Antimicrobial Activities of Extracts and Flavonoid Glycosides of Corn Silk (Zea mays L)
Bibliographic record
Abstract
Corn silk refers to the stigmas of Zea mays L. ( Gramineae ) from the female flowers of maize. It is medicinally used in a number of diseases and contained a number of flavonoids. Screening of plants against pathogenic bacteria is an important step to validate its medicinal properties. Therefore, the aim of this study was to screen the antimicrobial activities of different solvent extracts, flavonoids of corn silk and compare the activities with standard antibiotic gentamycin. The pet-ether (PECS), chloroform (CECS) and methanol (MECS) extracts (25 mg/mL) of corn silk were tested for their antimicrobial activity. Twelve pathogenic bacteria such as Bacillus cereus, Bacillus subtilis, Staphylococcus aureus, Pseudomonas aeruginosa, Enterobacter aerogenase, Salmonella typhi, Salmonella paratyphi, Escherichia coli, Shigella sonneii, Shigella flexneri, Proteus vulgaris, Proteus mirabilis and one fungus Candida albicans were used to screen the extracts. Gentamycin (50 mg/mL) was used as reference antibiotic. Two isolated flavonoid glycosides (2.0 mg/mL) of corn silk were tested for their antimicrobial activity. The microbial growth inhibitory potential was determined by using the agar hole-plate diffusion method. PECS, MECS and flavonoids were sensitive against eleven bacteria out of twelve bacteria. CECS was sensitive only against five bacteria. No extracts and flavonoids were sensitive against Escherichia coli and Candid albicans . The results were compared with gentamycin, which was sensitive against all the bacteria tested. Extracts and flavonoids showed significantly (p<0.05) higher sensitivity against a number of bacteria than gentamycin.
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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 | 0.001 | 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".