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Record W4283756161 · doi:10.1101/2022.06.27.497873

Natural products lysobactin and sorangicin A show in vitro activity against <i>Mycobacterium abscessus</i> complex

2022· preprint· en· W4283756161 on OpenAlexaff
Jaryd Sullivan, Jacqueline Yao, Christophe Courtine, Andréanne Lupien, Jennifer Herrmann, Rolf Müller, Marcel A. Behr

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2022
Typepreprint
Languageen
FieldMedicine
TopicMycobacterium research and diagnosis
Canadian institutionsMcGill UniversityMcGill University Health Centre
Fundersnot available
KeywordsMycobacterium abscessusAntibioticsMicrobiologyNontuberculous mycobacteriaCystic fibrosisPathogenMedicineNatural historyMycobacteriumBiologyTuberculosisInternal medicinePathology

Abstract

fetched live from OpenAlex

Abstract The prevalence of lung disease caused by Mycobacterium abscessus is increasing among patients with cystic fibrosis. M. abscessus is a multidrug resistant opportunistic pathogen that is notoriously difficult to treat due to a lack of efficacious therapeutic regimens. Currently, there are no standard regimens, and treatment guidelines are based empirically on drug susceptibility testing. Thus, novel antibiotics are required. Natural products represent a vast pool of biologically active compounds that have a history of being a good source of antibiotics. Here, we screened a library of 517 natural products purified from fermentations of various bacteria and fungi against M. abscessus ATCC 19977. Lysobactin and sorangicin A were active against the M. abscessus complex and drug resistant clinical isolates. These natural products merit further consideration to be included in the M. abscessus drug pipeline.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0030.001

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 head0.022
GPT teacher head0.256
Teacher spread0.234 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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
Published2022
Admission routes1
Has abstractyes

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