Independent, but not co-supplementation, with nitrate and resveratrol improves glucose tolerance and reduces markers of cellular stress in high-fat-fed male mice
Bibliographic record
Abstract
Independent supplementation with nitrate (NIT) and resveratrol (RSV) enriches various aspects of mitochondrial biology in key metabolic tissues. Although RSV is known to activate Sirt1 and initiate mitochondrial biogenesis, the metabolic benefits elicited by dietary nitrate appear to be dependent on 5′-adenosine monophosphate-activated protein kinase (AMPK)-mediated signaling events, a process also linked to the activation of Sirt1. Although the benefits of individual supplementation with these compounds have been characterized, it is unknown if co-supplementation may produce superior metabolic adaptations. Thus, we aimed to determine if treatment with combined +NIT and +RSV (+RN) could additively alter metabolic adaptations in the presence of a high-fat diet (HFD). Both +RSV and +NIT improved glucose tolerance compared with HFD ( P < 0.05); however, this response was attenuated following combined +RN supplementation. Within skeletal muscle, all supplements increased mitochondrial ADP sensitivity compared with HFD ( P < 0.05), without altering mitochondrial content. Although +RSV and +NIT decreased hepatic lipid deposition compared with HFD ( P < 0.05), this effect was abolished with +RN, which aligned with significant reductions in Sirt1 protein content ( P < 0.05) after combined treatment, in the absence of changes to mitochondrial content or function. Within epididymal white adipose tissue (eWAT), all supplements reduced crown-like structure accumulation compared with HFD ( P < 0.0001) and mitochondrial reactive oxygen species (ROS) emission ( P < 0.05), alongside reduced adipocyte cross-sectional area (CSA) ( P < 0.05), with the greatest effect observed after +RN treatment ( P = 0.0001). Although the present data suggest additive changes in adipose tissue metabolism after +RN treatment, concomitant impairments in hepatic lipid homeostasis appear to prevent improvements in whole body glucose homeostasis observed with independent treatment, which may be Sirt1 dependent.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.001 | 0.001 |
| 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".