Biochemical changes in cyanobacteria during the synthesis of silver nanoparticles
Bibliographic record
Abstract
The methods of synthesis of silver (Ag) nanoparticles by the cyanobacteria Spirulina platensis and Nostoc linckia were studied. A complex of biochemical, spectral, and analytical methods was used to characterize biomass and to assess changes in the main components of biomass (proteins, lipids, carbohydrates, and phycobilin) during nanoparticle formation. The size and shape of Ag nanoparticles in the biomass of both types of cyanobacteria were determined. Neutron activation analysis was used to study the accumulation dynamics of the Ag quantity. The analytical results suggest that the major reduction of Ag concentration in solutions and the increase in biomass occur within the first 24 h of experiments. While in this time interval minor changes in the N. linckia and S. platensis biomass took place, a significant reduction of the levels of proteins, carbohydrates, and phycobiliproteins in both cultures and of lipids in S. platensis was observed after 48 h. At the same time, the antiradical activity of the biomass decreased. The obtained results show the necessity of determining the optimal conditions of the interaction between the biomass and the solution containing Ag ions that would allow nanoparticle formation without biomass degradation at the time of Ag nanoparticle formation by the studied cyanobacteria.
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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".