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Total Internal Reflection Fluorescence

Axelrod, D, Burghardt, T P, Thompson, N L·1984·Annual Review of Biophysics and Bioengineering

Abstract

Total internal reflection fluorescence (TIRF) is an optical effect particularly well-suited to the study of molecular and cellular phenomena at liquid/solid interfaces. Such interfaces are central to a wide range of biochemical and biophysical processes: binding to and triggering of ceils by hormones, neurotransmitters, and antigens; blood coagulation at foreign surfaces; electron transport in the mitochondrial membrane; adherence and mo­bility of bacteria, algae, and cultured animal cells to surfaces; and possible enhancement of reaction rates with cell surface receptors upon nonspecific adsorption and surface diffusion of an agonist. Liquid/solid interfaces also have important medical and industrial applications: e.g. detection of serum antibodies by surface immobilized antigens; and the manufacture of biochemical products by surface-immobilized enzymes. Total internal reflection spectroscopy for optical absorption studies (called attenuated total reflection or ATR) was developed somewhat earlier than the fluorescence applications and has been widely used in surface

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Metadata

Authors
Axelrod, D., Burghardt, T. P., & Thompson, N. L.
Venue
Annual Review of Biophysics and Bioengineering
Published
1984-06
Volume
13
Issue
1
Pages
247-268
ISSN
0084-6589 (ISSN-L)
OpenAlex
W2096963388
Cited by
741
References
0
FWCI
8.29
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Total Internal Reflection Fluorescence. https://app.cochat.ai/papers/10.1146/annurev.bb.13.060184.001335
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Axelrod, D., Burghardt, T. P., & Thompson, N. L. (1984). Total Internal Reflection Fluorescence. Annual Review of Biophysics and Bioengineering. https://doi.org/10.1146/annurev.bb.13.060184.001335

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.