Long-Term Administration of Antioxidant N-Acetyl-L-Cysteine Impacts Beta Cell Oxidative Stress, Insulin Secretion, and Intracellular Signaling Pathways in Aging Mice
Bibliographic record
Abstract
Research into the effects of long-term antioxidant supplementation on the islet microenvironment is limited. This study examined whether long-term N-acetyl-L-cysteine (NAC) supplementation can prevent changes in metabolic outcomes, beta cell function, and pancreatic stellate cell (PaSC) activation in aging mice. Male C57BL/6N mice at 18 weeks were administered 50 mM NAC through their daily drinking water and treated for up to 60 weeks. Aging NAC mice displayed lower body weights and improved glucose tolerance but reduced insulin secretion and insulin signaling compared to control (ND) mice. When some 40-week-old ND and NAC mice were subjected to 8 weeks of a high-fat diet (HFD)-stress challenge, results showed that NAC reduced HFD-induced beta cell oxidative stress and preserved nuclear PDX-1 expression. The findings from this study suggest that while NAC can be beneficial for diet-induced stress during aging, the effects of long-term NAC on the islets of physiologically aging mice are more ambiguous. Further exploration is required to determine the effects of NAC-mediated lowering of beta cell oxidative stress on insulin secretion and signaling pathways. This study highlights the importance of investigating oxidative stress balance in aging islets under normal diet conditions to determine if antioxidative therapies can be utilized without interfering with essential physiological processes.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".