Protein Films of Bovine Serum Albumen Conjugated Gold Nanoparticles: A Synthetic Route from Bioconjugated Nanoparticles to Biodegradable Protein Films
Bibliographic record
Abstract
Bovine serum albumen (BSA) conjugated gold (Au) nanoparticles (NPs) were directly synthesized by using BSA as a weak reducing agent against HAuCl 4 in aqueous phase. A systematic variation in Au/BSA mole ratio showed a dramatic change in the size and shape of NPs which was very much dependent on the physical state of BSA. The nature of both colloidal NPs (due to surface plasmon resonance) and BSA (due to tryptophan residues) was monitored simultaneously by UV−visible measurements during the course of the reaction. A systematic variation in the reaction temperature from 20 to 70 °C demonstrated a clear denaturation process of BSA and how it influenced the synthesis of Au NPs. A predominantly native state of BSA that existed up to 40 °C proved to be a very mild reducing agent to convert Au(III) into Au(0). However, the reducing potential increased with unfolding of BSA beyond 40 °C and became maximum in the denaturation temperature range (i.e., 52−58 °C). Unfolded BSA conjugated NPs thus produced then started a seeding process with other similar NPs or free BSA to produce self-assembled colloidal assemblies in the form of soft film of BSA bearing NPs. SEM, TEM, and AFM studies were used to characterize the BSA conjugated NPs in the form of soft film. The soft film was used with water insoluble zein protein to produce very robust biodegradable protein films suitable for various food and pharmaceutical applications. Tensile strength and strain at failure measurements of zein protein films demonstrated that the film made with BSA conjugated NPs existed in the form of a soft film was much stronger and flexible in comparison to that made with nonaggregated NPs.
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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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".