BACKGROUND: Lipidomics, the comprehensive measurement of lipids within a biological system or substrate, is an emerging field with significant potential for improving clinical diagnosis and our understanding of health and disease. While lipids diverse biological roles contribute to their clinical utility, the diversity of lipid structure and concentrations prove to make lipidomics analytically challenging. Without internal standards to match each lipid species, researchers often apply individual internal standards to a broad range of related lipids. To aid in standardizing and automating this relative quantitation process, we developed LipidMatch Normalizer (LMN) http://secim.ufl.edu/secim-tools/ which can be used in most open source lipidomics workflows. RESULTS: LMN uses a ranking system (1-3) to assign lipid standards to target analytes. A ranking of 1 signifies that both the lipid class and adduct of the internal standard and target analyte match, while a ranking of 3 signifies that neither the adduct or class match. If multiple internal standards are provided for a lipid class, standards with the closest retention time to the target analyte will be chosen. The user can also signify which lipid classes an internal standard represents, for example indicating that ether-linked phosphatidylcholine can be semi-quantified using phosphatidylcholine. LMN is designed to work with any lipid identification software and feature finding software, and in this study is used to quantify lipids in NIST SRM 1950 human plasma annotated using LipidMatch and MZmine. CONCLUSIONS: LMN can be integrated into an open source workflow which completes all data processing steps including feature finding, annotation, and quantification for LC-MS/MS studies. Using LMN we determined that in certain cases the use of peak height versus peak area, certain adducts, and negative versus positive polarity data can have major effects on the final concentration obtained.

BACKGROUND: Lipids are ubiquitous and serve numerous biological functions; thus lipids have been shown to have great potential as candidates for elucidating biomarkers and pathway perturbations associated with disease. Methods expanding coverage of the lipidome increase the likelihood of biomarker discovery and could lead to more comprehensive understanding of disease etiology. RESULTS: We introduce LipidMatch, an R-based tool for lipid identification for liquid chromatography tandem mass spectrometry workflows. LipidMatch currently has over 250,000 lipid species spanning 56 lipid types contained in in silico fragmentation libraries. Unique fragmentation libraries, compared to other open source software, include oxidized lipids, bile acids, sphingosines, and previously uncharacterized adducts, including ammoniated cardiolipins. LipidMatch uses rule-based identification. For each lipid type, the user can select which fragments must be observed for identification. Rule-based identification allows for correct annotation of lipids based on the fragments observed, unlike typical identification based solely on spectral similarity scores, where over-reporting structural details that are not conferred by fragmentation data is common. Another unique feature of LipidMatch is ranking lipid identifications for a given feature by the sum of fragment intensities. For each lipid candidate, the intensities of experimental fragments with exact mass matches to expected in silico fragments are summed. The lipid identifications with the greatest summed intensity using this ranking algorithm were comparable to other lipid identification software annotations, MS-DIAL and Greazy. For example, for features with identifications from all 3 software, 92% of LipidMatch identifications by fatty acyl constituents were corroborated by at least one other software in positive mode and 98% in negative ion mode. CONCLUSIONS: LipidMatch allows users to annotate lipids across a wide range of high resolution tandem mass spectrometry experiments, including imaging experiments, direct infusion experiments, and experiments employing liquid chromatography. LipidMatch leverages the most extensive in silico fragmentation libraries of freely available software. When integrated into a larger lipidomics workflow, LipidMatch may increase the probability of finding lipid-based biomarkers and determining etiology of disease by covering a greater portion of the lipidome and using annotation which does not over-report biologically relevant structural details of identified lipid molecules.

The relationships between the detector, diversity combiner, and soft-decision generator are unique in the way they contribute to providing the antijamming (AJ) and antiscintillation (AS) capability. The primary focus of this work is on describing this symbiotic relationship. This is done with an approach that permits possible architectures for detection, diversity combining, and soft-decision generation to surface as the secondary focus. The soft-decision generators for DPSK (differential-phase-shift keying) and MFSK (M-ary frequency-shift keying) channels are discussed in detail, because such generators present a variety of implementation problems related to automatic gain control and jamming sensitivity.>

A modified noncoherent PN code tracking loop (MCTL) has been previously presented by the authors [3]. The loop was shown to have the hardware simplicity of the tau-dither loop and a tracking performance superior to the traditional delay-locked code tracking loop (TCTL). Further work conducted herein expands on these previous results by considering the band-limiting effects of the bandpass arm filters on the performance of the MCTL. It will be shown that an even greater improvement in tracking performance is experienced by the MCTL over the TCTL when such effects are included. Furthermore, it was mentioned in [3] that a specificS/Nexisted below which the MCTL acquisition behavior was superior to the TCTL and above which its behavior was inferior. The bandlimiting effects will be shown to have a more deleterious effect on the TCTL and, as such, the crossoverS/Nwill increase, thus enhancing the comparable capabilities in favor of the MCTL. This paper also discusses the implementation sensitivities to hardware gain and phase imbalance by expanding on the noise-free work in [3] to include the noisy case.

Nonuniform amplitude windowingM-ary frequency shiftkeying (FSK) data prior to demodulation reduces the crosstalk normally caused by Doppler and oscillator drift. A major disadvantage of such nonuniform windowing is the loss in signal detectability as a result of the mismatch between the nonuniform windowed signal and the uniform windowed detectors. This paper is concerned with the tradeoff of nonuniform windowing to combat frequency offset degradation and signal detectability losses caused by the use of such windows in a DFT (discrete Fourier transform)-based detector of noncoherentM-ary FSK. What is shown here is that if a frequency control system can maintain frequency to within a certain deviation (which depends on error rate and nonuniform window), nonuniform windowing is not warranted; on the other hand, if the frequency deviation becomes too large, nonuniform windowing is advised. A technique is developed that will determine this crossover deviation.