Intracellular Uptake Mechanism of Lutein in Retinal Pigment Epithelial Cells
Bibliographic record
Abstract
PURPOSE: Lutein is a carotenoid mainly found in green leafy vegetables and is located in the macula lutea in the human eye. It has received much attention recently due to its preventive effect on age-related macular degeneration, and it has been consumed as a supplement. However, little information about the pharmacokinetic properties of lutein is available. Detailed knowledge of pharmacokinetic properties of lutein is needed for the development of pharmaceutics. In this study, we focused on the macular accumulation of lutein and investigated the uptake mechanism into human retinal pigment epithelial cells. METHODS: ARPE-19 cells were used for the study on the accumulation mechanism of lutein. The concentration of lutein was determined using an HPLC system. Involvement of scavenger class B type 1 (SR-B1) in the accumulation of lutein in ARPE-19 cells was suggested from the results of an inhibition study using block lipid transport 1 (BLT-1), a selective inhibitor of SR-B1. To investigate the involvement of SR-B1 in more detail, small interfering RNA (siRNA) was transfected and the mRNA and protein expression levels of SR-B1 were assessed by quantitative real-time reverse transcription polymerase chain reaction and Western blotting, respectively. RESULTS: We confirmed a sufficient siRNA knockdown effect in both mRNA and protein expression levels of SR-B1. We then found that lutein uptake was significantly decreased by siRNA knockdown of SR-B1. CONCLUSION: The uptake of lutein was significantly decreased by 40% compared with the control uptake level. This suggested that active transport of lutein into ARPE-19 cells is mainly via SR-B1, given the result that lutein uptake at 4ºC was about 40% less that that at 37ºC.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".