Evaluating antibacterial and antioxidant properties of sericin recovered from cocoons of Bombyx mori, Gonometa postica and Samia ricini in Kenya
Bibliographic record
Abstract
Microbial infections and excessive reactive oxygen species are the primary contributors to delays in wound healing with Pseudomonas aeruginosa, Escherichia coli and Staphylococcus aureus as the common wound infection causing bacteria. In fact, wound management has become more challenging since most of these microbes have developed resistance against commonly used conventional antibiotics thus making it necessary to develop natural products with both antibacterial and antioxidant activities. Increasing attention has been paid to silk sericin in the last decade, with limited research focus in Africa. Therefore, this work focus on evaluating antibacterial and antioxidant capacity of sericin recovered from cocoons of domesticated (Bombyx mori, Samia ricini) and wild (Gonometa postica) silkworms in Kenya. Sericin recovery was achieved using high temperature-high pressure method. Results revealed significance interspecies variation in all the parameters. Total flavonoid content ranged between 270±60.1 and 603.3±44.1 mg GAE/100g with S. ricini demonstrating the highest whereas G. postica exhibited the least content. Moreover, S. ricini showed the highest total phenolic content at 780.0±67.6 mg QE/100g while G. postica had the least phenolic content at 330.6±14.6 mg QE/100g. Samia ricini revealed the highest radical scavenging capacity at 40.47 ± 3.76% whereas B. mori sericin extract showed the least radical scavenging ability at 24.6± 2.96%. Furthermore, S. ricini silk sericin extract demonstrated the highest inhibitory activity against Staphylococcus aureus, Pseudomonas aeruginosa and Klebsiella pneumonia which translated to 70.79 ± 11.28%, 93.86 ± 1.92%, 94.77 ± 7.07% when compared to streptomycin, chloramphenicol and oxytetracycline respectively. Bombyx mori and Gonometa postica showed the highest inhibitory activity against S. pyogene and E. coli respectively. These findings uncovered sufficient antibacterial efficacy of all three silk sericin extracts against both Gram-positive and negative bacteria, however, in depth research is still required to guarantee the aforementioned bioactivities to boost the therapeutic potential of silk sericin-based biomaterials.
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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".