Characterization of Fatty Acid Transport across Human Brain Microvessel Endothelial Cells (HBMECs)
Bibliographic record
Abstract
Endothelial cells lining the blood capillaries of the Blood Brain Barrier (BBB) are tightly packed thus regulating the transport of substances from the blood into the brain, including fatty acids. Fatty acids are essential for both the developing and adult mammalian brain. Since most fatty acids in the brain enter from the blood, we examined the mechanism of their transport across Human Brain Microvessel Endothelial Cells (HBMECs). HBMECs were plated onto transwell plate inserts and then incubated for up to 4 h with [1‐14C]oleate in the apical medium. Radioactivity in the basolateral medium was temporally examined. There was a near linear increase in [1‐14C]oleate incorporation into the basolateral media in the presence of albumin indicating a protein acceptor is required for oleate transport. The presence of phloretin, a non‐specific fatty acid uptake inhibitor, significantly decreased [1‐14C]oleate transport into the basolateral medium. In addition, siRNA knockdown of fatty acid transport protein‐1 (FATP‐1) or fatty acid translocase (FAT/CD36) significantly decreased [1‐14C]oleate incorporation into the basolateral media. In summary, transport of oleate across HBMECs is, in part, a transcellular process. Oleate transport across HBMECs is mediated by both diffusion and carrier mediated processes. (Supported by the Manitoba Health Research Council and the Canadian Institutes of Health Research)
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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 | 0.001 |
| 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 | 0.001 |
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".