Selenium and Glutathione Peroxidase With Beta-Thalassemia Major
Bibliographic record
Abstract
BACKGROUND: Chronic iron-overload is a major cause of organ failure and mortality worldwide, but its pathogenesis remains to be elucidated. OBJECTIVES: To examine the relationship between various measures of body iron burden, selenium concentrations and glutathione peroxidase (GPx) activity in patients with beta-thalassemia major. METHODS: An age- and gender-matched case control study was conducted to examine the relationship between various measures of body iron burden (serum ferritin, transferrin saturation, total serum iron), plasma concentrations of selenium and glutathione peroxidase (GPx) activity in patients with homozygous beta-thalassemia major (N = 20) and healthy controls (N = 10). Ten patients received the experimental oral chelator L1 and ten received chelation therapy with subcutaneous desferal. RESULTS: Significantly decreased plasma concentrations of selenium (microg/L) were observed in patients chelated with L1 (1.4 +/- 0.2) or desferal (1.4 +/- 0.1), in comparison to healthy controls (1.8 +/- 0.1, p < 0.01). Significantly decreased plasma activity of GPx (microg/L) was observed in patients chelated with L1 (166 +/- 43) or desferal (178 +/- 46), in comparison to healthy controls (296 +/- 22, p < 0.001). Significantly increased concentrations of all measures of body iron burden were observed in beta-thalassemia patients, in comparison to healthy controls (p < 0.001). CONCLUSION: Patients with beta-thalassemia major and chronic iron-overload have decreased concentrations of the essential element selenium and the protective selenium-dependent antioxidant enzyme GPx. Additional research examining the effects of dietary antioxidant supplementation with selenium on these aforementioned parameters in patients with beta-thalassemia major and iron-overload is warranted.
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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 | 0.001 |
| 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) | 0.002 | 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".