Stingless Bee Honey Stick Deodorant: Formulation, Antioxidant and Antimicrobial Activities
Why this work is in the frame
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Bibliographic record
Abstract
Introduction: Deodorant often contain ingredients like aluminium salts, triclosan, fragrances, propylene glycol, and parabens that are usually associated with skin irritation and other health conditions. This study addresses the problem by formulating and characterising a natural deodorant that was free from these ingredients by using stingless bee honey (SBH) as an antibacterial and antioxidant ingredient. SBH, recognised for its efficacy in inhibiting the proliferation of odour-producing bacteria like Staphylococcus sp, was integrated into a stick deodorant formulation owing to its significant benefits. Methods: The evaluation of SBH began with testing its antioxidant activity, including total phenolic content (TPC), total flavonoid content (TFC) and DPPH assay. Thereafter, the minimum inhibitory concentration (MIC) and minimum bactericidal concentration (MBC) were determined. Based on the MIC value, an SBH-stick deodorant was formulated and then characterised based on its pH, softening point, antimicrobial study by using well diffusion method and stability study (30 °C ± 2 °C /75% RH ± 5%) for two weeks. Results: The TPC and TFC in this study were 57.99 ± 0.38 mg GAE/100g and 0.132 ± 0.04 mg QE/mL, respectively. Meanwhile, the DPPH scavenging activity was 66.78 ± 0.45%. The result showed that 20% w/w and 50% w/w of SBH were needed as MIC and MBC, respectively. The formulated stick deodorant was reported to have suitable pH, softening point and exhibit its antibacterial activity towards Staphyloccoccus aureus after being formulated as deodorant. It was also stable during the two weeks of storage. Conclusion: The SBH stick deodorant was successfully formulated and demonstrated potential antibacterial activity against Staphylococcus aureus, a known body-odour causing bacteria. These findings highlight the potential application of SBH as a natural antibacterial agent in personal care products, offering a promising alternative to synthetic deodorants.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 it