Antiatherogenic activity of extracts of Argania spinosa L. pericarp: beneficial effects on lipid peroxidation and cholesterol homeostasisThis article is one of a selection of papers published in this special issue (part 1 of 2) on the Safety and Efficacy of Natural Health Products.
Bibliographic record
Abstract
Prevention of lipoprotein oxidation by natural compounds may prevent atherosclerosis via reducing early atherogenesis. In this study, we investigated for the first time the beneficial properties of methanolic extract of argania pericarp (MEAP) towards atherogenesis by protecting human low-density lipoprotein (LDL) against oxidation while promoting high-density lipoprotein (HDL)-mediated cholesterol efflux. By measuring the formation of malondialdehyde (MDA) and conjugated diene as well as the lag phase and the progression rate of lipid peroxidation, the MEAP was found to possess an inhibitory effect. In addition, MEAP reduced the rate of disappearance of alpha-tocopherol as well as the apoB electrophoretic mobility in a dose-dependent manner. These effects are related to the free radical scavenging and copper-chelating effects of MEAP. In terms of cell viability, MEAP has shown a cytotoxic effect (0-40 microg/mL). Incubation of 3H-cholesterol-loaded J774 macrophages with HDL in the presence of increasing concentrations of MEAP enhanced HDL-mediated cholesterol efflux independently of ABCA1 receptor pathways. Our findings suggest that argania seed pericarp provides a source of natural antioxidants that inhibit LDL oxidation and enhance cholesterol efflux and thus can prevent development of cardiovascular diseases.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".