Modulation of hepatic gene expression profiles by vitamin B<sub>1</sub>, vitamin B<sub>2</sub>, and niacin supplementation in mice exposed to acute hypoxia
Bibliographic record
Abstract
This study was aimed to observe the effects of vitamin B1, vitamin B2, and niacin supplementation on hepatic gene expression profiles in mice exposed to acute hypoxia. Thirty mice were randomly divided into normal, acute hypoxia, and acute hypoxia plus vitamin B1, vitamin B2, and niacin supplementation groups and fed corresponding diets for 2 weeks and then exposed to a simulated altitude of 6000 m for 8 h. Hepatic gene expression profiles were analyzed using a microarray technique. Several biochemical markers were also assayed. The results showed that a total of 2476 genes were expressed differentially after acute hypoxia exposure (1508 upregulated genes and 968 downregulated genes). Compared with the acute hypoxia group, there were 1382 genes differentially expressed (626 upregulated genes and 756 downregulated genes) in the acute hypoxia plus vitamin B1, vitamin B2, and niacin supplementation group. Pathway analysis indicated that carbohydrate, lipid, and amino acid metabolism, as well as electron transfer chain, were improved to some extent after vitamin B1, vitamin B2, and niacin supplementation. Supportive results were obtained from biochemical assays. Our findings suggest that the supplementation of vitamin B1, vitamin B2, and niacin is beneficial in improving nutritional metabolism partly via gene expression under acute hypoxia condition.
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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 | 0.000 |
| 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".