Production of a phenolic-rich extract of aroeira honey and characterization of its antimicrobial, antitumoral and antioxidant activities
Bibliographic record
Abstract
Objective: a phenolic-rich extract of Astronium urundeuva honey (PhEAH) wasproduced and its pharmacological proprieties were determined. Method: PhEAHwas prepared using a solid-phase extraction column. Next, antibacterial and antifungalactivities were evaluated by broth microdilution method and the antioxidanteffect was investigated using 2,2-Diphenyl-1-picrylhydrazyl (DPPH) assay. Urethralcatheter sensitized with PhEAH were produced and its anti-adhesive and anti-biofilmeffect determined. Finally, antitumoral and antiviral activities were studded using3-(4.5-dimethylthiazol-2-yl)-2.5-diphenyltetrazolium bromide (MTT) test. Results:PhEAH showed an elevated total phenol concentration (PhEAH: 18.7±0.4 mg GA/g vs. fresh honey: 0.99±0.005 mg GA/g). Although PhEAH did not show significantantifungal and antiviral effects, it was moderately active against Gram-negative bacilli(Klebsiella aerogenes, K. pneumoniae, Proteus mirabilis, Pseudomonas aeruginosa andEnterobacter cloacae) and showed increased antibacterial activity against salmonellosispathogens (Salmonella Typhimurium and Salmonella Enteritidis). PhEAH-impregnatedurethral catheters inhibited the growth of various pathogenic bacteria andimpaired the ability of P. aeruginosa to colonize and adhere to it. In addition to its antimicrobialactivity, PhEAH presented antioxidant properties and reduced the viabilityof human glioblastoma cells. Conclusion: in conclusion, our study shows that PhEAHcontains large amounts of phenolic compounds, which are associated with its antibacterial,anti-adhesive, antioxidant, and antitumor effects.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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".