Ascorbate improves metabolic abnormalities in <i>Wrn</i> mutant mice but not the free radical scavenger catechin
Bibliographic record
Abstract
Werner syndrome (WS) is a premature aging disorder caused by mutations in a RecQ-like DNA helicase. Mice lacking the helicase domain of the WRN homologue exhibit many phenotypic features of WS. Importantly, mutant Wrn(Deltahel/Deltahel) mice show abnormal increases in visceral fat deposition and fasting blood triglyceride levels followed by insulin resistance and high blood glucose levels. These mice also exhibit increased heart and liver tissue reactive oxygen species concomitantly with oxidative DNA damage, indicating a pro-oxidant status. We treated mice with either ascorbate or catechin hydrate for 9 months. Vitamin C supplementation reduced oxidative stress in liver and heart tissues and reversed hypertriglyceridemia, hyperglycemia, and insulin resistance and reduced fat weight in mutant Wrn(Deltahel/Deltahel) mice. Although the free scavenger catechin hydrate also reduced oxidative DNA damage in heart and liver tissues, it did not reverse any of the metabolic phenotype aspects in treated mutant mice. Finally, vitamin C and catechin hydrate did not affect the metabolic status of wild-type mice. These results indicate that vitamin C supplementation could be beneficial for WS patients.
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 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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".