Promotion of whole blood rheology after vitamin C supplementation: focus on red blood cells
Bibliographic record
Abstract
Hemorheological properties represent significant contributors in the pathogenesis of cardiovascular diseases. As plasma vitamin C is inversely associated with blood viscosity in humans, we aimed to characterize the effect of vitamin C supplementation on hemorheology with an emphasis on erythrocyte functions. Twenty young healthy volunteers were asked to take vitamin C (1000 mg per day) for 3 weeks. We observed beneficial effect of intervention on multiple hemorheological parameters: whole blood viscosity in the range of medium to high shear rates, Casson yield stress, complex viscosity, and storage and loss moduli. As erythrocyte properties play a significant role in hemorheology, we characterized their deformability, nitric oxide production, and sodium pump activity in erythrocyte membranes. We can conclude that observed promotion in whole blood rheology may be consequence of improved erythrocyte functionality as concerns their ability to pass through narrow capillaries of the microcirculation, nitric oxide production, and sodium pump activity. Parameters reflecting oxidative stress and antioxidant status in plasma were not affected by our intervention. As improvement in hemorheology may play an important role in cardioprotection, it would be challenging to investigate the vitamin C supplementation to patients suffering from microcirculatory disturbances and worsened organ perfusion in the case of cardiovascular diseases.
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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".