Antimicrobial Potential of Actinomycetes Isolated from Soil of Nepal
Bibliographic record
Abstract
Antimicrobial resistance (AMR) to antibiotics is increasing rapidly, which is a serious public health problem worldwide, so the issue of AMR should be addressed in time. Many studies have been conducted in Nepal to isolate potent Actinomycetes strain from soil and water in various parts of the country. The aim of this review is to find novel Actinomycetes isolates from Nepal producing bioactive compounds capable of suppressing the growth of multidrug-resistant pathogens. Preliminary screening in these studies in Nepal have identified isolates with notable antimicrobial activity against various pathogenic bacteria including Escherichia coli, ESBL E. coli, Staphylococcus, MRSA, Enterococcus faecalis, Klebsiella pneumoniae, Bacillus subtilis, Pseudomonas aeruginosa, Acinetobacter baumannii, Salmonella Typhi and others. Findings from several studies in Nepal indicate that Actinomycetes isolated from different habitats of Nepal can produce a wide array of bioactive compounds like diketopiperazines, actinomycins, bacterial alkaloids, anthramycin-type antibiotics, lipase inhibitors, cytocidal metabolites, antifungal and antitumor antibiotics. In conclusion various regions across Nepal contain novel Actinomycetes strains that can produce novel bioactive compounds and effective antimicrobial drugs to combat the growing problem of AMR.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".