Supplement comprising of laccase and citric acid as an alternative for antibiotics: <i>In vitro</i> triggers of melanin production
Bibliographic record
Abstract
Abstract An indiscriminate use of antibiotics in humans and animals has led to the widespread selection of antibiotic‐resistance, thus constricting the use of antibiotics. A possible solution to counter this problem could be to develop alternatives that can boost the host immunity, thus reducing the quantity and frequency of antibiotic use. In this work, for the first time, citric acid and laccase were used as extracellular inducers of melanin production in yeast cells and human cell lines. It is proposed that the formulation of laccase and citric acid together could further promote melatonin‐stimulated, melanocyte‐derived melanin production. Melanization as a probe of immunity described in this study, is an easy and a rapid test compared to other immunity tests and it allows performing statistical analyses. The results showed the synergistic effect of citric acid and laccase on melanin production by yeast cells, with significant statistical differences compared to all other tested conditions ( p : 0.0005–0.005). Laccase and citric acid together boosted melanin production after 8 days of incubation. An increase in melanin production by two human colon cells lines (Cacao‐2/15 and HT‐29) was observed on supplementation with both laccase and citric acid in the cell growth medium. Produced melanin showed antimicrobial properties similar to antibiotics. Therefore, a formulation with citric acid and laccase may prove to be an excellent alternative to reduce the antibiotic use in human and animal subjects.
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".