ArticleAnalytical chemistry2010
Method for the identification of lipid classes based on referenced Kendrick mass analysis.
Article in Analytical chemistry, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
25 citing papers in PubMed.
- Rapid Annotation Strategy forJournal of the American Society for Mass Spectrometry · 2025Article
- Chemical Informatics Combined with Kendrick Mass Analysis to Enhance Annotation and Identify Pathways in Soybean Metabolomics.Metabolites · 2025Article
- Reproducible mass spectrometry data processing and compound annotation in MZmine 3.Nature protocols · 2024Review
- Evaluation of Surface-Induced Dissociation Ion Mobility-Mass Spectrometry for Lipid Structural Characterization.Journal of the American Society for Mass Spectrometry · 2024Article
- What's the defect? Using mass defects to study oligomerization of membrane proteins and peptides in nanodiscs with native mass spectrometry.Methods (San Diego, Calif.) · 2023Review
- Software and Computational Tools for LC-MS-Based Epilipidomics: Challenges and Solutions.Analytical chemistry · 2023Review
- Novel Ambient Oxidation Trends in Fingerprint Aging Discovered by Kendrick Mass Defect Analysis.ACS central science · 2022Article
- A Current Encyclopedia of Bioinformatics Tools, Data Formats and Resources for Mass Spectrometry Lipidomics.Metabolites · 2022Review
- Referenced Kendrick Mass Defect Annotation and Class-Based Filtering of Imaging MS Lipidomics Experiments.Analytical chemistry · 2022Article
- Dual-polarity SALDI FT-ICR MS imaging and Kendrick mass defect data filtering for lipid analysis.Analytical and bioanalytical chemistry · 2021Article
- Generative Algorithm for Molecular Graphs Uncovers Products of Oil Oxidation.Journal of chemical information and modeling · 2021Article
- A large-scale genome-lipid association map guides lipid identification.Nature metabolism · 2020Article
- Chemical Class Prediction of Unknown Biomolecules Using Ion Mobility-Mass Spectrometry and Machine Learning: Supervised Inference of Feature Taxonomy from Ensemble Randomization.Analytical chemistry · 2020Article
- Untargeted high-resolution paired mass distance data mining for retrieving general chemical relationships.Communications chemistry · 2020Article
- Article
- Rapid profiling of triglycerides in human breast milk using liquid extraction surface analysis Fourier transform mass spectrometry reveals new very long chain fatty acids and differences within individuals.Rapid communications in mass spectrometry : RCM · 2019Article
- Improved matrix coating for positive- and negative-ion-mode MALDI-TOF imaging of lipids in blood vessel tissues.Analytical and bioanalytical chemistry · 2019Article
- Molecular Characterization of High Molecular Weight Polyesters by Matrix-Assisted Laser Desorption/Ionization High-Resolution Time-of-Flight Mass Spectrometry Combined with On-plate Alkaline Degradation and Mass Defect Analysis.Journal of the American Society for Mass Spectrometry · 2019Article
- Characterization of Red Wine Proanthocyanidins Using a Putative Proanthocyanidin Database, Amide Hydrophilic Interaction Liquid Chromatography (HILIC), and Time-of-Flight Mass Spectrometry.Molecules (Basel, Switzerland) · 2018Article
- Advanced Multidimensional Separations in Mass Spectrometry: Navigating the Big Data Deluge.Annual review of analytical chemistry (Palo Alto, Calif.) · 2016Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
A rapid method for the determination of lipid classes with high sensitivity is described. The referenced Kendrick mass defect (RKMD) and RKMD plots are novel adaptations of the Kendrick mass defect analysis that allows for the rapid identification of members of a homologous series in addition to identifying the lipid class. Assignment of lipid classes by the RKMD method is accomplished by conversion of the lipid masses to the Kendrick mass scale and then referencing the converted masses to each lipid class. Referencing of the masses to a given lipid class is achieved by first subtracting the heteroatom and lipid backbone contributions to the mass defect, leaving behind the contribution to the mass by the fatty acid constituents. The final step in the referencing makes use of spacing differences in mass defects between members of the same Kendrick class to identify members of the lipid class being referenced. The end result of this is that a lipid belonging to the class being referenced will have an integer RKMD with the value of the integer being the degrees of unsaturation in the lipid. The RKMD method was able to successfully identify the lipids in an idealized data set consisting of 160 lipids drawn from the glyceride and phosphoglyceride classes. As a real world example the lipid extract from bovine milk was analyzed using both accurate mass measurements and the RKMD method.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.