Pharmaco-nutraceutical improvement of the response to obeticholic acid with omega-3 polyunsaturated fatty acids
Bibliographic record
Abstract
Obeticholic acid (OCA) is the second-line therapy for primary biliary cholangitis. While efficient in promoting bile acid (BA) detoxification and limiting liver fibrosis, its clinical use is restricted by severe dose-dependent side effects. We tested the hypothesis that adding n-3 polyunsaturated fatty acids (PUFAs), eicosapentaenoic (EPA) and docosahexaenoic (DHA) acids to OCA may improve the therapeutic effect of the low drug dosage. Several liver cell lines were exposed to vehicle, low or high OCA dose (1-20 μM) in the presence or absence of EPA/DHA for 24 h. To induce ER stress, apoptosis, and fibrosis, HepG2 cells were exposed to a 400 μM BA mixture or to 2 ng/ml transforming growth factor-β (TGF-β). For inflammation analyses, THP-1 cells were activated with 100 ng/ml lipopolysaccharides (LPS). The impact of OCA+EPA/DHA was assessed using transcriptomic (qRT-PCR), proteomic (ELISA, caspase-3), and metabolomic (LC-MS/MS) approaches. The addition of EPA/DHA reinforced the ability of low OCA dose to down-regulate the expression of genes involved in BA synthesis (CYP7A1 and CYP8B1) and uptake (NTCP) and to up-regulate the expression of MRP2 and 3 genes. EPA/DHA also enhanced the anti-inflammatory response of the drug by reducing the expression of the LPS-induced cytokines: tumor necrosis factor α (TNFα), interleukin (IL)-6, IL-1β, and monocyte chemoattractant protein-1 in THP-1 macrophages. OCA+EPA/DHA decreased the expression of BIP, CHOP, and COL1A1 genes and the caspase-3 activity. EPA+DHA potentiate the response to low OCA doses on BA toxicity and provide additional benefits on ER stress, apoptosis, inflammation, and fibrosis. These observations support the idea that adding n-3 PUFAs to the drug may reduce the risk of dose-related side effects in patients treated with OCA.
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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 | 0.001 |
| 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".