Comparative Antioxidant Efficacy of Green-Synthesised Selenium Nanoparticles From Pongamia pinnata, Citrus sinensis, and Acacia auriculiformis: An In Vitro Analysis
Notice bibliographique
Résumé
Aim This study aims to synthesise selenium nanoparticles (SeNPs) using extracts from Citrus sinensis peel (CSP), Millettia pinnata Leaf (MPL), and Acacia auriculiformis bark (AAB) as eco-friendly reducing agents. It seeks to compare the effectiveness of these plant extracts in the production of SeNPs and evaluate the antioxidant activities of the synthesised nanoparticles, establishing a link between the phytochemical constituents of the extracts and the antioxidant capacity of SeNPs for their potential applications in drug development and environmental sustainability. Introduction Nanotechnology offers innovative solutions in various fields, including medicine, environmental science, and materials engineering. SeNPs are of particular interest due to their unique properties and potential applications. The methods for synthesizing nanoparticles often involve hazardous chemicals, posing risks to the environment and human health. In response, green synthesis methods utilizing plant extracts have emerged as a sustainable alternative. This study focuses on utilizing CSP, MPL, and AAB extracts, rich in natural reducing agents such as flavonoids and phenolic acids, for the eco-friendly synthesis of SeNPs. These plant sources are chosen based on their known phytochemical profiles and potential antioxidant activities, and we aim to explore the correlation between the extracts' phytochemical composition and the antioxidant capabilities of the synthesised SeNPs. Methods SeNPs were synthesised using aqueous extracts of CSP, MPL, and AAB through a reduction process, in which selenium ions (Se4+) are reduced to elemental selenium. The presence of SeNPs was first visually monitored by colour change and then confirmed through UV-Vis spectroscopy and Fourier transform infrared (FTIR) spectroscopy analyses. The antioxidant activity of the synthesised SeNPs was assessed using the 1,1-diphenyl-2-picryl hydroxyl (DPPH) radical scavenging assay and the efficacy of SeNPs synthesised from different plant extracts was compared. Results The UV-Vis spectral analysis indicated a successful synthesis of SeNPs, as evidenced by the characteristic absorption peaks. The FTIR analysis confirmed the presence of organic molecules derived from the plant components on the outer layer of SeNPs, suggesting successful capping and stabilization of nanoparticles by phytochemicals in the extracts. Among the three types of SeNPs, those synthesised using Citrus sinensis peel extract (CSPE) exhibited the highest DPPH radical scavenging activity, indicating superior antioxidant properties compared to SeNPs synthesised from Millettia pinnata leaf extract (MPLE) and Acacia auriculiformis bark extract (AABE). This suggests that the antioxidant capacity of SeNPs is significantly influenced by the phytochemical composition of the plant extract used for synthesis. Conclusion The study highlights the potential of CSPE as an effective natural source for synthesising antioxidant-rich SeNPs and underscores the importance of green synthesis approaches in producing environmentally friendly and biologically active nanomaterials.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».