Quantitative electron microscope autoradiography: application of multiple linear regression analysis.
A new method for the analysis of high resolution EM autoradiographs is described. It identifies labelled cell organelle profiles in sections on a strictly statistical basis and provides accurate estimates for their radioactivity without the need to make any assumptions about their size, shape and spatial arrangement. The radioactivity in interfacial membranes and transitional junctional regions between pairs of adjoining cell structures can be determined without any additional measurements. The uniformity of internal labelling of large cell organelles can be also assessed. Correcting for cross-fire does not need any predictive information from a frequency distribution function describing the image spread about a radioactive point source. Instead, the section area is subdivided into regions in such a way that each region with cross-fired silver grains over it includes also the sites of the radioactive disintegrations that have produced them. The method is based on the quantitative regression relationship between the number of developed silver grains overlying any given region and the size of the cell organelle profiles included. A transparent overlay screen bearing a regular array of circles and a point-counting procedure are applied to divide the section area into regions and to measure their area and the size of the cell organelle profiles. The least squares method is used for the simple and rapid calculation of specific activity estimates and exact standard errors to be attached to them. A modest computing facility and a standard library program are required. Simulation modelling and analysis of residuals were used to lend support to the validity of the method.
D000818:Animals; D001345:Autoradiography / Q000379:methods*; D001370:Axonal Transport; D004372:Ducks; D008465:Mechanoreceptors / Q000502:physiology / Q000648:ultrastructure; D008854:Microscopy, Electron / Q000379:methods*; D009475:Neurons, Afferent / Q000648:ultrastructure*; D011506:Proteins; D012044:Regression Analysis; D014276:Trigeminal Nerve / Q000502:physiology / Q000648:ultrastructure
D011506:Proteins