Effect of Drinking Ration with Reduced Deuterium Content on Brain Tissue Prooxidant-Antioxidant Balance in Rats with Acute Hypoxia Model
Bibliographic record
Abstract
The aim was to investigate prooxidant-antioxidant system in the blood and brain homogenates functional activity in rats with acute hypoxia model with different deuterium/protium (D/H) ratios in drinking diet. Studies have shown that consuming DDW (–665 ‰) within 8 weeks lead to deuterium concentration decrease in blood plasma at 317 ‰ and brain at 209 ‰ of rats, in comparison to control group, consuming natural water. DDW consumption before hypoxia modeling in rats improves antioxidant defense enzymes (catalase, superoxide dismutase, glutathione peroxidase and glutathione reductase) activity in the blood, increasing its antioxidant potential by 20 %, while free radical oxidation intensity in plasma and biomolecules peroxide modification rate in erythrocytes. Also, in brain tissues consuming DDW, there were no abnormalities in catalase, superoxide dismutase activity, and it was noted increase (by 71 %) in reduced thiol-containing compounds concentration, which reduces nerve hypoxi? cell damage risk. Neuroprotective effect presence is confirmed by higher (by 32 %) antioxidant activity markers of lyophilized brain tissues, and by free radical oxidation lower intensity (by 13 %) and biomolecules oxidative modification rate (by 16 %) in these lyophilized tissues. Thus, the advisability of using DDW neuroprotective effects in cerebral circulation disturbance in experimental and clinical practice.
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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 | 0.000 |
| 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".