Effect of Bacoside A on growth and biofilm formation by <i>Staphylococcus aureus</i> and <i>Pseudomonas aeruginosa</i>
Bibliographic record
Abstract
The goal of this study was to evaluate the antibiofilm and antimicrobial activities of Bacoside A, a formulation of phytochemicals from Bacopa monnieri, against Staphylococcus aureus and Pseudomonas aeruginosa, which are known to form biofilms as one of their virulence traits. The antimicrobial effects of Bacoside A were tested using the minimum inhibitory concentration and minimum bactericidal concentration assays. A cell membrane disruption assay was performed to find its possible target site. MTT assay, crystal violet assay, and microscopic studies were performed to assess the antibiofilm activity. Bacoside A showed antimicrobial activity against both test organisms in their planktonic and biofilm states. At a subminimum inhibitory concentration of 200 μg·mL−1, Bacoside A significantly removed ∼88%–93% of bacterial biofilm developed on microtiter plates. Biochemical and microscopic studies suggested that the eradication of biofilm might be due to the loss of extracellular polymeric substances and to a change in cell membrane integrity of the selected bacterial strains treated with Bacoside A. These results indicate that Bacoside A might be considered as an antimicrobial having the ability to disrupt biofilms. Thus, either alone or in combination with other therapeutics, Bacoside A could be useful to treat biofilm-related infections caused by opportunistic bacterial pathogens.
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".