Application of new methods and analytical approaches to research on polyunsaturated fatty acid homeostasis
Bibliographic record
Abstract
New methods and analytical approaches are important to challenge and/or validate established beliefs in any field including the metabolism of polyunsaturated fatty acids (PUFA; polyunsaturates). Four methods that have recently been applied toward obtaining a better understanding of the homeostasis of PUFA include the following: whole-body fatty acid balance analysis, magnetic resonance imaging (MRI), 13C nuclear magnetic resonance (NMR) spectroscopy, and gas chromatography-combustion-isotope ratio mass spectrometry (GC-C-IRMS). Whole-body balance studies permit the measurement of both the percentage of oxidation of linoleate and alpha-linolenate and their conversion to long-chain PUFA. This method has shown that beta-oxidation to CO2 is normally the predominant metabolic fate of linoleate and alpha-linolenate. Furthermore, models of experimental undernutrition in both humans and animals show that beta-oxidation of linoleate and alpha-linolenate markedly exceeds their intake, despite theoretically sufficient intake of linoleate or alpha-linolenate. Preliminary results suggest that by using MRI to measure body fat content, indirect whole-body linoleate balance can be done in living humans. 13C NMR spectroscopy provided unexpected evidence that linoleate and alpha-linolenate were metabolized into lipids synthesized de novo, an observation later quantified by tracer mass balance done using GC-C-IRMS. This latter method showed that within 48 h of dosing with 13C-alpha-linolenate, >80% underwent beta-oxidation to CO2 by suckling rats, whereas 8-9% was converted to newly synthesized lipids and <1 % to docosahexaenoate. Further application of these recently developed methods in different models should clarify the emerging importance of beta-oxidation and carbon recycling in PUFA homeostasis in mammals including humans.
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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 | 0.013 | 0.008 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".