Functional food ingredients as adjunctive therapies to pharmacotherapy for treating disorders of metabolic syndrome
Bibliographic record
Abstract
Abstract Information regarding the use of functional foods and nutraceuticals (FFN) in combating disease is rarely communicated to health care practitioners as medicinal strategies for patients. Metabolic syndrome (MetS) is an ideal paradigm for demonstrating the therapeutic properties of FFN. Encompassing multiple etiologies, including atherogenic dyslipidemia, insulin resistance, and hypertension, MetS affects over a third of American adults. However, as disease-related risk factors accumulate over time, guidelines for treating disorders of MetS progressively de-emphasize the use of FFN. Using marine omega-3 fatty acids, plant sterols, fiber, and tomato extract as examples, the purpose of this review is to endorse FFN as long-term adjunctive therapies to pharmaceutical treatment for disorders and risk factors for MetS. An additional goal is to compare physiological and molecular targets of FFN against corresponding prescription medications. Results reveal that FFN are viable treatment strategies for disorders of MetS, complementing pharmacological interventions by targeting and improving the biological processes that foster the development of disease. Thus, efficacious FFN therapies should be emphasized throughout all stages of treatment as adjuncts to pharmacotherapy for disorders of MetS. Accordingly, new developments in FFN research must be implemented into clinical guidelines with the prospect of improving disease prognoses as accessories to prescription medications.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| 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 teacher head, 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".