Antimicrobial, antioxidant, and angiogenic bioactive silver nanoparticles produced using <i>Murraya paniculata</i> (L.) jack leaves
Bibliographic record
Abstract
Murraya paniculata (MP) can be used as a reducing agent to produce silver nanoparticles (AgNPs) using a simple procedure. AgNPs are characterized in morphological and chemical properties, antioxidant activity, and cytotoxicity. The morphology of AgNPs derived from MP shows a face-centered cubic structure, spherical shape with an average particle size of 23 nm. The chemical structure shows characteristic peaks of AgNPs using UV-vis spectrometer at 438 nm. The formation of AgNPs is confirmed by analyzing their vibrational states under infrared radiation; typical peaks of AgNPs are recognized: at 3429 cm−1 (O-H stretch, H-bonded alcohols, phenols groups), 2923 cm−1 (C-H stretch alkanes), 1626 cm−1 (N-H bend 1° amines), 1583 cm−1 (C-C stretch in ring aromatic), 1039 cm−1 (C-N stretch aliphatic amines), 728 cm−1 (C-Cl stretch alkyl halides), and 589 cm−1 (C-Br stretch alkyl halides), respectively. AgNPs produced from MP show antioxidant activity and cytotoxicity. They show the highest sensitivity toward Bacillus cereus. Cytotoxicity of biosynthesized AgNPs, determined by scratch wound assay on in vitro human endothelial vein cell, created from MP showed dose-dependent activity. These AgNPs, at a concentration of 15.625 μg/mL, stimulate the proliferation and migration of endothelial cells (EC) showing an angiogenic activity.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".