Synergistic broad-spectrum antibacterial activity of Hypoxis hemerocallidea-derived silver nanoparticles and streptomycin against respiratory pathobionts
Bibliographic record
Abstract
Respiratory tract infections arise due to the introduction of microbes into the airway, disrupting the normal, healthy, complex interdependent microbiome. The selective disruption of this community can be either beneficial or dangerous. Nanoparticles are a potential tool for modifying this population. Coated silver nanoparticles (AgNPs) were synthesized using ethanolic extracts of Hypoxis hemerocallidea (EEHH), a Southern African plant used extensively in traditional medicine and the source of many bioactive secondary metabolites. The room temperature reaction between silver nitrate and EEHH forms largely spherical AgNPs with an average diameter of 6-20 nm. These nanoparticles show similar levels of antibacterial activity as the broad-spectrum antibiotic streptomycin against Bacillus cereus, Streptococcus pneumonia, Escherichia coli, Pseudomonas aeuroginosa, and Moraxella catarrhalis. However, the AgNPs synergistically increase the antibacterial activity of streptomycin when they are applied in combination (30-52%). AgNPs are reiterated to be promising dual-function antibiotics, synergistically enhancing activity while also acting as delivery agents for small molecules.
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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) | 0.001 | 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 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".