Zirconia-Cu(I) stabilized copper oxide mesoporous nano-catalyst: Synthesis and DNA reactivity of 1,2,4-oxadiazole-quinolinepeptidomimetics-based metal(II) complexes
Bibliographic record
Abstract
Contemporary research reveals an undemanding protocol for the catalytic synthesis of 1,2,4-oxadiazole-quinolinepeptide in the incidence of a cost-effective and reusable mesoporous ZrO2-supported Cu2O (Cu2ZrO3) catalyst. This paper depicts a unique system for peptide bond synthesis staying away from toxic solvents and reactants. The catalyst was reused for four cycles without noteworthy loss in the activity, and the catalyst was genuinely heterogeneous. The method followed a simple workup procedure, and no column chromatography was needed. Further, the synthesized 1,2,4-oxadiazole-quinolinepeptide ligand (L), and its complexes of type, [FeLCl2] and [CuL]Cl2 were synthesized and characterized by spectral and analytical techniques. An octahedral geometry has been projected for Fe(II) complexes, while the Cu(II) complex exhibits a square planar geometry. The binding properties of the complexes with CT-DNA were studied by absorption spectral analysis, followed by viscosity measurement and thermal denaturation studies. The photo-induced cleavage studies revealed that the complexes possess photonuclease activity against pUC19 DNA under UV–visible irradiation.
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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) | 0.000 | 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 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".