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Record W6976932828 · doi:10.60692/p6aqk-h3w07

Mursamacin: a novel class of antibiotics from soil-dwelling roundworms of Central Kenya that inhibits methicillin-resistant Staphylococcus aureus

2017· article· en· W6976932828 on OpenAlexaff

Bibliographic record

VenueGreater South Information System · 2017
Typearticle
Languageen
FieldEngineering
TopicSatellite Communication Systems
Canadian institutionsCareer Trek
Fundersnot available
KeywordsAntibioticsStaphylococcus aureusBacteriaAntimicrobialAntibiotic resistanceStaphylococcus

Abstract

fetched live from OpenAlex

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 Steinernema roundworms found 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 Staphylococcus aureus infections. The bacteria were identified as Xenorhabdus griffiniae and produced cell free supernatants that inhibited S. aureus. Fermenting the bacteria for 4 days yielded a heat stable anti-staphylococcal class of compounds that at low concentrations also inhibited methicillin-resistant S. aureus. This class contained two major compounds whose identity remains unknown. Thus X. griffinae isolated from Steinernema 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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.565
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.062
GPT teacher head0.235
Teacher spread0.173 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2017
Admission routes1
Has abstractyes

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