Comparative Antioxidant Efficacy of Green-Synthesised Selenium Nanoparticles From Pongamia pinnata, Citrus sinensis, and Acacia auriculiformis: An In Vitro Analysis
Bibliographic record
Abstract
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.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".