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Record W2951458531 · doi:10.1371/journal.pntd.0007126

Triple oral beta-lactam containing therapy for Buruli ulcer treatment shortening

2019· article· en· W2951458531 on OpenAlexaff
María Pilar Arenaz-Callao, Rubén González del Río, Ainhoa Lucía, Charles J. Thompson, Alfonso Mendoza-Losana, Santiago Ramón‐García

Bibliographic record

VenuePLoS neglected tropical diseases · 2019
Typearticle
Languageen
FieldMedicine
TopicMycobacterium research and diagnosis
Canadian institutionsUniversity of British Columbia
FundersUniversidad de ZaragozaFP7 People: Marie-Curie ActionsEuropean CommissionGlaxoSmithKline
KeywordsClarithromycinBuruli ulcerRifampicinMedicineAntibioticsMycobacterium ulceransAmoxicillinPharmacologyMinimum inhibitory concentrationMicrobiologyInternal medicineBiologyDisease

Abstract

fetched live from OpenAlex

The potential use of clinically approved beta-lactams for Buruli ulcer (BU) treatment was investigated with representative classes analyzed in vitro for activity against Mycobacterium ulcerans. Beta-lactams tested were effective alone and displayed a strong synergistic profile in combination with antibiotics currently used to treat BU, i.e. rifampicin and clarithromycin; this activity was further potentiated in the presence of the beta-lactamase inhibitor clavulanate. In addition, quadruple combinations of rifampicin, clarithromycin, clavulanate and beta-lactams resulted in multiplicative reductions in their minimal inhibitory concentration (MIC) values. The MIC of amoxicillin against a panel of clinical isolates decreased more than 200-fold within this quadruple combination. Amoxicillin/clavulanate formulations are readily available with clinical pedigree, low toxicity, and orally and pediatric available; thus, supporting its potential inclusion as a new anti-BU drug in current combination therapies.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.145
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.042
GPT teacher head0.311
Teacher spread0.270 · 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

Citations19
Published2019
Admission routes1
Has abstractyes

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