On the mechanism of oleate transport across human brain microvessel endothelial cells
Bibliographic record
Abstract
The blood-brain barrier formed by the brain capillary endothelial cells provides a protective barrier between the systemic blood and the extracellular environment of the CNS. As most fatty acids in the brain enter from the blood, we examined the mechanism of oleate (C18:1) transport across primary human brain microvessel endothelial cells (HBMEC). The permeability of [1-14C]oleate was determined using confluent cells grown on Transwell inserts in both the absence or presence of bovine serum albumin in the basolateral media, and following inhibition of various fatty acid transporters. The passage of [1-14C]oleate across confluent HBMEC monolayers was significantly enhanced when fatty acid free albumin was present in the basolateral media. The presence of the non-specific fatty acid uptake inhibitor phloretin significantly decreased [1-14C]oleate uptake by HBMEC and the subsequent release of [1-14C]oleate into the basolateral medium. Knockdown of fatty acid transport protein-1 or fatty acid translocase/CD36 significantly decreased [1-14C]oleate transport across the HBMEC monolayer from either apical as well as basolateral sides. The findings indicate that a fatty acid acceptor is a requirement for oleate transport across HBMEC monolayers. In addition, transport of oleate across HBMEC is, in part, a transcellular process mediated by fatty acid transport proteins.
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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 | 0.001 |
| 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".