Green Synthesis of Iron Nanoparticles Using Gum Arabic (Acacia senegal): Antimicrobial, Anticoagulant, and Wound-Healing Applications
Bibliographic record
Abstract
Recently, iron nanoparticles (FeNPs) synthesized using gum arabic as a green reducing agent have demonstrated significant biological activity, highlighting the potential of nanotechnology in biomedical applications.The FeNPs were prepared by dissolving 4.04 g of iron nitrate [Fe(NO)9HO] in 100 mL of deionized water, heating the solution to 60 for 1 hour, and then mixing it with 10 mL of plant extract.The color of the solution turned reddish brown, confirming the formation of nanoparticles.The biocompatibility of FeNPs, along with their antimicrobial, anticoagulant, and wound-healing activities, suggests their potential applications in healthcare.The antimicrobial properties of FeNPs were evaluated against several bacterial strains, including Staphylococcus aureus, Staphylococcus epidermidis, Escherichia coli, and Pseudomonas aeruginosa.The results showed that the nanocomposite exhibited significant inhibitory effects against Staphylococcus species, with inhibition rates ranging from 61.96% to 77.82% across various concentrations.These findings suggest that FeNPs inhibited biofilm formation in Staphylococcus species, which were the most sensitive bacteria tested, in a concentrationdependent manner.This suggests that FeNPs could serve as a suitable replacement for conventional antibacterial substances, especially for infections that involve biofilms.The anticoagulant activity of FeNPs was assessed by measuring prothrombin time (PT) and partial thromboplastin time (PTT) at concentrations ranging from 50 to 100 g/mL.A marked increase in clotting time was observed, indicating strong anticoagulant effects.The greatest delay in clotting was observed at the concentration of 100 g/mL.This effect is attributed to the interaction of FeNPs with key coagulation factors (VIII, IX, and XI), which delays thrombin formation and alters fibrin production.Additionally, Fe NPs generate reactive oxygen species (ROS) that influence platelet activity, further aiding in the prevention of blood clots.FeNPs were shown to accelerate fibroblast migration and collagen synthesis during the wound healing process.The treated group exhibited a significantly higher rate of scratch closure (~88%) compared to the untreated group (~78%) after 72 hours.FeNPs were shown to accelerate fibroblast migration and collagen synthesis during the wound healing process.The treated group exhibited a significantly higher rate of scratch closure (~88%) compared to the untreated group (~78%) after 72 hours.Moreover, these particles are also capable of inducing angiogenesis and activating the immune system.The gum Arabic-synthesized Fe NPs exhibited strong antimicrobial, anticoagulant, and wound-healing activities, demonstrating their high potential in biomedical applications.Further studies are required to optimize their efficacy and safety for use in patient care settings.
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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) | 0.000 | 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 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".