Synthesis and enhanced neuroprotective activity of C60-based ebselen derivatives
Bibliographic record
Abstract
A C 60 -based ebselen derivative 4 was synthesized through the cycloaddition of C 60 with the azide (3) containing the ebselen component. It was obtained in a four-step synthesis starting from 2-(chloroseleno)benzoyl chloride and 2-(2-aminoethoxy)ethanol in 53% yield (based on consumed C 60 ). Its structure was characterized by 1 H NMR, 13 C NMR, IR, UV, and FAB-MS. To verify that the C 60 -based ebselen derivative 4 had enhanced antioxidative and neuroprotective activity, the C 60 derivative 5 and the ebselen derivative 6 were selected to treat cortical neuronal cells using the same procedures as with the C 60 -based ebselen derivative 4. The cellular viability of different derivative treatment groups was estimated by LDH leakage assay and MTT assay. At the same final concentration (30 µmol/L), the results showed that the antioxidative and protective potencies of the C 60 -based ebselen derivative 4 (MTT (OD) 0.340 ± 0.035, LDH release (UL –1 ) 4.80 ± 0.16) against H 2 O 2 -mediated neuronal injury have an advantage over those of C 60 derivative 5 (MTT (OD) 0.297 ± 0.036, LDH release (UL –1 ) 5.37 ± 0.31) and ebselen derivative 6 (MTT (OD) 0.267 ± 0.027, LDH release (UL –1 ) 5.85 ± 0.26). Correspondingly, the GPX activity of 4 (1.62 U/µmol) was higher than that of 5 (0.77 U/µmol) and 6 (1.24 U/µmol). These findings demonstrate that the incorporation of two components with similar biological activity (C 60 component and ebselen component) may be a desirable way of obtaining a new and more biologically effective C 60 -based compound.Key words: fullerene, ebselen derivative, azide, neuroprotective activity, cellular viability.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".