Generation of Bioactive Oxylipins from Exogenously Added Arachidonic, Eicosapentaenoic and Docosahexaenoic Acid in Primary Human Brain Microvessel Endothelial Cells
Bibliographic record
Abstract
The human blood-brain barrier (BBB) is the restrictive barrier between the brain parenchyma and the circulating blood and is formed in part by microvessel endothelial cells. The brain contains significant amounts of arachidonic acid (ARA), and docosahexaenoic acid (DHA), which potentially give rise to the generation of bioactive oxylipins. Oxylipins are oxygenated fatty acid metabolites that are involved in an assortment of biological functions regulating neurological health and disease. Since it is not known which oxylipins are generated by human brain microvessel endothelial cells (HBMECs), they were incubated for up to 30 min in the absence or presence of 0.1-mM ARA, eicosapentaenoic acid (EPA) or DHA bound to albumin (1:1 molar ratio), and the oxylipins generated were examined using high performance liquid chromatography-tandem mass spectrometry (HPLC/MS/MS). Of 135 oxylipins screened in the media, 63 were present at >0.1 ng/mL at baseline, and 95 were present after incubation with fatty acid. Oxylipins were rapidly generated and reached maximum levels by 2-5 min. While ARA, EPA and DHA each stimulated the production of oxylipins derived from these fatty acids themselves, ARA also stimulated the production of oxylipins from endogenous 18- and 20-carbon fatty acids, including α-linolenic acid. Oxylipins generated by the lipoxygenase pathway predominated both in resting and stimulated states. Oxylipins formed via the cytochrome P450 pathway were formed primarily from DHA and EPA, but not ARA. These data indicate that HBMECs are capable of generating a plethora of bioactive lipids that have the potential to modulate BBB endothelial cell function.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".