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Magnification Mismatches Between Micrographs: Corrective Procedures and Implications for Structural Analysis

A. Aldroubi, B.L. Trus, M. Unser, F.P. Booy, A.C. Steven

Ultramicroscopy, vol. 46, no. 1-4, pp. 175-188, October 1992.

Quantitative structural analysis from electron micrographs of biological macromolecules inevitably requires the synthesis of data from many parts of the same micrograph and, ultimately, from multiple micrographs. Higher resolutions require the inclusion of progressively more data, and for the particles analyzed to be consistent to within ever more stringent limits. Disparities in magnification between micrographs or even within the field of one micrograph, arising from lens hysteresis or distortions, limit the resolution of such analyses. A quantitative assessment of this effect shows that its severity depends on the size of the particle under study: for particles that are 100 nm in diameter, for example, a 2% discrepancy in magnification restricts the resolution to approximately 5 nm. In this study, we derive and describe the properties of a family of algorithms designed for cross-calibrating the magnifications of particles from different micrographs, or from widely differing parts of the same micrograph. This approach is based on the assumption that all of the particles are of identical size: thus, it is applicable primarily to cryo-electron micrographs in which native dimensions are precisely preserved. As applied to icosahedral virus capsids, this procedure is accurate to within 0.1-0.2%, provided that at least five randomly oriented particles are included in the calculation. The algorithm is stable in the presence of noise levels typical of those encountered in practice, and is readily adaptable to non-isometric particles. It may also be used to discriminate subpopulations of subtly different sizes.

AUTHOR="Aldroubi, A. and Trus, B.L. and Unser, M. and Booy, F.P. and
        Steven, A.C.",
TITLE="Magnification Mismatches Between Micrographs: {C}orrective
        Procedures and Implications for Structural Analysis",

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