The effect of the ALAnerv nutritional supplement on some oxidative stress markers in postacute stroke patients undergoing rehabilitation
Bibliographic record
Abstract
Stroke is a pathologic condition associated with redox imbalance. This pilot study was designed to evaluate the effect of the consumption of the nutritional supplement ALAnerv on some oxidative stress markers in postacute stroke patients undergoing rehabilitation. To achieve this goal, we assigned 28 patients to 2 study groups: (-)ALA and (+)ALA. Patients in both groups participated in the same rehabilitation program and received comparable standard medications; however, patients in the (+)ALA group received ALAnerv for 2 weeks (2 pills per day). We assessed total and nonproteic thiols, protein carbonyls, ceruloplasmin, oxidized low-density lipoprotein (LDL) particles, lipid hydroperoxide concentrations, gamma-glutamyl transpeptidase activity, and total antioxidant capacity. Regression analysis indicated that supplementation with ALAnerv was responsible for the significant decrease in glucose (p = 0.002) and oxidized LDL particles (p < 0.001) during the study period. For both parameters, the variation in the percent of concentration between the 2 groups during the study period reached statistical significance (p = 0.012 and p < 0.001, respectively). Moreover, Barthel Index values at discharge were significantly influenced by ALAnerv treatment. These preliminary results indicate that ALAnerv might be helpful because it rapidly corrects plasma fasting glucose and corrects serum oxidized LDL particle concentrations, suggesting the need for longer treatment with 2 pills or more per day.
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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) | 0.001 | 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 | 0.000 |
| 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".