Dairy Product Intake Modifies MicroRNA Expression among Individuals with Hyperinsulinemia: A Post-Intervention Cross-Sectional Study
Bibliographic record
Abstract
INTRODUCTION: MicroRNA (miRNA) profiles have been shown to change after intake of dairy products. Dysregulation of miRNA is associated with the changes in the level of glycemic parameters. The objectives are: (1) to investigate miRNA expression after consumption of dairy products and (2) to study the association between miRNAs and glycemic profile among individuals with hyperinsulinemia. METHODS: In crossover design, 24 participants were randomized into 2 phases: high dairy (HD) (≥4 servings/day according to the Canadian food guide [2007]) and adequate dairy (AD) (≤2 servings/day) over 6 weeks. First, miRNAs were extracted from a pooled plasma sample of 10 subjects after HD and AD intervention which analyzed in duplicate by array hybridization (Affymetrix Gene Chip miRNA Array v. 4.0). Second, 6 miRNAs related to type 2 diabetes (T2D) were validated by quantitative reverse transcription polymerase chain reaction (qRT-PCR) from plasma of 24 participants. RESULTS: Microarray analysis indicated that 297 miRNAs expressed differentially (FC ≥ ±1.2; p value <0.05) in a pooled plasma sample of 10 subjects. Among pooled miRNAs, the level of selected miRNAs, including miR-652-3p, miR-106b-5p, miR-93-5p, and miR-107 were downregulated; conversely, miR-223-3p and miR-122-5p were upregulated. After qRT-PCR validation, only the expression level of miR-106-5p tended to be increased after HD compared to AD (p = 0.06). After AD intervention, the level of fasting plasma glucose (FPG) and insulin and homeostatic model assessment of insulin resistance were negatively correlated with miR-122-5p. Similarly, negative correlation was found between miR-106-5p and FPG. CONCLUSION: The miRNAs profile was modified after HD compared to AD, and this may have role in modifying the risk of T2D (registration No. NCT02961179).
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 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 | 0.000 | 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 | 0.001 |
| 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".