Bioinorganic Synthesis of Polyrhodanine Stabilized Fe3O4/Graphene Oxide in Microbial Supernatant Media for Anticancer and Antibacterial Applications
Post-publication record
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Bibliographic record
Abstract
Polyrhodanines have been broadly utilized in diverse fields due to their attractive features. The effect of polyrhodanine- (PR-) based materials on human cells can be considered a controversial matter, while many contradictions exist. In this study, we focused on the synthesis of polyrhodanine/Fe3O4 modified by graphene oxide and the effect of kombucha (Ko) supernatant on results. The general structure of synthetic compounds was determined in detail through Fourier-transform infrared spectroscopy (FT-IR). Also, obtained compounds were morphologically, magnetically, and chemically characterized using scanning electron microscopy (SEM) and vibrating sample magnetometer (VSM), energy dispersive X-ray (EDX) analysis. The antibacterial effects of all synthesized nanomaterials were done according to CLSI against four infamous pathogens. Also, the cytotoxic effects of the synthesized compounds on the human liver cancer cell line (Hep-G2) were assessed by MTT assay. Our results showed that Go/Fe has the highest average inhibitory effect against Escherichia coli and Pseudomonas aeruginosa, and this compound possesses the least antimicrobial effect on Staphylococcus aureus. Considering the viability percent of cells in the PR/GO/Fe3O4 compound and comparing it with GO/Fe3O4, it can be understood that the toxic effects of polyrhodanine can diminish the metabolic activity of cells at higher concentrations (mostly more than 50 µg/mL), and PR/Fe3O4/Ko exhibited some promotive effects on cell growth, which enhanced the viability percent to more than 100%. Similarly, the cell viability percent of PR/GO/Fe3O4/KO compared to PR/GO/Fe3O4 is much higher, which can be attributed to the presence of kombucha in the compound. Consequently, based on the results, it can be concluded that this novel polyrhodanine-based nanocompound can act as drug carriers due to their low toxic effects and may open a new window on the antibacterial agents.
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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".