The association of dietary insulinemic indices with PI3K, PTEN, and Akt gene expressions in visceral and subcutaneous adipose tissues among individuals undergoing abdominal surgery
Bibliographic record
Abstract
Background/objective: The current study investigates the association between dietary insulinemic indices and Akt, PTEN, and PI3K gene expressions in visceral adipose tissue (VAT) and subcutaneous adipose tissue (SAT) among individuals undergoing abdominal surgery. Materials and methods: ). The food frequency questionnaire was used to determine dietary glycemic and insulinemic indices. Real-time polymerase chain reaction was conducted for the expression of PI3K, PTEN, and Akt genes. Results: In the final adjusted model, in normal-weight patients, there was an inverse relationship between the lifestyle with a higher insulinemic potential and the PI3K gene expression in VAT. In addition, there was an inverse association between dietary insulin load and the Akt gene expression in VAT. However, a higher glycemic index was positively associated with the PTEN gene expression in VAT. In overweight patients, a high insulinemic potential of the diet was associated with higher PTEN gene expression in VAT. In obese individuals, there were positive associations between lifestyle index for insulin resistance and hyperinsulinemia and the PI3K gene expression in VAT. Moreover, the higher insulinemic potential of diet and lifestyle was positively related to a higher expression of the PTEN and Akt genes in VAT. Conclusion: Our findings revealed that high insulinemic lifestyles and dietary patterns may be related to the expression of PI3K, PTEN, and Akt in adipose tissues.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 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".