Comparison of Deconvolution Filters for Photoacoustic Tomography

In this work, we compare the merits of three temporal data deconvolution methods for use in the filtered backprojection algorithm for photoacoustic tomography (PAT). We evaluate the standard Fourier division technique, the Wiener deconvolution filter, and a Tikhonov L-2 norm regularized matrix inversion method. Our experiments were carried out on subjects of various appearances, namely a pencil lead, two man-made phantoms, an in vivo subcutaneous mouse tumor model, and a perfused and excised mouse brain. All subjects were scanned using an imaging system with a rotatable hemispherical bowl, into which 128 ultrasound transducer elements were embedded in a spiral pattern. We characterized the frequency response of each deconvolution method, compared the final image quality achieved by each deconvolution technique, and evaluated each method’s robustness to noise. The frequency response was quantified by measuring the accuracy with which each filter recovered the ideal flat frequency spectrum of an experimentally measured impulse response. Image quality under the various scenarios was quantified by computing noise versus resolution curves for a point source phantom, as well as the full width at half maximum (FWHM) and contrast-to-noise ratio (CNR) of selected image features such as dots and linear structures in additional imaging subjects. It was found that the Tikhonov filter yielded the most accurate balance of lower and higher frequency content (as measured by comparing the spectra of deconvolved impulse response signals to the ideal flat frequency spectrum), achieved a competitive image resolution and contrast-to-noise ratio, and yielded the greatest robustness to noise. While the Wiener filter achieved a similar image resolution, it tended to underrepresent the lower frequency content of the deconvolved signals, and hence of the reconstructed images after backprojection. In addition, its robustness to noise was poorer than that of the Tikhonov filter. The performance of the Fourier filter was found to be the poorest of all three methods, based on the reconstructed images’ lowest resolution (blurriest appearance), generally lowest contrast-to-noise ratio, and lowest robustness to noise. Overall, the Tikhonov filter was deemed to produce the most desirable image reconstructions.     

Short-term projections of AIDS cases in Mexico.

We attempt to analyze and predict the behavior of the AIDS epidemic in Mexico. The reporting delay is corrected by using a cluster analysis, and the corrected data are used to make short-term projections by extrapolation, by fitting linear and log-linear models, and by back-calculation. The incubation period is assumed to have a Weibull distribution, and step functions are used for the infection functions. Most of the methods predict a mean of 25,000 accumulated cases by the end of 1993, and a comparison of the predictions with actual data up to November 1990 shows good agreement in all cases except the log-transformation linear model. The data for 1990 also show the reporting delay correction to be adequate in most cases.     

Structural identification of the metabolites for strictosamide in rats bile by an ion trap-TOF mass spectrometer and mass defect filter technique

We report herein, a facile metabolite identification workflow on the antimicrobial strictosamide, which is derived from accurate mass measurement by a hybrid ion trap-TOF mass spectrometer. In step 1, the parent drug and metabolites in rat bile were separated on an HPLC column followed by ion trap-TOF mass spectrometer analysis after a single oral dose of 50mg/kg strictosamide. In step 2, mass defect filter technique, which enables high-resolution mass spectrometers to be utilized for detecting drug metabolites based on well-defined mass defect ranges, was used to find metabolites in the mass spectrum. In step 3, the differences of accurate masses and their mass fragmentation pattern among the parent drug and metabolites used to assign structures for the metabolites successfully. As a result, five metabolites of strictosamide were found in rat bile, and all the metabolites were reported for the first time.     

“Lossless” compression of high resolution mass spectra of small molecules

Fourier transform ion cyclotron resonance (FTICR) provides the highest resolving power of any commercially available mass spectrometer. This advantage is most significant for species of low mass-to-charge ratio (m/z), such as metabolites. Unfortunately, FTICR spectra contain a very large number of data points, most of which are noise. This is most pronounced at the low m/z end of spectra, where data point density is the highest but peak density low. We therefore developed a filter that offers lossless compression of FTICR mass spectra from singly charged metabolites. The filter relies on the high resolving power and mass measurement precision of FTICR and removes only those m/z channels that cannot contain signal from singly charged organic species. The resulting pseudospectra still contain the same signal as the original spectra but less uninformative background. The filter does not affect the outcome of standard downstream chemometric analysis methods, such as principal component analysis, but use of the filter significantly reduces memory requirements and CPU time for such analyses. We demonstrate the utility of the filter for urinary metabolite profiling using direct infusion electrospray ionization and a 15 tesla FTICR mass spectrometer.     

Novel calibration method for mass spectrometers for on-line gas analysis. Set-up for the monitoring of a bacterial fermentation

A set-up procedure for the minimisation of signal noise of a capillary inlet mass spectrometer system, enabling direct use of data without noise filtering or drift correction, is described. A reliable calibration method was developed, involving standard calibration mixtures determined by the extreme vertices design. This novel method was shown to be the most accurate in comparison with a number of commonly used methods. These procedures enabled reliable on-line fermenter headspace gas analysis. With a relatively inexpensive mass spectrometer, monitoring of a fermentation and accurate estimation of oxygen uptake rate, carbon dioxide evolution rate, respiratory quotient and biomass concentration was possible.     

Decreasing motion artifacts in calcium-dependent fluorescence transients from the perfused mouse heart using frequency filtering

A strategy has been developed for the removal of motion artifact and noise in calcium-dependent fluorescence transients from the perfused mouse heart using frequency filtering. An analytical model indicates that the spectral removal of motion artifacts is independent of the phase shift of the motion waveform in the frequency domain, and thus to the time shift (or delay) of motion in the time domain. This is based on the "shift theorem" of Fourier analysis, which avoids erroneous correction of motion artifact when using the motion signal obtained using reflectance from the heart. Several major steps are adopted to implement this model for elimination of motion as well as detection noise from the fluorescence transient signals from the calcium-sensitive probe Rhod-2. These include (1) extracting the fluorescence calcium transient signal from the raw data by using power spectrum density (PSD) in the frequency domain by subtracting the motion recorded using the reflectance of excitation light, (2) digitally filtering out the random noise using multiple bandpass filters centralized at harmonic frequencies of the transients, and (3) extracting high frequency noise with a Gaussian Kernel filter method. The processed signal of transients acquired with excessive motion artifact is comparable to transients acquired with minimal motion obtained by immobilizing the heart against the detection window, demonstrating the usefulness of this technique.     

Detection and correction of probe-level artefacts on microarrays

ABSTRACT: BACKGROUND: A recent large-scale analysis of Gene Expression Omnibus (GEO) data found frequent evidence for spatial defects in a substantial fraction of Affymetrix microarrays in the GEO. Nevertheless, in contrast to quality assessment, artefact detection is not widely used in standard gene expression analysis pipelines. Furthermore, although approaches have been proposed to detect diverse types of spatial noise on arrays, the correction of these artefacts is mostly left to either summarization methods or the corresponding arrays are completely discarded. RESULTS: We show that state-of-the-art robust summarization procedures are vulnerable to artefacts on arrays and cannot appropriately correct for these. To address this problem, we present a simple approach to detect artefacts with high recall and precision, which we further improve by taking into account the spatial layout of arrays. Finally, we propose two correction methods for these artefacts that either substitute values of defective probes using probeset information or filter corrupted probes. We show that our approach can identify and correct defective probe measurements appropriately and outperforms existing tools. CONCLUSIONS: While summarization is insufficient to correct for defective probes, this problem can be addressed in a straightforward way by the methods we present for identification and correction of defective probes. As these methods output CEL files with corrected probe values that serve as input to standard normalization and summarization procedures, they can be easily integrated into existing microarray analysis pipelines as an additional pre-processing step. An R package is freely available from http://www.bio.ifi.lmu.de/artefact-correction.     

Estimation of organ transport function: model-free deconvolution by recursive quadratic programming optimization.

A model-free deconvolution method is proposed for evaluating the frequency distribution function of organ transit times. The deconvolution is treated as a nonlinear constrained optimization problem and it is solved by using a modified constrained variable metric approach. The only constraint implemented in the solution is that all the discrete transport function values are not allowed to become negative. The method is tested on model mathematical systems of known analytical transport functions. The tests are performed on systems that included noise in both the input and output functions. The criteria of successful deconvolution are the reconvolution error and, most importantly, the deviation of the computed transport function from the known analytical one. The proposed method is then applied, as a pilot experiment, to biological data obtained from an isolated, perfused rabbit lung preparation contained within a plethysmograph. The results indicate that this type of deconvolution produces stable estimates which faithfully follow the analytical function while negating the need to assume either any functional form for the behavior of the transport function or any educated initial guess of its values.     

Step changes in end-tidal CO2: methods and implications.

A dynamic end-tidal forcing technique for producing step changes in end-tidal CO2 with end-tidal O2 held constant independent of the ventilation response or the mixed venous return is introduced for characterizing the human ventilation response to end-tidal CO2 step changes for both normoxic (PAO2 = 125 Torr) and hypoxic (PAO2 = 60 Torr) conditions. The ventilation response approaches a steady state within 5 min. In normoxia, the on-transient is faster than the off-transient, presumably reflecting the action of cerebral blood flow. The hypoxic step response is faster than the normoxic response presumably reflecting the increased contribution from the carotid body. The delay in the ventilation response after the change in end-tidal CO2 is less in hypoxia than in normoxia and reflects the action of a transport delay and that of a virtual delay. These delays are interpreted with respect to the high-frequency phase shift data for the same subject, generated using sinusoidal end-tidal forcing. The methods of others for experiments utilizing step changes in inspired CO2 are considered with respect to our methods.     

Characterizing and correcting for the dynamic response of a bag-in-box system

A bag-in-box system (BBS) whose volume is monitored by a mechanical spirometer tends to have a slow response if the volume of the box is large, and this may significantly affect its measurement of gas flow. We describe a device for creating reproducible gas flows with which the impulse response of a BBS may be conveniently determined. Two computational techniques for correcting a BBS flow measurement for the effects of the impulse response were investigated: 1) an exponential model method that assumes a second-order model of the BBS dynamics and 2) a Fourier transform-based method of deconvolution known as Wiener filtering. Both correction methods produced a significant increase in the accuracy of BBS flow estimations, with the Wiener filter giving superior results.     

Correcting mass isotopomer distributions for naturally occurring isotopes

In one method of metabolic flux analysis, simulated mass spectrometry data is fitted to measured mass distributions of metabolites that are isolated from cultures with defined feeding of (13)C-labeled substrates. Doing so, simulated mass distributions must be corrected for the presence of naturally occurring isotopes. A method that was recently introduced for this purpose consists of consecutive correction steps for each isotope of each element in the considered compound. Here we show that all isotopes of each individual element must, however, be corrected in one single step. Furthermore, it is shown that the source of information with respect to isotopic compositions of the elements needs to be chosen with care.     

基于频域反卷积滤波器的光声成像

采用探测器的脉冲响应在频域反卷积滤波光声信号以进一步提高光声成像的分辨率.由仿真和实验结果表明,频域反卷积滤波重建相对于时域反投影重建和滤波反投影重建具有更好的成像效果,明显地提高重建图像的分辨率,经仿真结果的计算,其重建图像的分辨率由2.58 mm提高到了0.16 mm.实验所用的光源为YAG激光器,波长为1064 ...     

Application of a noninhibitory growth model to predict the transient response in a chemostat

A method of adapting a kinetic model based on steady-state chemostat data to predict the transient performance of a chemostat culture is presented. The proposal provides for a time delay which can be considered equivalent to a period of reduced activity of the organism subsequent to the introduction of a step change in operating conditions. The adapted kinetic model gives substantially better performance in predicting the transient response of an experimental system than the unmodified kinetic model.     

Combinatorial image analysis of DNA microarray features

MOTIVATION: DNA and protein microarrays have become an established leading-edge technology for large-scale analysis of gene and protein content and activity. Contact-printed microarrays has emerged as a relatively simple and cost effective method of choice but its reliability is especially susceptible to quality of pixel information obtained from digital scans of spotted features in the microarray image. RESULTS: We address the statistical computation requirements for optimizing data acquisition and processing of digital scans. We consider the use of median filters to reduce noise levels in images and top-hat filters to correct for trends in background values. We also consider, as alternative estimators of spot intensity, discs of fixed radius, proportions of histograms and k-means clustering, either with or without a square-root intensity transformation and background subtraction. We identify, using combinatoric procedures, optimal filter and estimator parameters, in achieving consistency among the replicates of a gene on each microarray. Our results, using test data from microarrays of HCMV, indicate that a highly effective approach for improving reliability and quality of microarray data is to apply a 21 by 21 top-hat filter, then estimate spot intensity as the mean of the largest 20% of pixel values in the target region, after a square-root transformation, and corrected for background, by subtracting the mean of the smallest 70% of pixel values. AVAILABILITY: Fortran90 subroutines implementing these methods are available from the authors, or at http://www.bioss.ac.uk/~chris.     

Metabolic profiling by ion mobility mass spectrometry (IMMS)

Ion Mobility Mass Spectrometry (IMMS) was evaluated as an analytical method for metabolic profiling. The specific instrument used in these studies was a direct infusion (DI)-electrospray ionization (ESI)—ambient pressure ion mobility spectrometer (APIMS) coupled to a time-of-flight mass spectrometer (TOFMS). The addition of an ion mobility spectrometer to a mass spectrometer had several advantages over direct infusion electrospray mass spectrometry alone. This tandem instrument (ESI-IMMS) added a rapid separation step with high-resolution prior to mass spectrometric analysis of metabolite mixtures without extending sample preparation time or reducing the high through put potential of direct mass spectrometry. Further, IMMS also reduced the baseline noise common with ESI-MS analyses of complex samples and enabled rapid separation of isobaric metabolites. IMMS was used to analyze the metabolome of Escherichia coli (E. coli), containing a collection of extremely diverse chemical compounds including hydrophobic lipids, inorganic ions, volatile alcohols and ketones, amino and non-amino organic acids, and hydrophilic carbohydrates. IMMS data were collected as two-dimensional spectra showing both mobility and mass of each ion detected. Using direct infusion ESI-IMMS of a non-derivatized methanol extract of an E. coli culture, more than 500 features were detected, of which over 200 intracellular metabolites were tentatively assigned as E. coli metabolites. This analytical method also allowed simultaneous separation of isomeric metabolic features.     

Recovering motifs from biased genomes: application of signal correction

A significant problem in biological motif analysis arises when the background symbol distribution is biased (e.g. high/low GC content in the case of DNA sequences). This can lead to overestimation of the amount of information encoded in a motif. A motif can be depicted as a signal using information theory (IT). We apply two concepts from IT, distortion and patterned interference (a type of noise), to model genomic and codon bias respectively. This modeling approach allows us to correct a raw signal to recover signals that are weakened by compositional bias. The corrected signal is more likely to be discriminated from a biased background by a macromolecule. We apply this correction technique to recover ribosome-binding site (RBS) signals from available sequenced and annotated prokaryotic genomes having diverse compositional biases. We observed that linear correction was sufficient for recovering signals even at the extremes of these biases. Further comparative genomics studies were made possible upon correction of these signals. We find that the average Euclidian distance between RBS signal frequency matrices of different genomes can be significantly reduced by using the correction technique. Within this reduced average distance, we can find examples of class-specific RBS signals. Our results have implications for motif-based prediction, particularly with regards to the estimation of reliable inter-genomic model parameters.     

Mechanisms of firing patterns in fast-spiking cortical interneurons

Cortical fast-spiking (FS) interneurons display highly variable electrophysiological properties. Their spike responses to step currents occur almost immediately following the step onset or after a substantial delay, during which subthreshold oscillations are frequently observed. Their firing patterns include high-frequency tonic firing and rhythmic or irregular bursting (stuttering). What is the origin of this variability? In the present paper, we hypothesize that it emerges naturally if one assumes a continuous distribution of properties in a small set of active channels. To test this hypothesis, we construct a minimal, single-compartment conductance-based model of FS cells that includes transient Na(+), delayed-rectifier K(+), and slowly inactivating d-type K(+) conductances. The model is analyzed using nonlinear dynamical system theory. For small Na(+) window current, the neuron exhibits high-frequency tonic firing. At current threshold, the spike response is almost instantaneous for small d-current conductance, gd, and it is delayed for larger gd. As gd further increases, the neuron stutters. Noise substantially reduces the delay duration and induces subthreshold oscillations. In contrast, when the Na(+) window current is large, the neuron always fires tonically. Near threshold, the firing rates are low, and the delay to firing is only weakly sensitive to noise; subthreshold oscillations are not observed. We propose that the variability in the response of cortical FS neurons is a consequence of heterogeneities in their gd and in the strength of their Na(+) window current. We predict the existence of two types of firing patterns in FS neurons, differing in the sensitivity of the delay duration to noise, in the minimal firing rate of the tonic discharge, and in the existence of subthreshold oscillations. We report experimental results from intracellular recordings supporting this prediction.     

Optical properties of the adaxial and abaxial faces of leaves. Chlorophyll fluorescence, absorption and scattering coefficients.

Emission fluorescence spectra were obtained for the adaxial and abaxial faces of dicotyledonous (Ficus benjamina L., Ficus elastica, Gardenia jasminoides and Hedera helix) and monocotyledonous leaves (Gladiolus spp. and Dracaena cincta bicolor). After correction by light-re-absorption processes, using a previously published physical model, the adaxial faces of dicotyledons showed a fluorescence ratio Fred/Ffar-red rather lower than the respective values for the abaxial faces. Monocotyledons and shade-adapted-plants showed similar values for the corrected fluorescence ratio for both faces. Even when differences in experimental fluorescence emission from adaxial and abaxial leaves in dicotyledons are mostly due to light re-absorption processes, the residual dissimilarity found after application of the correction model would point to the fact that fluorescence re-absorption is not the only responsible for the observed disparity. It was concluded that light re-absorption processes does not account entirely for the differences in the experimental emission spectra between adaxial and abaxial leaves. Differences that remains still present after correction might be interpreted in terms of a different photosystem ratio (PSII/PSI). Experiments at low temperature sustained this hypothesis. In dicotyledons, light reflectance for adaxial leaves was found to be lower than for the abaxial ones. It was mainly due to an increase in the scattering coefficient for the lower leaf-side. The absorption coefficient values were slightly higher for the upper leaf-side. During senescence of Ficus benjamina leaves, the scattering coefficient increased for both the upper and lower leaf-sides. With senescence time the absorption coefficient spectra broadened while the corrected fluorescence ratio (Fred/Ffar-red) decreased for both faces. The results pointed to a preferential destruction of photosystem II relative to photosystem I during senescence.     

Incorporating sequence information into the scoring function: a hidden Markov model for improved peptide identification

MOTIVATION: The identification of peptides by tandem mass spectrometry (MS/MS) is a central method of proteomics research, but due to the complexity of MS/MS data and the large databases searched, the accuracy of peptide identification algorithms remains limited. To improve the accuracy of identification we applied a machine-learning approach using a hidden Markov model (HMM) to capture the complex and often subtle links between a peptide sequence and its MS/MS spectrum. Model: Our model, HMM_Score, represents ion types as HMM states and calculates the maximum joint probability for a peptide/spectrum pair using emission probabilities from three factors: the amino acids adjacent to each fragmentation site, the mass dependence of ion types and the intensity dependence of ion types. The Viterbi algorithm is used to calculate the most probable assignment between ion types in a spectrum and a peptide sequence, then a correction factor is added to account for the propensity of the model to favor longer peptides. An expectation value is calculated based on the model score to assess the significance of each peptide/spectrum match. RESULTS: We trained and tested HMM_Score on three data sets generated by two different mass spectrometer types. For a reference data set recently reported in the literature and validated using seven identification algorithms, HMM_Score produced 43% more positive identification results at a 1% false positive rate than the best of two other commonly used algorithms, Mascot and X!Tandem. HMM_Score is a highly accurate platform for peptide identification that works well for a variety of mass spectrometer and biological sample types. AVAILABILITY: The program is freely available on ProteomeCommons via an OpenSource license. See http://bioinfo.unc.edu/downloads/ for the download link.     

Firing-rate models capture essential response dynamics of LGN relay cells

Firing-rate models provide a practical tool for studying signal processing in the early visual system, permitting more thorough mathematical analysis than spike-based models. We show here that essential response properties of relay cells in the lateral geniculate nucleus (LGN) can be captured by surprisingly simple firing-rate models consisting of a low-pass filter and a nonlinear activation function. The starting point for our analysis are two spiking neuron models based on experimental data: a spike-response model fitted to data from macaque (Carandini et al. J. Vis., 20(14), 1–2011, 2007), and a model with conductance-based synapses and afterhyperpolarizing currents fitted to data from cat (Casti et al. J. Comput. Neurosci., 24(2), 235–252, 2008). We obtained the nonlinear activation function by stimulating the model neurons with stationary stochastic spike trains, while we characterized the linear filter by fitting a low-pass filter to responses to sinusoidally modulated stochastic spike trains. To account for the non-Poisson nature of retinal spike trains, we performed all analyses with spike trains with higher-order gamma statistics in addition to Poissonian spike trains. Interestingly, the properties of the low-pass filter depend only on the average input rate, but not on the modulation depth of sinusoidally modulated input. Thus, the response properties of our model are fully specified by just three parameters (low-frequency gain, cutoff frequency, and delay) for a given mean input rate and input regularity. This simple firing-rate model reproduces the response of spiking neurons to a step in input rate very well for Poissonian as well as for non-Poissonian input. We also found that the cutoff frequencies, and thus the filter time constants, of the rate-based model are unrelated to the membrane time constants of the underlying spiking models, in agreement with similar observations for simpler models.