Regulation of the proprotein convertase subtilisin/kexin type 9 in intestinal epithelial cells
Bibliographic record
Abstract
Proprotein convertase subtilisin/kexin type 9 (PCSK9) posttranslationally promotes the degradation of the low-density lipoprotein receptor (LDLr) in hepatocytes and increases plasma LDL cholesterol. It is not clear, however, whether PCSK9 plays a role in the small intestine. Here, we characterized the patterns of variations of PCSK9 and LDLr in fully differentiated Caco-2/15 cells as a function of various potential effectors. Cholesterol (100 microM) solubilized in albumin or micelles significantly downregulated PCSK9 gene (30%, P<0.05) and protein expression (50%, P<0.05), surprisingly in concert with a decrease in LDLr protein levels (45%, P<0.05). Cells treated with 25-hydroxycholesterol (50 microM) also displayed significant reduction in PCSK9 gene (37%, P<0.01) and protein (75% P<0.001) expression, whereas LDLr showed a decrease at the gene (30%, P<0.05) and protein (57%, P<0.01) levels, respectively. The amounts of PCSK9 mRNA and protein in Caco-2/15 cells were associated to the regulation of 3-hydroxy-3-methylglutaryl-CoA reductase and sterol regulatory element binding protein-2 (SREBP-2) that can transcriptionally activate PCSK9 via sterol-regulatory elements located in its proximal promoter region. On the other hand, depletion of cholesterol content by hydroxypropyl-beta-cyclodextrin upregulated PCSK9 transcripts (20%, P<0.05) and protein mass (540%, P<0.001), in parallel with SREBP-2 protein levels. The addition of bile acids (BA) taurocholate and deoxycholate to the apical culture medium lowered PCSK9 gene expression (25%, P<0.01) and raised PCSK9 protein expression (30%, P<0.01), respectively, probably via the modulation of farnesoid X receptor. Furthermore, unconjugated and conjugated BA exhibited different effects on PCSK9 and LDLr. Altogether, these data indicate that intestinal PCSK9 is highly modulated by sterols and emphasize the distinct effects of BA species.
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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 | 0.001 |
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".