MétaCan
Menu
Back to cohort
Record W2921986645 · doi:10.4103/ijmy.ijmy_153_18

Antimycobacterial strategies to evade antimicrobial resistance in the nontuberculous mycobacteria

2019· review· en· W2921986645 on OpenAlexaff
BeverleyCherie Millar, John E. Moore

Bibliographic record

VenueInternational Journal of Mycobacteriology · 2019
Typereview
Languageen
FieldMedicine
TopicMycobacterium research and diagnosis
Canadian institutionsQueen's University
Fundersnot available
KeywordsAntimycobacterialNontuberculous mycobacteriaRepurposingAntimicrobialMedicineIntensive care medicineBiologyMicrobiologyMycobacteriumTuberculosisMycobacterium tuberculosisPathology

Abstract

fetched live from OpenAlex

The nontuberculous mycobacteria (NTM) have recently emerged as important bacterial pathogens of both animals and humans. Of particular, concern is the high level of antimicrobial resistance (AMR) displayed by these organisms, which complicates treatment and potential successful outcomes. This review, therefore, wishes to examine novel compounds and approaches to combatting AMR in the NTMs, specifically examining antimycobacterial (NTM) compounds from plants and venoms, as well as examining synergistic and combination effects with other antimicrobials. Novel and modified drugs including new inhaled drugs are examined, as well as the repurposing of existing drugs for antimycobacterial activity. Many of these novel interventions are at various stages of development, from initial concept through to licensed intervention. The challenge remains to translate these interventions from in vitro laboratory models to effective in vivo interactions. When these are realized, then we will have the opportunity of overcoming NTM AMR, to the benefit of medicine, society, and humanity.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.830
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0020.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0010.000

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 head0.053
GPT teacher head0.398
Teacher spread0.344 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations22
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueInternational Journal of MycobacteriologySame topicMycobacterium research and diagnosisFrench-language works237,207