Effect of a hydrogen (<scp><scp>H<sub>2</sub></scp></scp>)‐enriched solution on the albumin redox of hemodialysis patients
Bibliographic record
Abstract
Elevated oxidative stress (OS) is associated with severe cardiovascular disease and premature death among patients treated with hemodialysis (HD). Oxidative stress is enhanced by contact between blood and dialysis membranes during HD sessions. This study aimed to clarify whether hydrogen (H2), which is a known antioxidant, is capable of suppressing increased OS induced during HD sessions. Eight patients on regular HD treatment were studied. Two HD sessions were performed in a cross-over design trial using standard and hydrogen-enriched solutions (mean of 50 p.p.b. H2; H2-HD). Blood samples were obtained from the inlet and outlet of the dialyzer during HD to determine changes in plasma levels of glutathione, hydrogen peroxide, and albumin redox state as a marker of OS. Comparison of inlet and outlet blood revealed significant decreases in total glutathione and reduced glutathione, as well as significant increases in hydrogen peroxide in both HD treatments. However, the mean proportion of reversibly oxidized albumin in outlet serum was significantly lower than that in inlet serum following the H2-HD session, whereas no significant changes were found in the standard solution session, suggesting that "intra-dialyzer" OS is reduced by H2 -HD. In conclusion, the application of H2-enriched solutions could ameliorate OS during HD.
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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".