Mursamacin: a novel class of antibiotics from soil-dwelling roundworms of Central Kenya that inhibits methicillin-resistant Staphylococcus aureus
Why this work is in the frame
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Bibliographic record
Abstract
<ns4:p> Antibiotic-resistant bacteria, also called “superbugs”, can at worst retrogress modern medicine to an era where even sore throats resulted in death. A solution is the development of novel types of antibiotics from untapped natural sources. Yet, no new class of antibiotic has been developed in clinical medicine in the last 30 years. Here, bacteria from insect-killing <ns4:italic>Steinernema</ns4:italic> roundworms in the soils of Central Kenya were isolated and subjected to specific molecular identification. These were then assayed for production of antibiotic compounds with potential to treat methicillin-resistant <ns4:italic>Staphylococcus aureus</ns4:italic> infections. The bacteria were identified as <ns4:italic>Xenorhabdus griffiniae</ns4:italic> and produced cell free supernatants that inhibited <ns4:italic>S. aureus</ns4:italic> . Fermenting the bacteria for 4 days yielded a heat stable anti-staphylococcal class of compounds that at low concentrations also inhibited methicillin-resistant <ns4:italic>S. aureus</ns4:italic> . This class contained two major compounds whose identity remains unknown. Thus <ns4:italic>X. griffinae</ns4:italic> isolated from <ns4:italic>Steinernema</ns4:italic> roundworms in Kenya have antimicrobial potential and may herald novel and newly sourced potential medicines for treatment of the world’s most prevalent antibiotic resistant bacteria. </ns4:p>
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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 it