Sex and organ specific proteomic responses to vitamin C deficiency in the brain, heart, liver, and spleen of Gulo-/- mice
Bibliographic record
Abstract
Recent advances in mass spectrometry have indicated that the water-soluble antioxidant vitamin C differentially modulates the abundance of various proteins in the hepatic tissue of female and male mice. In this study, we performed LC-MS/MS to identify and quantify proteins that correlate with serum vitamin C concentrations in the whole brain, heart, liver, and spleen tissues in mice deficient for the enzyme L-Gulonolactone oxidase required for vitamin C synthesis in mammals. This work shows for the first time that various biological processes affected by a vitamin C deficiency are not only sex specific dependent but also tissue specific dependent even though many proteins have been identified and quantified in more than three organs. For example, the abundance of several complex III subunits of the mitochondrial electron transport chain correlated positively with the levels of serum vitamin C only in the liver and not in the other tissues examined in this study even though such proteins were identified in all the organs analyzed. Western blot analyses on the Uqcrc1 and Uqcrfs1 complex III subunits validated the mass spectrometry results. Interestingly, the ferritin subunits represented the few quantified protein complexes that correlated positively with serum vitamin C in all the organs examined. Concomitantly, serum ferritin light chain 1 was inversely correlated with vitamin C levels in the serum. Thus, our study provides an initial comprehensive atlas of proteins significantly correlating with vitamin C in four organs in mice that will be a useful resource to the scientific community.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".