A Randomized Double-Blinded, Placebo-Controlled Trial Investigating the Effect of Fish Oil Supplementation on Gene Expression Related to Insulin Action, Blood Lipids, and Inflammation in Gestational Diabetes Mellitus-Fish Oil Supplementation and Gestational Diabetes
Bibliographic record
Abstract
Gestational diabetes mellitus (GDM) is a common complication of pregnancy, and it is mostly associated with postpartum diabetes, insulin resistance, and dyslipidemia. Fish oil (omega-3) supplementation has been shown to reduce the risk of different chronic diseases such as cardiovascular disease, type 2 diabetes, and cancers, though the evidence of its impact on gestational diabetes is scarce. Our goal in this study was to determine the effect of fish oil administration on gene expression related to insulin action, blood lipids, and inflammation in women with GDM. Participants with GDM (n = 40), aged 18–40 years, were randomized to take either 1000 mg fish oil capsules, containing 180 mg eicosapentaenoic acid and 120 mg docosahexaenoic acid (n = 20), or placebo (n = 20) twice a day for 6 weeks. Gene expression related to insulin, lipids, and inflammation was quantified in peripheral blood mononuclear cells (PBMCs) of GDM women using Reverse Transcription Polymerase Chain Reaction (RT-PCR) method. Results of RT-PCR indicated that omega-3 supplementation upregulated gene expression of peroxisome proliferator-activated receptor gamma (PPAR-γ) (P = 0.04) in PBMCs of patients with GDM, compared with the placebo. In addition, gene expression of the low-density lipoprotein receptor (LDLR) (P < 0.001), interleukin-1 (IL-1) (P = 0.007), and tumor necrosis factor alpha (TNF-α) (P = 0.01) was downregulated in PBMCs of women with GDM, following omega-3 supplementation. No significant effect of omega-3 supplementation was indicated on gene expression of IL-8 in PBMCs of patients with GDM. Overall, fish oil supplementation for 6 weeks in women with GDM significantly improved gene expression of PPAR-γ, IL-1, and TNF-α, but not gene expression of IL-8.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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".