Rapid synthesis of bovine serum albumin-conjugated gold nanoparticles using pulsed laser ablation and their anticancer activity on hela cells
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Nanoscience research aims to produce nanoparticles without adverse effects for medical applications. The pulsed laser ablation (PLA) technique was utilized in this study to synthesize gold nanoparticles (AuNPs) using bovine serum albumin (BSA) in simulated body fluid (SBF) at the fundamental wavelength of the Nd: YAG laser (1064 nm). BSA acted as a stabilizer, reducing and capping agent to produce spherically shaped AuNPs (diameter 3–10 nm). The successful synthesis of AuNPs was confirmed through color changes and UV–vis spectroscopy. The agglomeration and precipitation of AuNPs are attributed to the presence of BSA in the solution, and electrostatic repulsion interactions between BSA and Au nanoclusters. The effect of salt concentration of SBF on BSA stability as well as the interaction of BSA conjugated AuNPs to form complexes was studied using molecular dynamic simulations. Our results show that the stability of AuNPs-BSA conjugates increase with the salt concentration of BSA. Moreover, the synthesized AuNPs exhibit low toxicity and high biocompatibility, supporting their application in drug delivery. Investigation of the cytotoxic effect of the synthesized AuNPs show that normal fibroblast cells (L929) remain intact after treatment whereas a dose-dependent inhibition effect on the growth of cervix cancer cells (HeLa) is observed. In general, this study presents an effective, environmentally-friendly, and facile approach to the synthesis of multifunctional AuNPs using the PLA technique, as a promising efficacious therapeutic treatment of cervical cancer.
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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 it