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PubMed2025

Continuous DNA Methylation Deconvolution-Based Surrogate for B-Cell Differentiation State in CLL.

Chronic Lymphocytic Leukemia (CLL) is clinically divided into IGHV mutated (M-CLL) and IGHV unmutated (U-CLL) subtypes, which are thought to arise from distinct cells of origin along the B-cell differentiation pathway. We measured genome-scale DNA methylation in purified CLL samples ( n = 89) and utilized reference-based cell deconvolution techniques to develop a continuous metric of epigenetic similarity across a B-naive-like to B-memory-like scale (B-Index). B-Index accurately classifies CLL into clinical subtypes (98.8%), has a stronger epigenetic signal than IGHV gene percent identity, and demonstrates additional epigenetic signal within the M-CLL subgroup. We demonstrate that U-CLL is epigenetically more similar to B-memory than B-naive cells and reconcile previous reports of a B-naive-like epigenetic signal. The B-memory-like program of U-CLL is enriched for binding sites of transcription factors related to the germinal center activation pathway. Our findings provide epigenetic evidence for discerning CLL mechanisms of initiation and cell of origin. We also identified an epigenetic signal associated with tumor burden, which may have some relation to viral infections such as Epstein-Barr-Virus. Our cell-type deconvolution-based approach to developing a continuous metric for CLL epigenetic differentiation state can be applied to other tumors with multiple subtypes across differentiation stages.

B-memory-like↗
PubMed1987

Evaluation of in vivo drug release by numerical deconvolution using oral solution data as weighting function.

Determination of in vivo drug release using compartmental model analysis is hampered by problems such as flip-flop phenomena and vanishing exponential terms. The usefulness of numerical deconvolution to estimate in vivo drug release was evaluated in this study by means of simulated data comparing solid dosage forms with a solution as a reference standard. Concentration-time data were generated using the standard linear two-compartment body model with various first-order release and absorption rate constants. Random errors of 5 and 10% were added to data sets for further analysis. The results of the study using error-free data afforded excellent agreement with the theoretical values except in one case where the release rate constant was overestimated by 6%. When random error was added to the data, the resulting in vivo release profile showed considerable fluctuation and no single rate constant could be assigned. However, further analysis showed that the method does not create additional error during the calculating process, as previously suggested, but merely reflects the inherent error added to the raw data. If the raw data are poor, no useful information can be obtained without using an arbitrary technique such as smoothing or fitting. In this regard, the time course of drug release obtained after numerical deconvolution merits investigation.

Absorption↗
PubMed1989

Numerical stability of pharmacokinetic deconvolution algorithms.

The sensitivity of pharmacokinetic deconvolution algorithms with respect to simulated experimental error has been studied. Approximations of cumulative absorption profiles reconstructed from simulated data sets with normally distributed random error were compared with corresponding known input functions. The coincidence of both functions was assessed in 600 numerical experiments by the nonparametric Kolmogorov-Smirnov test. A constrained iterative nonlinear regression procedure based on the analytical convolution of multiphasic zero-order input functions with linear disposition models was found to perform well under conditions where the results of direct numerical deconvolution and model-based mass balance methods were unsatisfactory.

Absorption↗
PubMed1992

Adaptive computer program for determination of absorption profiles by numerical deconvolution: application to amoxicillin absorption.

We have developed a specific numerical deconvolution program for the Apple Macintosh microcomputer. After comparison with other methods, we used the program to evaluate the influence of nifedipine on the absorption and bioavailability of amoxicillin. The technique provided a model-independent approach. This study shows that the simultaneous administration of nifedipine with amoxicillin leads to a significant increase in both the total quantity of amoxicillin absorbed (+22%) and the rate of absorption. Parameters of clearance, volume of distribution, and elimination were unaffected. Numerical deconvolution analysis showed that nifedipine did not modify the absorption kinetics of amoxicillin, which are characterized by a lag time followed by a constant rate of absorption, suggesting zero-order kinetics with first-order kinetics at the end of the process. The results suggest the existence of a specialized, saturable transport molecule for this antibiotic.

Adult↗
PubMed1992

Differentiation between transmembrane helices and peripheral helices by the deconvolution of circular dichroism spectra of membrane proteins.

The interpretation of the circular dichroism (CD) spectra of proteins to date requires additional secondary structural information of the proteins to be analyzed, such as X-ray or NMR data. Therefore, these methods are inappropriate for a CD database whose secondary structures are unknown, as in the case of the membrane proteins. The convex constraint analysis algorithm (Perczel, A., Hollósi, M., Tusnády, G., & Fasman, G. D., 1991, Protein Eng. 4, 669-679), on the other hand, operates only on a collection of spectral data to extract the common spectral components with their spectral weights. The linear combinations of these derived "pure" CD curves can reconstruct the original data set with great accuracy. For a membrane protein data set, the five-component spectra so obtained from the deconvolution consisted of two different types of alpha helices (the alpha helix in the soluble domain and the alpha T helix, for the transmembrane alpha helix), a beta-pleated sheet, a class C-like spectrum related to beta turns, and a spectrum correlated with the unordered conformation. The deconvoluted CD spectrum for the alpha T helix was characterized by a positive red-shifted band in the range 195-200 nm (+95,000 deg cm2 dmol-1), with the intensity of the negative band at 208 nm being slightly less negative than that of the 222-nm band (-50,000 and -60,000 deg cm2 dmol-1, respectively) in comparison with the regular alpha helix, with a positive band at 190 nm and two negative bands at 208 and 222 nm with magnitudes of +70,000, -30,000, and -30,000 deg cm2 dmol-1, respectively.

Adenosine Triphosphatases↗
PubMed1988

The appended curve technique for deconvolutional analysis--method and validation.

Deconvolutional analysis (DCA) is useful in correction of organ time activity curves (response function) for variations in blood activity (input function). Despite enthusiastic reports of applications of DCA in renal and cardiac scintigraphy, routine use has awaited an easily implemented algorithm which is insensitive to statistical noise. The matrix method suffers from the propagation of errors in early data points through the entire curve. Curve fitting or constraint methods require prior knowledge of the expected form of the results. DCA by Fourier transforms (FT) is less influenced by single data points but often suffers from high frequency artifacts which result from the abrupt termination of data acquisition at a nonzero value. To reduce this artifact, we extend the input (i) and response curves to three to five times the initial period of data acquisition (P) by appending a smooth low frequency curve with a gradual taper to zero. Satisfactory results have been obtained using a half cosine curve of length 2-3P. The FTs of the input and response I and R, are computed and R/I determined. The inverse FT is performed and the curve segment corresponding to the initial period of acquisition (P) is retained. We have validated this technique in a dog model by comparing the mean renal transit times of 131I-iodohippuran by direct renal artery injection to that calculated by deconvolution of an intravenous injection. The correlation was excellent (r = 0.97, P less than 0.005). The extension of the data curves by appending a low frequency "tail" before DCA reduces the data termination artifact. This method is rapid, simple, and easily implemented on a microcomputer.(ABSTRACT TRUNCATED AT 250 WORDS)

Animals↗
PubMed1985

Deconvolution applied to the kinetics of extracorporal drug removal. Haemodialysis of cefsulodin.

A novel approach to the evaluation of the kinetics of drug removal by an extracorporal device (ECD), e.g., haemodialysis, haemofiltration, and haemoperfusion, is presented. The rate and extent of extracorporal drug removal (ECR) are determined by deconvolution. The proposed method is model independent in the sense that no specific models of corporal or extracorporal disposition are required. The estimation of various derived functions and parameters useful for describing ECR such as clearance and fractional drug removal are facilitated by the technique. The kinetics of cefsulodin elimination by haemodialysis in 3 patients were evaluated using the deconvolution approach. The results indicated that cefsulodin was dialyzable with approximately 50% of the drug in the body removed by haemodialysis over 3-4 h.

Cefsulodin↗
PubMed1986

A note on appropriate constraints on the initial input response when applying deconvolution.

When deconvolution is employed to estimate cumulative input profiles, nonzero initial values may result unless certain constraints are imposed on the function used to approximate the input response c(t). It is shown that the initial value of the response to a nonimpulse input is zero, i.e., c(t0) = 0, where t0 is the input lag time. If, in addition, the initial value of the impulse response is zero, i.e., c delta (0) = 0, then c'(t0) = 0. Therefore, it is appropriate to impose the constraint c(t0) = 0 in general and c'(t0) = 0 when c delta (0) = 0 if c(t) is the response to a nonimpulse input. The use of such constraints is demonstrated in an example where the cumulative in vivo dissolution profile is estimated by deconvolution.

Animals↗
PubMed1990

Comments on two recent deconvolution methods.

In a recent paper Vajda et al. presented a deconvolution method based on the assumptions that the response of a system and the input function to a system are described by first-order linear processes. The method is similar to one proposed by Veng-Pedersen, and obtains similar results. In this article a simpler, not new, and now generally available method for this special use is considered to point out potential risks associated with all three deconvolution methods.

Cimetidine↗
PubMed1988

Numerical deconvolution using system identification methods.

A deconvolution method is presented for use in pharmacokinetic applications involving continuous models and small samples of discrete observations. The method is based on the continuous-time counterpart of discrete-time least squares system identification, well established in control engineering. The same technique, requiring only the solution of a linear regression problem, is used both in system identification and input identification steps. The deconvolution requires no a priori information, since the proposed procedure performs system identification (including optimal selection of model order), selects the form of the input function and calculates its parametric representation and its values at specified time points.

Models, Biological↗
PubMed1992

Quantal analysis using maximum entropy noise deconvolution.

When applying quantal analysis to synaptic transmission it is often unclear how much of the measured postsynaptic signal fluctuation arises from random sampling and noise rather than from the probabilistic transmitter release process. Unconstrained noise deconvolution methods do not overcome this because they tend to overfit the data, often giving a misleading picture of the underlying process. Instead, maximum entropy deconvolution provides a solution which is the smoothest, or most featureless, distribution that is still compatible with the data, taking noise and sample size into account. A simple way of achieving this is described, together with results of Monte Carlo simulations which show that the features present in the maximum entropy solution usually reflect the process underlying the data and not random sampling or noise.

Algorithms↗
PubMed1987

A FORTRAN program for deconvolution analysis using the matrix algorithm method with special reference to renography.

A FORTRAN IV program is presented for deconvolution analysis using the matrix algorithm method. With the deconvolution technique retention functions are calculated from time-activity curve data representing both kidneys and blood background. The program computes for each kidney the minimum and maximum time of the retention function. It also calculates the initial amplitudes, absolute as well as relative, and the mean transit time of the retention functions. The design of the program allows for optional reviews of intermediate outputs at important stages. It also allows for the plotting of conventional time-activity curves of both kidneys corrected for blood background. Finally, the program plots the retention functions and some of their characteristics.

Algorithms↗
PubMed1986

Simultaneous analysis of multiple fluorescence decay curves by Laplace transforms. Deconvolution with reference or excitation profiles.

The properties and potentials of the noniterative Laplace deconvolution (LAP2) (M. Ameloot and H. Hendrickx, Biophys. J. 44 (1983) 27) are further investigated. It is shown that LAP2 is exact and that no extrapolations have to be calculated or assumed for the data measured in the actual time window if the impulse response function of the investigated system can be described by a sum of exponentials. The formulas for the LAP2 deconvolution against the measured decay of a reference compound instead of the recorded excitation profile are derived. The procedure for the simultaneous analysis of multiple fluorescence decay curves by LAP2 is described in detail. This global analysis allows one to link any decay parameter, is fast and compares favorably with the nonlinear least-squares iterative reconvolution methods. Because of its short computation time the global analysis by LAP2 provides an efficient way to analyze the fluorescence decay surface in terms of decay associated spectra.

Anthracenes↗
PubMed1985

Quantitative deconvolution of heavily fused chromatographic peaks of biological components using a multi-wavelength UV detector.

Quantitative deconvolution of a chromatographic peak with extremely low UV absorption (less than 0.005 A.U.) is demonstrated for the analysis of an anaesthetic (ketamine) in rabbit serum. One ketamine metabolite, nor-ketamine, was deconvoluted from a completely fused peak in the three-dimensional chromatogram by using a highly sensitive multi-wavelength UV detector. After injection of ketamine, the nor-ketamine level in the serum increased to 3 micrograms/ml, calculated as ketamine, in 120 min.

Animals↗
PubMed1992

Multiple oral administration of a ketoprofen-dextran ester prodrug in pigs: assessment of gastrointestinal bioavailability by deconvolution.

Deconvolution has been applied to estimate the in vivo dissolution/release process of ketoprofen from a ketoprofen-dextran ester prodrug in pigs. The prodrug was given to three pigs at intervals of 12 hr and in seven doses corresponding to 4 mg ketoprofen/kg body weight. Frequent blood sampling was carried out at the first, third, and seventh intervals. Plasma steady-state concentrations of ketoprofen following the prodrug administration were between 2 and 4 micrograms/ml. The reference consisted of a single p.o. dose of parent ketoprofen (4 mg/kg body weight). For each pig the response following the multiple dosing was deconvolved with the reference response using an algebraic deconvolution procedure adopted from the literature. The obtained cumulated in vivo dissolution/release profiles revealed similar release rates for the three pigs and similar extents of release (59, 70, and 65%). The mean in vivo dissolution/release times (MDT) were calculated to be 5.4, 6.1, and 5.7 hr, respectively. In conclusion, following administration of the dextran prodrug the plasma concentration curves and the dissolution/release profiles are uniform, with small interindividual variations.

Administration, Oral↗
PubMed1987

Theoretical aspects of multiple deconvolution analysis for quantification of left to right cardiac shunts.

A new method for quantification of left to right cardiac shunts by Bourguignon et al based on multiple deconvolution analysis is critically analysed within the framework of a simple mathematical model. Underlying assumptions are explicitly stated and their validity discussed. It turns out that some reinterpretation of the method is necessary. Using the same ideas as in multiple deconvolution analysis, a new relation for the pulmonary to systemic flow ratio is proposed on a theoretical basis. This technique may be useful when diagnosing left to right cardiac shunts with radiocardiographic methods.

Coronary Circulation↗
PubMed1987

Error analysis by simulation studies in renography deconvolution.

The renogram, defined as the time-activity curve obtained from measurements with a gamma detector over the kidneys after a prior injection of a radioactive tracer, can be quantified using the deconvolution method. Essentially all the inherent information in the renogram, the estimated relative renal uptake function and transit time spectrum through the kidney, can be derived from the computed renal retention function. This study shows how statistical and physiological noise and different backgrounds affect the accuracy of the derived parameters. Confidence intervals for the estimated relative renal function and mean transit time (MTT) are presented. The principal source of error in relative renal function was due to extrarenal background. It was found that the error in mean transit time due to statistical noise was proportional to MTT, that the presence of extrarenal background strongly affected the accuracy of the MTT, whereas the vascular background in the renogram was of minor importance. Physiological noise, interpreted as periodic changes in transit times does, strictly speaking, invalidate the deconvolution principle, but it was possible to calculate a valid mean value of the different actual transit times. The transit time spectrum, measured by differentiation of the computed retention function, was found to be of no practical value with use of the unconstrained matrix method. The signal to noise ratio and consequently the need for smoothing can be estimated from the sum of the squared second derivatives of the renogram itself. The plateau levels in the renal retention function provide a more reliable estimate for the relative function ratio than the relative amplitude of a renogram in which extrarenal background only has been subtracted.

Algorithms↗