regression, correlation is mathematically expressed by the correlation coefficient, which describes the strength and direction of the relationship between two variables. The coefficient is symbolically represented by 'r' and ranges from -1 to +1. A positive value indicates a positive correlation where the two variables move in the same direction. A negative value suggests a...
3.4K