Least-squares analysis of experimental data from the analytical ultracentrifuge is discussed in detail, with particular attention to the use of interference optics in studying nonideal self-associating macromolecular systems. Several samples are given that describe the application of the technique, the expected precision of the results, and some of its limitations. A FORTRAN IV computer program is available from the authors.

We introduce a methodology, fluorescence lifetime imaging (FLIM), in which the contrast depends on the fluorescence lifetime at each point in a two-dimensional image and not on the local concentration and/or intensity of the fluorophore. We used FLIM to create lifetime images of NADH when free in solution and when bound to malate dehydrogenase. This represents a challengi case for lifetime imaging because the NADH decay times are just 0.4 and 1.0 ns in the free and bound states, respectively. In the present apparatus, lifetimeimages are created from a series of phase-sensitive images obtained with a gain-modulated image intensifier and recorded with a charge-coupled device (CCD) camera. The intensifier gain is modulated at the light-modulation frequency or a harmonic thereof. A series of stationary phase-sensitive images, each obtained with various phase shifts of the ginmodulation signal, is used to determine the phase angle or modulation of the emission at each pixel, which is in essence the lifetime image. We also describe an imang procedure that allows speyific decay times to be suppressed, allowing in this case suppression of the emission from either free or bound NADH. Since the fluorescence lifetimes of probes are known to be sensitive to numerous chemical and physical factors such as pH, oxygen, temperature, cations, polarity, and binding to macromolecules, this method allows imaging of the chemical or property of interest in macroscopic and microscopic samples. The concept of FLIM appears to have numerous potential applications in the biosciences.The phenomenon of fluorescence is widely utilized for research in the biosciences. These applications have been focused on two divergent types of measurements, timeresolved fluorescence and fluorescence microscopy. In the former, one takes advantage of the high information content ofthe time-dependent fluorescence decays to uncover details about the structure and dynamics of macromolecules (1-3). Such measurements are performed almost exclusively by using picosecond laser sources coupled with high-speed photodetectors. In contrast, fluorescence microscopy, in combination with dyes, stains, fluorophores, or fluorophorelabeled antibodies, is most often used to determine the localization of species of interest, usually proteins or other macromolecules (4-6). The acquisition of two-dimensional (2D) fluorescence images is typically accomplished with low-speed accumulating detectors. Consequently, the high information content of time-resolved fluorescence is not usually available for studies of microscopic biological samples. This is particularly disadvantageous when one considers the sensitivity of fluorescence decay times to chemical and environmental factors of interest, such as local pH, cation concentration, oxygen, and polarity, to name a few.In the present report we combine measurements of fluorescence lifetimes with 2D imaging to create images in which the lifetimes at each pixel are used to create contrast in the images. While there have been reports...

Endocrine signaling provides one critical means of physiological communication within an organism. Many endocrine signals exhibit an episodic or pulsatile configuration. In an effort to provide a versatile and statistically based algorithm for investigating the regulation of endocrine pulse signals, we have formulated a computerized algorithm in which a pulse is defined as a statistically significant increase in a "cluster" of hormone values followed by a statistically significant decrease in a second cluster of values. The increase or decrease is judged in relation to the actual experimental error expressed by the replicates in the presumptive nadir and peak data clusters. The program permits the operator to specify the cluster sizes of test peaks and pre- and postpeak nadirs. This method is largely insensitive to unstable base-line hormone concentrations and is not adversely affected by varying pulse amplitudes, widths, or configurations within the endocrine series. In addition, the simple statistical basis for this algorithm renders it minimally dependent on explicit or a priori assumptions about rates of hormone secretion or disappearance. The program has been validated for false-positive errors against a wide range of intraseries coefficients of variation (4-52%). We have illustrated its performance for profiles of luteinizing hormone, follicle-stimulating hormone, growth hormone, prolactin, adrenocorticotropic hormone, and cortisol and compared these episodic patterns with those of stable serum constituents (total serum protein and calcium), which do not exhibit pulsatile fluctuation.

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