Dynamic regulation of hepatic vitamin E secretion by the α‐ tocopherol transfer protein
Bibliographic record
Abstract
Vitamin E, a plant‐derived neutral lipid, is an essential nutrient for all vertebrates that scavenges free radicals in biological membranes, thereby preventing oxidative stress. Of the eight naturally‐occurring forms of vitamin E, α‐tocopherol is the most biologically active. This discrimination is achieved by the selective retention of α‐tocopherol by the hepatic α‐tocopherol transfer protein (α‐TTP), and by the selective degradation of all other vitamin E isoforms by CYP4F2. In cultured hepatocytes, α‐TTP facilitates the secretion of α‐tocopherol to the circulation for uptake by extrahepatic target tissues. We aim to understand how the actions of α‐TTP are regulated in vivo. Specifically, we study how α‐tocopherol status affects the intracellular localization of α‐TTP, and whether phosphorylation of tyrosines in α‐TTP affects it activity. Using live‐cell fluorescence imaging, we found that localization of α‐TTP in hepatocytes is dynamic: in the absence of α‐tocopherol, the protein is found in a punctate perinuclear pattern, but upon addition of vitamin E, the protein redistributes to a diffuse cytosolic pattern. In addition, we found that tyrosine residue(s) of α‐TTP are phosphorylated, and that this modification is necessary for α‐TTP's activity. These findings suggest that trans‐localization and tyrosine phosphorylation of α‐TTP are regulated under physiological conditions. Thus, dynamic and homeostatic mechanisms regulate the body‐wide distribution of α‐tocopherol. Research support: NIH 5T32DK007319–33 and NIH RO1DK067494.
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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".