Ascorbic acid-mediated selenium nanoparticles as potential antihyperuricemic, antioxidant, anticoagulant, and thrombolytic agents
Bibliographic record
Abstract
Abstract Selenium (Se) is an important trace element that is involved in controlling oxidative stress and inflammatory disorders. Gouty arthritis is the inflammation and pain within the joints and tissues caused due to the accumulation of monosodium urate (MSU) crystals. This study aimed to investigate the antigout, antioxidant, anticoagulant, and thrombolytic potential of ascorbic acid-mediated Se nanoparticles (A-SeNPs). Different analytical techniques were used to investigate the formation of A-SeNPs. The antigout potential of the nanoparticles was carried out using MSU crystal dissolution, uric acid (UA) degradation assay, and xanthine oxidase inhibition (XOI). A-SeNPs exhibited excellent antihyperurecemic activity in a concentration-dependent manner. It was observed that at the tested concentration of 20 mg·mL −1 , the A-SeNPs demonstrated significant breakage and dissolution of MSU crystals and resulted in UA degradation of 67.76%. Similarly, A-SeNPs resulted in 76% XOI with an excellent IC 50 of 140 µg·mL −1 . Furthermore, considerable antioxidant activity was noted for the A-SeNPs as evaluated with multiple antioxidant assays. Finally, the NPs were found to have significant anticoagulant and thrombolytic potential. Thus, it was concluded that A-SeNPs have potent antihyperuricemic, antioxidant, anticoagulant, and thrombolytic activities, making them an ideal choice for future biomedical applications.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".