Influence of branched chain amino acids on insulin sensitivity and the mediator roles of short chain fatty acids and gut hormones: a review
Bibliographic record
Abstract
Circulating levels of branched chain amino acids (BCAAs) correlate strongly with type 2 diabetes (T2D). The correlation may be associated with insulin-resistance factors independent of glycemic markers currently used in the diagnosis and monitoring of diabetes. This can revolutionize the thought process and methodology not only in diabetes treatment, but also in its advance screening and prevention with BCAAs used as biomarkers and targets for treatment. Whether insulin resistance is the cause or result of BCAAs imbalances requires further investigation. Although the overall diet is important, the role of specific diets targeting the gut microbiome composition and hormone secretion affecting BCAA absorption and metabolism will be explored. Generic diet modifications apparently induce only negligible changes in the intrinsic genetic make-up of the gut and BCAA levels but influence specific modulation of the gut microbiome. This genetic make-up is indeed similar among T2D patients independent of numerous variables including obesity. Short-chain fatty acids (SCFAs), the primary end-products of non-digestible carbohydrates (NDC) fermentation, mediate metabolic imbalances through gut microbiota and gut hormone secretion. This review focuses on extensive evidence gathered using diverse methodologies on the strong parallel correlation between BCAA levels and insulin resistance. Furthermore, the role of specific diets particularly SCFAs as mediators of the stubbornly fixed intrinsic genetic make-up of gut microbiota will be scrutinized to delineate BCAA levels and insulin resistance in T2D.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".