Synergistic in vitro antioxidant activity and observational clinical trial of F105, a phytochemical formulation including<i>Citrus bergamia</i>, in subjects with moderate cardiometabolic risk factors
Bibliographic record
Abstract
We examined the clinical safety and efficacy of F105 in 11 subjects with moderate dyslipidemia. F105 is a combination of bergamot fruit extract (Citrus bergamia, BFE) and 9 phytoextracts selected for their ability to improve the antioxidant and anti-inflammatory activity of BFE. In vitro F105 exhibited a synergistic inhibition of oxygen radical absorbing capacity, peroxynitrite formation, and myeloperoxidase activity. Following 12 weeks of F105 daily, no treatment-related adverse events or changes in body mass were seen. Statistically significant changes were noted in total cholesterol (-7.3%), LDL-cholesterol (-10%), non-HDL cholesterol (-7.1%), cholesterol/HDL (-26%), and apolipoprotein B (-2.8%). A post hoc analysis of 8 subjects with HbA1c > 5.4 and HOMA-IR score > 2 or elevated triglycerides revealed additional statistically significant changes in addition to those previously observed in all subjects including triglycerides (-27%), oxLDL (-19%), LDL/HDL (-25%), triglycerides/HDL (-27%), oxLDL/HDL (-25%), and PAI-1 (-37%). A follow-up case report of a 70-year-old female patient, nonresponsive to statin therapy and placed on F105 daily, demonstrated improved cardiometabolic variables over 12 weeks similar to the subgroup. In summary, F105 was clinically well-tolerated and effective for ameliorating dyslipidemia in subjects with moderate cardiometabolic risk factors, particularly in the individuals with HbA1c > 5.4%.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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) | 0.001 | 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".