Biomineralization of Gold Nanoparticles by Lysozyme and Cytochrome c and Their Applications in Protein Film Formation
Bibliographic record
Abstract
Lysozyme (Lys) and cytochrome c (Cyc,c) proteins were used as mild reducing and stabilizing agents to synthesize gold nanoparticles (NPs) at precisely 40 and 80 degrees C. All reactions were monitored simultaneously by UV-visible measurements to determine changes in the nature of the protein during the course of reaction. The synthesis of Au NPs caused the simultaneous denaturation of protein due to the formation of bioconjugate NPs, and the denaturation temperature decreased with the number of NPs. Lys entrapped NPs in a typical gel state, and Cyc,c carried them on well-defined micelles at 80 degrees C or in the form of long fibrils or strands at 40 degrees C. The shape, size, and arrangement of bioconjugate NPs were characterized by atomic force microscopy and transmission electron microscopy measurements. Purified bioconjugate NPs were further used in zein protein film formation. The resulting films were characterized by photophysical and mechanical measurements. The induction of bioconjugate NPs made protein films isotropic and relatively more brittle (with a greater effect for Cyc,c than for Lys conjugate NPs) than in their absence and was considered to be well suited for biomedical applications.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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 source (direct Gemma or distilled Codex), 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".