Application of methyl fatty hydroxamic acids based on Jatropha curcas seed oil and their metal complexes as anti microbial agents
Bibliographic record
Abstract
Hydroxamic acids, fatty hydroxamic acids and their metal complexes are known as compounds that have biological activity. They have been investigated as antimicrobial compounds and were applied as antibacterial and antifungal agents in pharmacy andpharmaceutical compounds. In this research, the methyl fatty hydroxamic acids (MFHAs) based on Jatrophacurcas seed oil and their metal complexes include the copper (II) methyl fatty hydroxamate (Cu-MFHs) and iron (III) methyl fatty hydroxamate (Fe-MFHs) were prepared and applied as anti microbial agents against the Escherichia coli (E. coli), Proteus vulgaris (P. vulgaris) andProteus mirabilis (P. mirabilis) as gramnegative bacteria; methicillin-resistant Staphylococcus aureus (MRSA) and Staphylococcus epidermidis (S. epidermidis) as gram-positive bacteria ; Candida parapsilosis (C. parapsilosis) and Candida Albicans(C. Albicans) as yeast family of fungi. The results showed that the antimicrobial activity of MFHAs, Cu-MFHs and Fe-MFHs increase while their amounts increase. Also metal complexation of MFHAs caused the anti microbial activity arise and this activity is higher for complexation by Cu(II) compared to that of Fe(III). Comparing antimicrobial activity of MFHAs, Cu-MFHs andFe-MFHs based on Jatrophacurcas seed oil with several antibiotic drugs such as ampicillin, chloramphenicol, gentamicin streptomycin, tetracycline and nystatin against the mentioned microbial showed that the Cu-MFHs andFe-MFHs have very strong antimicrobial activity.
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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 | 0.000 | 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".