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PubMed2006

Resampling and deconvolution of linear time-of-flight records for enhanced protein profiling.

We have developed a peak deconvolution strategy that is applicable to the full mass range of a time-of-flight (TOF) spectrum. This strategy involves resampling a spectrum to create a time series that has equal peak widths (in time) across the entire spectrum, and then using the deconvolution filters we have previously described. We use this technique to deconvolve the protein mass spectra for blood serum and cell lysates acquired on three separate TOF instruments. Following deconvolution, we resolve spectral structures consistent with expected events such as multiply charged ions, matrix adducts and post-translational protein modifications. The deconvolution procedure produces a 40% improvement in the resolution and enhanced experimental sensitivity over the full length of the linear TOF record, up to m/z 150 000. This approach is particularly appropriate for automated data analysis and peak detection in dense TOF spectra.

Algorithms↗
PubMed1999

Three-dimensional imaging by deconvolution microscopy.

Deconvolution is a computational method used to reduce out-of-focus fluorescence in three-dimensional (3D) microscope images. It can be applied in principle to any type of microscope image but has most often been used to improve images from conventional fluorescence microscopes. Compared to other forms of 3D light microscopy, like confocal microscopy, the advantage of deconvolution microscopy is that it can be accomplished at very low light levels, thus enabling multiple focal-plane imaging of light-sensitive living specimens over long time periods. Here we discuss the principles of deconvolution microscopy, describe different computational approaches for deconvolution, and discuss interpretation of deconvolved images with a particular emphasis on what artifacts may arise.

Artifacts↗
PubMed1999

Deconvolution of impulse response in event-related BOLD fMRI.

The temporal characteristics of the BOLD response in sensorimotor and auditory cortices were measured in subjects performing finger tapping while listening to metronome pacing tones. A repeated trial paradigm was used with stimulus durations of 167 ms to 16 s and intertrial times of 30 s. Both cortical systems were found to be nonlinear in that the response to a long stimulus could not be predicted by convolving the 1-s response with a rectangular function. In the short-time regime, the amplitude of the response varied only slowly with stimulus duration. It was found that this character was predicted with a modification to Buxton's balloon model. Wiener deconvolution was used to deblur the response to concatenated short episodes of finger tapping at different temporal separations and at rates from 1 to 4 Hz. While the measured response curves were distorted by overlap between the individual episodes, the deconvolved response at each rate was found to agree well with separate scans at each of the individual rates. Thus, although the impulse response cannot predict the response to fully overlapping stimuli, linear deconvolution is effective when the stimuli are separated by at least 4 s. The deconvolution filter must be measured for each subject using a short-stimulus paradigm. It is concluded that deconvolution may be effective in diminishing the hemodynamically imposed temporal blurring and may have potential applications in quantitating responses in eventrelated fMRI.

Acoustic Stimulation↗
PubMed1989

An inequality-constrained least-squares deconvolution method.

The output-function (Y) of a linear system is the convolution of the input function (I) to the system with the disposition-function (H) of the system. Given Y and H deconvolution yields I. A non-parametric method for numerical deconvolution is described. The method is based on an inequality-constrained least-squares criterion and approximates I by a discontinuous function. No assumptions are made about the form of H or Y. Numerical stability and physical realism are obtained by constraining the estimated I to be nonnegative and piecewise-monotonic (nonincreasing, nondecreasing, or alternating segments of both). When I is constrained to be monotonic, the deconvolution yields a staircase function. The method can be used to calculate drug input rates. It is compared to previously published deconvolution methods for this purpose, using simulated data and real theophylline and pentobarbital data.

Models, Theoretical↗
PubMed1991

Analyzing pulsatile endocrine data in patients with chronic renal failure: a brief review of deconvolution techniques.

Deconvolution analysis provides an important new technique to evaluate underlying hormone secretory rates quantitatively based upon serially measured plasma hormone concentrations with or without prior knowledge of the half-time of hormone disappearance from the blood. Information about endocrine gland secretion is particularly important in chronic renal failure, wherein the decreased metabolic clearance rates of various hormones would otherwise confound the interpretation of plasma hormone concentrations. Here we review two particularly useful techniques of deconvolution, one of which is a waveform-defined algorithm and the other waveform independent. The first method can be used to estimate both hormone half-life and secretory rates in vivo. The second methodology allows calculation of in vivo hormone secretion rates without assuming any special form for the secretion event, but requires a priori knowledge of hormone half-life. We illustrate examples of these two deconvolution approaches, and discuss why the interpretations of hormone concentration measurements in earlier studies (where deconvolution methods were not employed) must be viewed with caution. Based on such considerations, additional investigations of in vivo hormone secretory pathophysiology will be required in children and adults with chronic renal failure.

Endocrine Glands↗
PubMed2006

Assessment of the gastric emptying velocity by the 13C-octanoate breath test: deconvolution versus a Wagner-Nelson analysis.

BACKGROUND: The dynamic change in gastric emptying on a minute-by-minute basis (gastric velocity) is evaluated by the 13C-octanoate breath test with deconvolution analysis. However, deconvolution is impractical, because it requires dual experiments to obtain 13CO2 excretion profiles following intraduodenal and oral administration of 13C-octanoate. We investigated whether the Wagner-Nelson method, used in drug absorption studies, can determine the velocity profile based on a single experiment as accurately as deconvolution, and whether the velocity assessed by the Wagner-Nelson method is sensitive enough to detect subtle changes in gastric emptying induced by butylscopolamine. METHODS: Five male volunteers underwent a 4-h breath test twice, after intraduodenal administration of 20 ml normal saline containing 100 mg 13C-octanoate and after ingestion of a 320-kcal muffin containing 100 mg 13C-octanoate. Deconvolution determined the velocity profile by subtracting duodenal from oral data, and the Wagner-Nelson method produced it from only oral data. The velocity profiles were compared between the two methods. Another six male subjects underwent the breath test by ingesting a muffin twice, once with and once without 20 mg oral butylscopolamine. The velocity profiles generated by the Wagner-Nelson analysis and the conventional 13CO2 excretion curves were compared between the two occasions. RESULTS: The two techniques yielded identical velocity profiles. The velocity profile detected a significant change in the emptying pattern induced by butylscopolamine (initial acceleration with subsequent deceleration), while the conventional breath curves failed to detect this change. CONCLUSIONS: Velocity assessment by a Wagner-Nelson analysis can precisely describe altered gastric emptying, based on a single experiment.

Adult↗
PubMed2005

Wavelet-based noise reduction for improved deconvolution of time-series data in dynamic susceptibility-contrast MRI.

Dynamic susceptibility-contrast (DSC) MRI requires deconvolution to retrieve the tissue residue function R(t) and the cerebral blood flow (CBF). In this study, deconvolution of time-series data was performed by wavelet-transform-based denoising combined with the Fourier transform (FT). Traditional FT-based deconvolution of noisy data requires frequency-domain filtering, often leading to excessive smoothing of the recovered signal. In the present approach, only a low degree of regularisation was employed while the major noise reduction was accomplished by wavelet transformation of data and Wiener-like filtering in the wavelet space. After inverse wavelet transform, the estimate of CBF.R(t) was obtained. DSC-MRI signal-versus-time curves (signal-to-noise ratios 40 and 100) were simulated, corresponding to CBF values in the range 10-60 ml/(min 100 g). Three shapes of the tissue residue function were investigated. The technique was also applied to six volunteers. Simulations showed CBF estimates with acceptable accuracy and precision, as well as independence of any time shift between the arterial input function and the tissue concentration curve. The grey-matter to white-matter CBF ratio in volunteers was 2.4+/-0.2. The proposed wavelet/FT deconvolution is robust and can be implemented into existing perfusion software. CBF maps from healthy volunteers showed high quality.

Adult↗
PubMed1982

Differential-wavelength deconvolution of time-resolved fluorescence intensities. A new method for the analysis of excited-state processes.

We describe a new procedure for the analysis of time-resolved decays of fluorescence intensity observed for excited-state reactions. This procedure is particularly valuable because it simplifies both determination of the rate constants of excited-state reactions and calculation of the emission spectra of the unreacted and the reacted species. These advantages are obtained without additional data acquisition, by the further analysis of data which would already be collected. As is usual for an excited-state process, time-resolved decays of fluorescence intensity are collected at wavelengths across the emission spectrum. Generally, one derives analytical expressions for the impulse response by deconvolution using the time profile of the exciting pulse. We suggest that in addition to the procedure just described, the response observed at longer wavelengths be deconvolved using the response observed on the blue side of the emission. Typically, this emission is from the initially excited state of the fluorophore (F). Then, the derived decay time is the decay rate of the reacted species (R). In addition, spectral overlap of the F and R states is revealed quantitatively as an apparent zero-decay-time component in the derived impulse response function. This is because the population of the initially excited state is considered to be the excitation function. This spectral overlap component is easily quantified, and allows the emission spectra of the F and R states to be calculated. This deconvolution procedure requires one favorable circumstance, which is the ability to choose a wavelength at which only the initially excited state is emitting. We tested our procedure on the excited state protonation of acridine and the excited-state deprotonation of 2-naphthol. The former reaction is essentially irreversible, whereas depending upon pH the dissociation of 2-naphthol can be reversible. We demonstrated that this procedure, which we call differential-wavelength deconvolution, revealed the individual spectra and simplified determination of the kinetic constants from the time-resolved decays. Without differential-wavelength deconvolution considerably more complex methods are required. We expect this procedure to greatly facilitate the use of pulse fluorometry methods in the analysis of excited-state processes.

Acridines↗
PubMed2002

Peak deconvolution in one-dimensional chromatography using a two-way data approach.

A deconvolution methodology for overlapped chromatographic signals is proposed. Several single-wavelength chromatograms of binary mixtures, obtained in different runs at diverse concentration ratios of the individual components, were simultaneously processed (multi-batch approach), after being arranged as two-way data. The chromatograms were modelled as linear combinations of forced peak profiles according to a polynomially modified Gaussian equation. The fitting was performed with a previously reported hybrid genetic algorithm with local search, leaving all model parameters free. The approach yielded more accurate solutions than those found when each experimental chromatogram was fitted independently to the peak model (single-batch approach). The improvement was especially significant for those chromatograms where the peaks were severely affected by the tails of the preceding compounds. Peak shifts among chromatograms, which are a usual source of non-bilinearity, were modelled in a continuous domain instead of in a discrete way, which avoided some drawbacks associated with latent variable methods. An experimental design involving simulated chromatograms was applied to check the method performance. Five main factors affecting the deconvolution were examined: concentration pattern, chromatographic resolution, number of batches and replicates, and noise level, which were evaluated using first- and second-order figures of merit. The method was also tested on three real samples containing compounds showing different overlap. Four multi-batch deconvolution methods were considered differing in the nature of the processed information and kind of peak matching among chromatograms. In all cases, the multi-batch deconvolution yielded better performance than the single-batch approach.

Chromatography↗
PubMed2003

Net analyte signal as a deconvolution-oriented resolution criterion in the optimisation of chromatographic techniques.

The performance of two multivariate calibration measurements, multivariate selectivity (SEL(s)) and scalar net analyte signal (scalar NAS), as chromatographic objective functions (COFs), was investigated. Since both assessments are straightforwardly related to the quantification of analytes in the presence of interferents, they were expected to confer new features in the optimisation of compound resolution, not present in conventional assessments. These capabilities are especially interesting in situations of low resolution, where peak deconvolution becomes an attractive alternative. For comparison purposes, chromatographic resolution (R(s)) and peak purity (p(s)) were used as reference COFs. In order to correlate COFs with the probability of deconvolution error, an artificial peak crossing was used to generate 73 different peak arrangements, which were deconvolved using three different methods. SEL(s) exhibited the best correlation, which allowed predicting properly the risk of obtaining inaccurate deconvolutions. The optimisation of a poorly resolved mixture of 16 aromatic compounds by reversed-phase liquid chromatography with methanol-water and acetonitrile-water mobile phases was examined to investigate the differences in performance among the resolution criteria. In situations like these, SEL(s) tends to consider acceptable mobile phase compositions with partial coelution, which permits however the deconvolution with low errors. In contrast, p(s) selects compositions where the resolution of some compounds is sacrificed to enhance the separation of others. Scalar NAS was not so favourable as expected, since it depends on sampling frequency and peak widening. SEL(s) was not affected by these factors.

Acetonitriles↗
PubMed1999

Evaluation of quantal neurosecretion from evoked and miniature postsynaptic responses by deconvolution method.

A new deconvolution algorithm has been developed for evaluation of quantal content and its variability at high-output synapses. The algorithm derives the distribution of the number of neurosecretory quanta released in a trial (M) from the measured sizes of evoked postsynaptic responses. The deconvolution employs the distribution of quantal sizes obtained by measuring sizes of miniature postsynaptic responses. The distribution of quantal content M is derived by ridge regression method from the distributions of sizes of the responses and of quantal sizes. The deconvolution method was applied to postsynaptic responses from the excitory innervation of lobster dactyl opener muscle obtained by focal extracellular recordings. The obtained solution (distribution of M) had six to eight components and was stable. The method was tested by the analysis of simulated multiquantal responses. For the simulated responses, the ridge regression solution reproduced the imposed distribution of M within the limits of the calculated confidence intervals. To further test the algorithm, the distribution of M at a low-output synapse was obtained both by deconvolution method and by the method of direct quantal counts. The results of these two methods were found to be in a very good agreement.

Action Potentials↗
PubMed1997

Estimation of endogenous glucose production after a glucose perturbation by nonparametric stochastic deconvolution.

The knowledge of the time course of endogenous glucose production (EGP) after a glucose perturbation is crucially important for understanding the glucose regulation system in both healthy and disease (e.g. diabetes) states. EGP is not directly accessible, and thus an indirect measurement approach is required. The estimation of EGP during an intravenous glucose tolerance test (IVGTT) can be posed as an input estimation problem solvable as a Fredholm integral equation of the first kind (A. Caumo and C. Cobelli, Am. J. Physiol., 264 (1993) E829-E841). The time-varying model of the kernel of the glucose system was identified from a concomitant tracer experiment, and EGP was reconstructed by employing the Phillips-Tikhonov regularization (deconvolution) algorithm. However, the proposed deconvolution approach left some issues open, e.g. how to choose the amount of regularization and how to deal with nonuniform/infrequent sampling. Here, a solution to these problems is provided by resorting to a new deconvolution algorithm. Thanks to the stochastic embedding into which the new deconvolution method is stated, the amount of regularization is determined in a statistically sound manner. In addition, in face of infrequent sampling, a time continuous profile of EGP is obtained. The method is shown to work reliably for reconstructing EGP in different IVGTT experimental protocols, both in normal and disease states.

Algorithms↗
PubMed1997

Deconvolution process in measurement of arterial velocity profiles via an ultrasonic pulsed Doppler velocimeter for evaluation of the wall shear rate.

A numerically based simulation of pulsed Doppler ultrasound convolution and deconvolution of theoretical hemodynamic velocity profiles yields two major conclusions on performing a deconvolution process. First, the most important parameter to be accounted for is the size of the sample volume. Second, a deconvolution process with an overestimated sample volume size is revealed by high-frequency noise on the resulting profile. A deconvolution process is presented for in vivo arterial velocity profiles, which has the advantage of being systematic and not needing experimental testing for determining the size or the shape of the sample volume. It is also independent of the observation angle. Finally, an example of an application to in vivo human velocity profiles is given. Evaluation of the wall shear rate from the corrected deconvolved profiles shows a noticeable improvement with respect to that using the directly convolved Doppler profiles.

Arteries↗
PubMed1998

A universal algorithm for fast and automated charge state deconvolution of electrospray mass-to-charge ratio spectra.

This article describes a new algorithm for charge state determination and deconvolution of electrospray ionization (ESI) mass-to-charge ratio spectra. The algorithm (ZSCORE) is based on a charge scoring scheme that incorporates all above-threshold members of a family of charge states or isotopic components, and deconvolves both low- and high-resolution mass-to-charge ratio spectra, with or without a peak list (stick plot). A scoring weight factor, log (I/I0), in which I is the signal magnitude at a calculated mass-to-charge ratio, and I0 is the signal threshold near that mass-to-charge ratio, was used in most cases. For high-resolution mass-to-charge ratio spectra in which all isotopic peaks are resolved, the algorithm can deconvolve overlapped isotopic multiplets of the same or different charge state. Compared to other deconvolution techniques, the algorithm is robust, rapid, and fully automated (i.e., no user input during the deconvolution process). It eliminates artifact peaks without introducing peak distortions. Its performance is demonstrated for experimental ESI Fourier transform ion cyclotron resonance mass-to-charge ratio spectra (both low and high resolution). Charge state deconvolution to yield a "zero-charge" mass spectrum should prove particularly useful for interpreting spectra of complex mixtures, identifying contaminants, noncovalent adducts, fragments (N-terminal, C-terminal, internal), and chemical modifications of electrosprayed biomacromolecules.

Algorithms↗
PubMed1988

Metabolite formation pharmacokinetics: rate and extent of metabolite formation determined by deconvolution.

A two-step analytic procedure to determine the rate and extent of metabolite production following administration of the parent compound is described. The procedure provides the rate and extent of metabolite production as a function of time by application of the general model independent approach of deconvolution. The metabolite unit impulse response function is obtained by implicit deconvolution of the metabolite data with a truncated constant-rate metabolite input function. Then the obtained unit impulse response function is used in an analytic deconvolution with metabolite data following administration of the parent compound to obtain the rate and extent of metabolite production. The input function is also deconvolved with metabolite data to obtain the unit impulse response function appropriate for prediction of metabolite levels given a selected input of parent compound. The expected profile following administration of the consecutive infusions of parent drug is shown for both parent and metabolite. The rationale for selection of deconvolution methods is discussed. The approach is applied to data for procainamide and N-acetylprocainamide from three human subjects. The results indicate that from 27 to 39% of the procainamide was converted to N-acetylprocainamide in these subjects.

Acecainide↗
PubMed1990

Obtaining meaningful results from Fourier deconvolution of reaction time data.

The technique of Fourier deconvolution is a powerful tool for testing distributional predictions of stage models of reaction time. However, direct application of Fourier theory to reaction time data has sometimes produced disappointing results. This article reviews Fourier transform theory as it applies to the problem of deconvolving a component of the reaction time distribution. Problems encountered in deconvolution are shown to be due to the presence of noise in the Fourier transforms of the sampled distributions, which is amplified by the operation of deconvolution. A variety of filtering techniques for the removal of noise are discussed, including window functions, adaptive kernel smoothing, and optimal Wiener filtering. The best results were obtained using a window function whose pass band was determined empirically from the power spectrum of the deconvolved distribution. These findings are discussed in relation to other, nontrigonometric approaches to the problem of deconvolution.

Computer Simulation↗
PubMed1984

Secondary structural changes in globular protein induced by a surfactant: Fourier self-deconvolution of FT-IR spectra.

Conformational changes in ovalbumin, a globular protein, induced by an anionic surfactant, sodium dodecyl sulfate (SDS), have been monitored by an FT-IR spectrometer using ZnSe cylindrical internal reflection optics which allows high quality IR spectra to be obtained in water solution. The most notable change, on addition of SDS, occurs in the composite band of the Amide I absorption band and the vibrational frequency of the composite C = O bond shifts from 1639 cm-1 to 1652 cm-1. On the other hand, the position of the Amide II band remains fairly unchanged. Comparison of the various peak positions in the deconvoluted spectra for the native protein and the perturbed protein clearly shows the effect of SDS on the secondary structures of the protein. SDS unfolds the protein. It increases the helix content slightly. More importantly, it alerts the beta sheet structure, destroying it almost completely in the Amide I region, while retaining it in its neighbourhood. In the deconvoluted spectra of the perturbed protein, a band at 1531 cm-1 indicates generation of some beta turns. We used the second derivative of the deconvoluted spectra for fixing positions of minor peaks and shoulders. The results of this study indicate that the deconvolution of the normal IR spectra, consisting of composite bands, provides evidence for the specific secondary structures in a protein and for the way they are affected by changes in the environment, e.g., the addition of SDS. This makes it possible to relate conformational changes to specific secondary structures.

Fourier Analysis↗
PubMed1994

A deconvolution method for evaluating indicator-dilution curves.

Characteristics of blood flow in tissue can be measured by administering an intravascular tracer and then deconvolving and analysing the resulting indicator-dilution curves. Existing deconvolution methods are not typically generalizable to a variety of tissues. The authors have developed a more general deconvolution method using simulated indicator-dilution data. This method involves filtering the Fourier transform of indicator-dilution data with a modification of the Wiener filter, an adaptive deconvolution filter. Unlike the Wiener filter, this adaptive filter requires no previous knowledge of the noise frequency spectrum; it is derived by varying the magnitude of the noise spectrum until the oscillations in the deconvolved data fall below an optimal value. The optimal value corresponds to the setting of the noise spectrum that allows the most accurate and precise measurement of vascular characteristics from deconvolved data. Vascular characteristics measured in brain tissues using this deconvolution method on actual indicator-dilution data were similar to established values. It should be possible to use this method on time-concentration data collected from a variety of tissues using a number of different tracer measurement techniques, thereby allowing the accurate characterization of vascular physiology.

Algorithms↗