Comprehensive Lipidomics Analysis of Bioactive Lipids in Complex Regulatory Networks
Bibliographic record
Abstract
In the present work we describe the development of an analytical technique for simultaneous profiling of over 100 biochemically related lipid mediators in biological samples. A multistep procedure was implemented to extract eicosanoids and other bioactive lipids from the biological matrix, chromatographically separate them using fast reversed-phase liquid chromatography, tentatively identify new candidate eicosanoids through a matching process of retention times, isotope distribution patterns, and high-resolution orbitrap MS/MS fragmentation patterns, and subsequently quantify tentative candidates by means of analytical reference standards. Key new aspects of this profiling technique included the classification of bioactive lipids into 12 groups according to their calculated exact masses and the development of optimized liquid chromatographic conditions for these groups to achieve sufficient separation of the numerous isobaric and isomeric species, many of which exhibited virtually identical collision-induced dissociation behavior. Importantly, no analytical standards were required at this screening stage of the assay, and tentative identifications were achieved by matching results to selected reference species from each of the groups. The analytical figures of merit for the orbitrap assay such as linear dynamic range, limit of detection, limit of quantitation, and precision demonstrated that the performance of the assay was very similar to that of a quadrupole linear ion trap assay, which was used for validation purposes. The method allowed us to examine eicosanoid profiles within the signaling cascade in chronic lymphocytic leukemia (CLL) cells under basal conditions and following arachidonic acid stimulation. The preliminary screening based on high-resolution tandem mass spectrometry data along with isotope pattern and retention time matching revealed the presence of 15 bioactive lipids, belonging to a range of prostaglandin, leukotriene, and hydroxy and epoxy fatty acid lipid mediators produced by CLL cells.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".