Fatty acid transport protein expression in human brain and potential role in fatty acid transport across human brain microvessel endothelial cells
Bibliographic record
Abstract
The blood-brain barrier (BBB), formed by the brain capillary endothelial cells, provides a protective barrier between the systemic blood and the extracellular environment of the CNS. Passage of fatty acids from the blood to the brain may occur either by diffusion or by proteins that facilitate their transport. Currently several protein families have been implicated in fatty acid transport. The focus of the present study was to identify the fatty acid transport proteins (FATPs) expressed in the brain microvessel endothelial cells and characterize their involvement in fatty acid transport across an in vitro BBB model. The major fatty acid transport proteins expressed in human brain microvessel endothelial cells (HBMEC), mouse capillaries and human grey matter were FATP-1, -4 and fatty acid binding protein 5 and fatty acid translocase/CD36. The passage of various radiolabeled fatty acids across confluent HBMEC monolayers was examined over a 30-min period in the presence of fatty acid free albumin in a 1 : 1 molar ratio. The apical to basolateral permeability of radiolabeled fatty acids was dependent upon both saturation and chain length of the fatty acid. Knockdown of various fatty acid transport proteins using siRNA significantly decreased radiolabeled fatty acid transport across the HBMEC monolayer. Our findings indicate that FATP-1 and FATP-4 are the predominant fatty acid transport proteins expressed in the BBB based on human and mouse expression studies. While transport studies in HBMEC monolayers support their involvement in fatty acid permeability, fatty acid translocase/CD36 also appears to play a prominent role in transport of fatty acids across HBMEC.
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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 | 0.001 | 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) | 0.002 | 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".