Antibacterial Activity of Silver Nanoparticles against Staphylococcus warneri Synthesized Using Endophytic Bacteria by Photo-irradiation
Bibliographic record
Abstract
Diseases caused by Staphylococcus warneri have a significant impact on human health. We evaluated the antibacterial activity of silver nanoparticles (synthesized using the endophytic strain SYSU 333150) against Staphylococcus warneri. The strain SYSU 333150 was isolated from the roots of Borszczowia aralocaspica Bunge. The 16S rRNA sequence results suggest that SYSU 333150 belongs to the genus Isoptericola and is likely a new species. Photo-irradiation was used to synthesize silver nanoparticles, which were characterized using UV-visible spectroscopy, transmission electron microscopy and X-ray diffraction. The nanoparticles were spherical and measured to be11 to 40 nm. X-ray diffraction revealed four peaks corresponding to the 111, 200, 220 and 311 planes of the face-centered cubic lattice, indicating a crystalline nature. Fourier transform infrared spectroscopy suggested that the metabolites in the culture supernatant were likely reducing and capping agents. The silver nanoparticles possessed antimicrobial activity (14 mm zone of inhibition) against Staphylococcus warneri, which was likely a result of DNA cleavage. The synthesized silver nanoparticles have potent antibacterial activity against Staphylococcus warneri and can be used to control infection.
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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".