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Record W3089234580 · doi:10.1128/mbio.01615-20

Outer Membrane Disruption Overcomes Intrinsic, Acquired, and Spontaneous Antibiotic Resistance

2020· article· en· W3089234580 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenuemBio · 2020
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAntibiotic Resistance in Bacteria
Canadian institutionsMcMaster University
FundersCanadian Institutes of Health ResearchGovernment of Canada
KeywordsBacterial outer membraneAntibiotic resistanceAntibioticsGram-negative bacteriaBacteriaMembrane permeabilityMembraneBiologyMicrobiologyChemistryBiochemistryEscherichia coliGenetics

Abstract

fetched live from OpenAlex

The spread of antibiotic resistance is an urgent threat to global health that necessitates new therapeutics. Treatments for Gram-negative pathogens are particularly challenging to identify due to the robust outer membrane permeability barrier in these organisms. Recent discovery efforts have attempted to overcome this hurdle by disrupting the outer membrane using chemical perturbants and have yielded several new peptides and small molecules that allow the entry of otherwise inactive antimicrobials. However, a comprehensive investigation into the strengths and limitations of outer membrane perturbants as antibiotic partners is currently lacking. Herein, we interrogate the interaction between outer membrane perturbation and several common impediments to effective antibiotic use. Interestingly, we discover that outer membrane disruption is able to overcome intrinsic, spontaneous, and acquired antibiotic resistance in Gram-negative bacteria, meriting increased attention toward this approach.

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.

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 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 score0.402
Threshold uncertainty score0.679

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.010
GPT teacher head0.229
Teacher spread0.220 · 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