Spectral Alignment Research Articles

Quantitative proton magnetic resonance spectroscopy of the normal liver and malignant hepatic lesions at 3.0 Tesla

This comparative study of tumour patients and volunteers aimed at differentiating liver parenchyma from neoplastic lesions by using localised (1)H MRS at 3.0 T as an adjunct to MRI. In total 186 single-voxel proton spectra of the liver were acquired at 3.0 T using the body transmit receive coil. Consecutive stacks of breath-hold spectra were acquired in the PRESS technique at a short echo time of 35 ms and a repetition time of 2,000 ms. Processing of the spectra included spectral alignment with the software package SAGE and quantitative processing with LCModel. The resulting metabolite concentrations were presented in arbitrary units relative to the internal water. In general, the spectra showed four main groups of resonances originating from the methyl protons (0.8-1.1 ppm) and methylene protons of the lipids (1.1-1.5 ppm; 2.0-2.2 ppm) as well as the methyl protons of choline-containing compounds (CCC) at 3.2 ppm. Overall, the CCC and lipid values in malignant liver tumours showed no significant differences to liver parenchyma. On average, total lipid measurements in normal liver parenchyma increased with age, while those of the CCC did not show pertinent changes. Significant differences between the contents of CCC in malignant liver tumours and normal liver parenchyma were not observed, because in patients and volunteers normal liver tissue showed a large variability in the content of CCC.

Proteomic Data Analysis Workflow for Discovery of Candidate Biomarker Peaks Predictive of Clinical Outcome for Patients with Acute Myeloid Leukemia

Our goal in this paper is to show an analytical workflow for selecting protein biomarker candidates from SELDI-MS data. The clinical question at issue is to enable prediction of the complete remission (CR) duration for acute myeloid leukemia (AML) patients. This would facilitate disease prognosis and make individual therapy possible. SELDI-mass spectrometry proteomics analyses were performed on blast cell samples collected from AML patients pre-chemotherapy. Although the biobank available included approximately 200 samples, only 58 were available for analysis. The presented workflow includes sample selection, experimental optimization, repeatability estimation, data preprocessing, data fusion, and feature selection. Specific difficulties have been the small number of samples and the skew distribution of the CR duration among the patients. Further, we had to deal with both noisy SELDI-MS data and a diverse patient cohort. This has been handled by sample selection and several methods for data preprocessing and feature detection in the analysis workflow. Four conceptually different methods for peak detection and alignment were considered, as well as two diverse methods for feature selection. The peak detection and alignment methods included the recently developed annotated regions of significance (ARS) method, the SELDI-MS software Ciphergen Express which was regarded as the standard method, segment-wise spectral alignment by a genetic algorithm (PAGA) followed by binning, and, finally, binning of raw data. In the feature selection, the "standard" Mann-Whitney t test was compared with a hierarchical orthogonal partial least-squares (O-PLS) analysis approach. The combined information from all these analyses gave a collection of 21 protein peaks. These were regarded as the most potential and robust biomarker candidates since they were picked out as significant features in several of the models. The chosen peaks will now be our first choice for the continuing work on protein identification and biological validation. The identification will be performed by chromatographic purification and MALDI MS/MS. Thus, we have shown that the use of several data handling methods can improve a protein profiling workflow from experimental optimization to a predictive model. The framework of this methodology should be seen as general and could be used with other one-dimensional spectral omics data than SELDI MS including an adequate number of samples.

Spectral alignment for top-down MS | BiSSCat | Zebrafish protein database | Automatic GUI | Assessing the quality of protein-protein interactions | TagFinder

Spectral alignment for top-down MS | BiSSCat | Zebrafish protein database | Automatic GUI | Assessing the quality of protein-protein interactions | TagFinder

Interpreting Top-Down Mass Spectra Using Spectral Alignment

Recent advances in mass spectrometry instrumentation, such as FTICR and OrbiTrap, have made it possible to generate high-resolution spectra of entire proteins. While these methods offer new opportunities for performing "top-down" studies of proteins, the computational tools for analyzing top-down data are still scarce. In this paper we investigate the application of spectral alignment to the problem of identifying protein forms in top-down mass spectra (i.e., identifying the modifications, mutations, insertions, and deletions). We demonstrate how spectral alignment efficiently discovers protein forms even in the presence of numerous modifications and how the algorithm can be extended to discover positional isomers from spectra of mixtures of isobaric protein forms.

Platelet Factor-4 Is an Indicator of Blood Count Recovery in Acute Myeloid Leukemia Patients in Complete Remission

To investigate whether serum biomarkers can be used to indicate the responsiveness of acute myeloid leukemia to remission induction chemotherapy, we performed MALDI-TOF protein profile analysis of patient sera. The resulting spectra revealed a protein (or peptide) peak at m/z 7764 that varied in intensity; its intensity was much higher in samples from patients in complete remission than in those from patients with resistant disease or in samples taken prior to treatment (at the time of diagnosis). Using fractionation, trypsin digestion, MS/MS, and protein molecular weight analyses, we identified the m/z 7764 protein as platelet factor-4 (PF4). This identification was confirmed by a magnetic bead-based MALDI immunoassay. Statistical comparison of PF4 levels and platelet counts in patient sera revealed a significant positive correlation between the two variables. This study demonstrates that PF4 protein levels are a good indicator for the recovery of blood count in the complete remission of acute myeloid leukemia. The linear positive correlation curve indicates that blood count recovery of platelets to >100,000/mm(3) is equivalent to a serum PF4 recovery level of >2.492 microg/ml.

Speaker Adaptation With Limited Data Using Regression-Tree-Based Spectral Peak Alignment

Spectral mismatch between training and testing utterances can cause significant degradation in the performance of automatic speech recognition (ASR) systems. Speaker adaptation and speaker normalization techniques are usually applied to address this issue. One way to reduce spectral mismatch is to reshape the spectrum by aligning corresponding formant peaks. There are various levels of mismatch in formant structures. In this paper, regression-tree-based phoneme- and state-level spectral peak alignment is proposed for rapid speaker adaptation using linearization of the vocal tract length normalization (VTLN) technique. This method is investigated in a maximum-likelihood linear regression (MLLR)-like framework, taking advantage of both the efficiency of frequency warping (VTLN) and the reliability of statistical estimations (MLLR). Two different regression classes are investigated: one based on phonetic classes (using combined knowledge and data-driven techniques) and the other based on Gaussian mixture classes. Compared to MLLR, VTLN, and global peak alignment, improved performance can be obtained for both supervised and unsupervised adaptations for both medium vocabulary (the RM1 database) and connected digits recognition (the TIDIGITS database) tasks. Performance improvements are largest with limited adaptation data which is often the case for ASR applications, and these improvements are shown to be statistically significant.

Effect of the Cavity Resonance-Gain Offset on the Output Power Characteristics of GaSb-Based VECSELs

In spite of elaborate heat-sinking employing intracavity heat-spreaders, the maximum output power of current (AlGaIn)(AsSb)-based vertical-external-cavity surface-emitting lasers (VECSELs) is still limited by thermal rollover (e.g., 0.8 W at 20degC at a peak emission wavelength of 2.35 mum). To identify the mechanisms underlying this thermal limitation, VECSEL structures with different cavity resonance-gain offsets have been fabricated and characterized. The resulting data have been analyzed using a thermooptical model. The temperature-dependent spectral alignment of quantum-well gain and microcavity resonance (so-called ldquogain offsetrdquo) is found to be one of the key parameters in optimizing high-power performance. A 45% increase in maximum room-temperature output power is obtained if the gain offset is chosen such that the gain spectrum matches the cavity resonance at operating pump power, i.e., at elevated active region temperatures.

Spectral phase‐corrected GRAPPA reconstruction of three‐dimensional echo‐planar spectroscopic imaging (3D‐EPSI)

MR spectroscopic (MRS) images from a large volume of brain can be obtained using a 3D echo-planar spectroscopic imaging (3D-EPSI) sequence. However, routine applications of 3D-EPSI are still limited by a long scan time. In this communication, a new approach termed "spectral phase-corrected generalized autocalibrating partially parallel acquisitions" (SPC-GRAPPA) is introduced for the reconstruction of 3D-EPSI data to accelerate data acquisition while preserving the accuracy of quantitation of brain metabolites. In SPC-GRAPPA, voxel-by-voxel spectral phase alignment between metabolite 3D-EPSI from individual coil elements is performed in the frequency domain, utilizing the whole spectrum from interleaved water reference 3D-EPSI for robust estimation of the zero-order phase correction. The performance of SPC-GRAPPA was compared with that of fully encoded 3D-EPSI and conventional GRAPPA. Analysis of whole-brain 3D-EPSI data reconstructed by SPC-GRAPPA demonstrates that SPC-GRAPPA with an acceleration factor of 1.5 yields results very similar to those obtained by fully encoded 3D-EPSI, and is more accurate than conventional GRAPPA.

A practical guide to robust detection of GABA in human brain by J-difference spectroscopy at 3 T using a standard volume coil

gamma-Aminobutyric acid (GABA) is the major inhibitory neurotransmitter in human brain and has been implicated in several neuropsychiatric disorders. In vivo human brain GABA concentrations are near the detection limit for magnetic resonance spectroscopy ( approximately 1 mM), and because of overlap with more abundant compounds, spectral editing is generally necessary to detect GABA. In previous reports, GABA spectra edited by J-difference spectroscopy vary considerably in appearance. We have evaluated the factors that affect GABA spectra and the conditions necessary for robust acquisition of J-difference spectra from arbitrary brain regions. In particular, we demonstrate that variations in spectral quality can be explained in part by the incoherent addition of transients that results from shot to shot frequency and phase variations. An automated time-domain spectral alignment strategy that enables reproducible acquisition of high-quality GABA spectra at 3 T with a standard 30-cm T/R volume coil is presented. Representative GABA spectra from human frontal lobe, an area where susceptibility-induced frequency and phase variations are especially troublesome, that demonstrate the robustness of the acquisition and data handling strategy used in this study are presented.

Data Fusion and Multicue Data Matching by Diffusion Maps

Data fusion and multicue data matching are fundamental tasks of high-dimensional data analysis. In this paper, we apply the recently introduced diffusion framework to address these tasks. Our contribution is three-fold: First, we present the Laplace-Beltrami approach for computing density invariant embeddings which are essential for integrating different sources of data. Second, we describe a refinement of the Nyström extension algorithm called "geometric harmonics." We also explain how to use this tool for data assimilation. Finally, we introduce a multicue data matching scheme based on nonlinear spectral graphs alignment. The effectiveness of the presented schemes is validated by applying it to the problems of lipreading and image sequence alignment.

Prediction of clinical outcome in non-small cell lung cancer (NSCLC) patients treated with gefitinib using Matrix-Assisted Laser Desorption/Ionization-Time of Flight Mass Spectrometry (MALDI-TOF MS) of serum

7004 Background: Assessment of epidermal growth factor receptor (EGFR) gene copy number, mutational status, and protein levels may predict response and possibly survival following treatment with EGFR tyrosine kinase inhibitors, but all these methods require tumor tissue, highlighting the need for a non-invasive predictive test. We evaluated the ability of MALDI-TOF MS profiling of serum to predict which patients (Pts) with NSCLC were likely to benefit from gefitinib treatment. Methods: Serum from Pts with NSCLC, collected prior to treatment with gefitinib, was subjected to MALDI-TOF MS using Voyager DE-STR or DE-PRO instruments. Replicate mass spectra obtained at two institutions were submitted to a third party for processing (background subtraction, noise estimation, normalization, spectral alignment and peak identification) and selection of discriminating mass/charge (m/z) values from a training cohort of 70 Caucasian Pts. The predictive capability of the profile was then assessed in independent cohorts of NSCLC Pts. Results: Intra- and inter- laboratory reproducibility of MALDI spectra were excellent. A set of 11 m/z values (mass range 5 - 12.5 kDa) predictive of clinical benefit were identified in the training cohort and confirmed by leave-one-out cross validation. Spectra from 19/70 Pts in the training cohort were unclassifiable. For the remaining 51 Pts the algorithm discriminated groups more or less likely to benefit with respect to time to progression (median 3.0 vs. 1.5 mo., p = 0.0325) and overall survival (median 14.6 vs. 2.3 mo., p = 0.0128). Validation was performed in an independent cohort consisting of serum from 69 Japanese Pts. Spectra from 13/69 Pts were unclassifiable. For the remaining 56 Pts it was possible to identify a group with superior time to progression (median 14.8 vs. 2.1 mo., p = 0.0012) and overall survival (median 19.1 vs. 7.9 mo., p = 0.0102). Conclusions: MALDI-TOF MS of pretreatment serum may aid with the identification of subsets of NSCLC Pts that will benefit from treatment with gefitinib. This algorithm is currently being evaluated in an expanded cohort of Pts receiving gefitinib treatment and in Pts treated with erlotinib. [Table: see text]

Packet Error Rate Distribution Between Random Bluetooth Piconet Pairs

The packet error rate between two piconets depends on the temporal alignment of their packets and the spectral alignment of the intervals from which the frequencies in their hop sequence are chosen. The relationship between two randomly paired piconets is one of over 828 billion possible relationships. We define these relationships and derive an expression for determining the packet error rate for a specific pair of piconets using single-slot packets. We derive the probability mass function for the packet error rate and extend it to provide the possible packet error rates for an arbitrary number of neighboring piconets. We also derive a probability mass function for the goodput of a piconet with a neighboring piconet. The probability mass functions for the packet error rate is bimodal, meaning the expected value of the goodput or packet error rate is not a good choice for piconet performance analysis.

Excited-state absorption and anisotropy properties of two-photon absorbing fluorene derivatives

The electronic structure of fluorene derivatives N-(7-benzothiazol-2-yl-9,9-bis-decyl-9H-fluoren-2-yl)-acetamide (1); 9,9-didecyl-2,7-bis-(N,N-benzothiazoyl)fluorene (2); 4,4'-{[9,9-bis(ethyl)-9H-fluorene-2,7-diyl]di-2,1-ethenediyl}bis(N,N-diphenyl)benzeneamine (3); and 4,4',4"{[9,9-bis(ethyl)-9H-fluorene-2,4,7-triyl]tri-2,1-ethenediyl}tris(N,N-diphenyl)benzeneamine (4) were investigated by a steady-state spectral technique, quantum-chemical calculations, and a picosecond pump-probe method. These derivatives are of interest for their relatively high two-photon absorption. The steady-state excitation anisotropy spectra reveal the nature of the ground-state absorption bands. Semiempirical quantum-chemical calculations of the fluorene derivatives (AM1, ZINDO/S) show good agreement with experimental data. The spectral positions and alignment of various electronic transitions of derivatives 1-4 were estimated from their excited-state absorption and anisotropy spectra.

A Novel Approach for Nontargeted Data Analysis for Metabolomics. Large-Scale Profiling of Tomato Fruit Volatiles

To take full advantage of the power of functional genomics technologies and in particular those for metabolomics, both the analytical approach and the strategy chosen for data analysis need to be as unbiased and comprehensive as possible. Existing approaches to analyze metabolomic data still do not allow a fast and unbiased comparative analysis of the metabolic composition of the hundreds of genotypes that are often the target of modern investigations. We have now developed a novel strategy to analyze such metabolomic data. This approach consists of (1) full mass spectral alignment of gas chromatography (GC)-mass spectrometry (MS) metabolic profiles using the MetAlign software package, (2) followed by multivariate comparative analysis of metabolic phenotypes at the level of individual molecular fragments, and (3) multivariate mass spectral reconstruction, a method allowing metabolite discrimination, recognition, and identification. This approach has allowed a fast and unbiased comparative multivariate analysis of the volatile metabolite composition of ripe fruits of 94 tomato (Lycopersicon esculentum Mill.) genotypes, based on intensity patterns of >20,000 individual molecular fragments throughout 198 GC-MS datasets. Variation in metabolite composition, both between- and within-fruit types, was found and the discriminative metabolites were revealed. In the entire genotype set, a total of 322 different compounds could be distinguished using multivariate mass spectral reconstruction. A hierarchical cluster analysis of these metabolites resulted in clustering of structurally related metabolites derived from the same biochemical precursors. The approach chosen will further enhance the comprehensiveness of GC-MS-based metabolomics approaches and will therefore prove a useful addition to nontargeted functional genomics research.

Stratospheric nitrogen dioxide in the Antarctic

Several UV–visible spectrometers have been developed at the ISAC‐CNR Institute. Differential Optical Absorption Spectroscopy (DOAS) methodology is applied to their measurements to monitor the amounts of stratospheric trace gases: mainly ozone (O3) and nitrogen dioxide (NO2) which is involved in the ozone cycle. Observations of the scattered zenith‐sky light were performed with one of these instruments installed at the Terra Nova Bay station (TNB), Antarctica. GASCOD (Gas Analyzer Spectrometer Correlating Optical Differences) is described briefly and a method for data analysis and validation of the results introduced. Some aspects of the DOAS technique are presented: the algorithm allowing the best spectral alignment between spectra obtained with GASCOD and a high‐resolution wavelength calibrated spectrum, is explained. Simple considerations allow for calculation of the NO2 concentration in the background spectrum used in DOAS analysis. For the period of activity of the GASCOD at TNB (1996–2003), the results of NO2 vertical column density (VCD) at twilight show a maximum in the summer and a minimum in the winter. Three years of measurements (2001–2003) are analysed in terms of stratospheric temperature and potential vorticity to obtain information about stratospheric warming that occurred in 2002 over Antarctica. The correlation between NO2 atmospheric content and stratospheric temperature is highlighted. The diurnal variations of NO2, which are controlled by photochemistry, show an unusual behaviour at high latitudes. Analysis of the a.m./p.m. ratios—the sunrise NO2 VC (a.m.) over the sunset VC (p.m.)—during different seasons and at various Solar Zenith Angles (SZA) is presented and discussed.

Processing methods for differential analysis of LC/MS profile data

BackgroundLiquid chromatography coupled to mass spectrometry (LC/MS) has been widely used in proteomics and metabolomics research. In this context, the technology has been increasingly used for differential profiling, i.e. broad screening of biomolecular components across multiple samples in order to elucidate the observed phenotypes and discover biomarkers. One of the major challenges in this domain remains development of better solutions for processing of LC/MS data.ResultsWe present a software package MZmine that enables differential LC/MS analysis of metabolomics data. This software is a toolbox containing methods for all data processing stages preceding differential analysis: spectral filtering, peak detection, alignment and normalization. Specifically, we developed and implemented a new recursive peak search algorithm and a secondary peak picking method for improving already aligned results, as well as a normalization tool that uses multiple internal standards. Visualization tools enable comparative viewing of data across multiple samples. Peak lists can be exported into other data analysis programs. The toolbox has already been utilized in a wide range of applications. We demonstrate its utility on an example of metabolic profiling of Catharanthus roseus cell cultures.ConclusionThe software is freely available under the GNU General Public License and it can be obtained from the project web page at: .

Threshold dependence on the spectral alignment between the quantum-well gain peak and the cavity resonance in InGaAsP photonic crystal lasers

Lithographically defined multiwavelength photonic crystal laser arrays are reported. The dependence of the threshold pump power on the spectral alignment between the quantum-well gain peak and the cavity resonance wavelength is investigated. This is done at, and slightly above, room temperature.

Angular spectrum of visible resonant cavity light-emitting diodes

We present spectrally resolved angular radiation patterns from visible resonant cavity light-emitting diodes. Recording the pattern for a fixed wavelength clearly demonstrates how the overall angular emission is strongly influenced by the relative spectral alignment of the cavity resonance and the underlying quantum well emission, i.e., the detuning. Combined with measurements of total optical power, taken over a range of solid angles, the results highlight the importance of accounting for the collection optics of a proposed application when an optimum design is considered.

Practical Confocal Microscopy and the Evaluation of System Performance

The laser scanning confocal microscope has enormous potential in many fields of biology. Currently there is a subjective nature in the assessment of a confocal microscope's performance by primarily evaluating the system with a specific test slide provided by the user's laboratory. To achieve better performance from the equipment, it is necessary to run a series of tests to ensure that the optical machine is functioning properly. We have devised these methods on the Leica TCS-SP and TCS-4D systems. Tests measuring field illumination, lens clarity, laser power output, dichroic functioning, spectral alignment, axial resolution, laser power stability, machine performance, and system noise were derived to test the Leica laser scanning confocal microscopy system. These tests should be applicable to other manufacturers' systems as well. The relationship between photomultiplier tube (PMT) voltage, laser power, and averaging using a 10-μm-diameter test bead has shown that the noise (coefficient of variation of bead intensity, CV) in an image increases as the PMT increases. Therefore increasing the PMT setting results in increased noise. For ideal image quality, it appears that it is better to decrease the PMT setting and increase laser power, as noise generated by high PMT settings will reduce the image quality far more than the bleaching caused by higher laser power. Averaging can be used to improve the image at high PMT values, provided the sample is not bleached by repeated passes of the laser.

Optimization and the Evaluation of Confocal System Performance to Quantify Fluorescence

The laser scanning confocal microscope (LSCM) has enormous potential in many fields of biology. Quality assurance is essential for the equipment to function correctly and realize its fullest potential. Currently the assessment of a confocal microscope’s performance is subjective primarily by evaluating the system with a specific test slide provided by the user. To achieve better performance, it is necessary to run a series of validation tests. These tests that were applied to measure field illumination, lens, clarity, dichroic functioning, objective spectral alignment, axial resolution, laser power and stability, photomultiplier tube (PMT) functioning, and system noise. Although th?se tests were derived on a Leica TCS-SP system and Leica TCD4D system, they should be applicable to other manufacturers’ systems.For optimal images, it is important to control the variables of laser power, PMT tube voltage, averaging, and bleaching. The relationship between PMT voltage, laser power, and averaging was determined using a Spherotech Rainbow 10 μm diameter test bead. It was demonstrated that the noise (coefficient of variation of bead intensity, CV) in an image greatly increases as the PMT increases. The system variables that affected the precision and accuracy of the confocal system will be discussed.