Quantitative profiling of inflammatory and pro-resolving lipid mediators in human adolescents and mouse plasma using UHPLC-MS/MS
Bibliographic record
Abstract
OBJECTIVES: Lipid mediators are bioactive lipids which help regulate inflammation. We aimed to develop an ultra-high-performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS) method to quantify 58 pro-inflammatory and pro-resolving lipid mediators in plasma, determine preliminary reference ranges for adolescents, and investigate how total parenteral nutrition (TPN) containing omega-3 polyunsaturated fatty acid (n-3 PUFA) or n-6 PUFA based lipid emulsions influence lipid mediator concentrations in plasma. METHODS: Lipid mediators were extracted from plasma using SPE and measured using UHPLC-MS/MS. EDTA plasma was collected from healthy adolescents between 13 and 17 years of age to determine preliminary reference ranges and from mice given intravenous TPN for seven days containing either an n-3 PUFA or n-6 PUFA based lipid emulsion. RESULTS: We successfully quantified 43 lipid mediators in human plasma with good precision and recovery including several leukotrienes, prostaglandins, resolvins, protectins, maresins, and lipoxins. We found that the addition of methanol to human plasma after blood separation reduces post blood draw increases in 12-hydroxyeicosatetraenoic acid (12-HETE), 12-hydroxyeicosapentaenoic acid (12-HEPE), 12S-hydroxyeicosatrienoic acid (12S-HETrE), 14-hydroxydocosahexaenoic acid (14-HDHA) and thromboxane B2 (TXB2). Compared to the n-6 PUFA based TPN, the n-3 PUFA based TPN increased specialized pro-resolving mediators such as maresin 1 (MaR1), MaR2, protectin D1 (PD1), PDX, and resolvin D5 (RvD5), and decreased inflammatory lipid mediators such as leukotriene B4 (LTB4) and prostaglandin D2 (PGD2). CONCLUSIONS: Our method provides an accurate and sensitive quantification of 58 lipid mediators from plasma samples, which we used to establish a preliminary reference range for lipid mediators in plasma samples of adolescents; and to show that n-3 PUFA, compared to n-6 PUFA rich TPN, leads to a less inflammatory lipid mediator profile in mice.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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 teacher head, 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".