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Record W2400984801 · doi:10.4155/fmc-2016-0017

<i>Pseudomonas Aeruginosa</i> : Targeting Cell-Wall Metabolism for New Antibacterial Discovery and Development

2016· review· en· W2400984801 on OpenAlexaff
Ryan P. Lamers, Lori L. Burrows

Bibliographic record

VenueFuture Medicinal Chemistry · 2016
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAntibiotic Resistance in Bacteria
Canadian institutionsMcMaster University
Fundersnot available
KeywordsPseudomonas aeruginosaAntibioticsMicrobiologyBiologyBacteriaAntibiotic resistanceGenetics

Abstract

fetched live from OpenAlex

Pseudomonas aeruginosa is a leading cause of hospital-acquired infections and is resistant to most antibiotics. With therapeutic options against P. aeruginosa dwindling, and the lack of new antibiotics in advanced developmental stages, strategies for preserving the effectiveness of current antibiotics are urgently required. β-Lactam antibiotics are important agents for treating P. aeruginosa infections, thus, adjuvants that potentiate the activity of these compounds are desirable for extending their lifespan while new antibiotics - or antibiotic classes - are discovered and developed. In this review, we discuss recent research that has identified exploitable targets of cell-wall metabolism for the design and development of compounds that hinder resistance and potentiate the activity of antipseudomonal β-lactams.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.005
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.003

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 head0.011
GPT teacher head0.263
Teacher spread0.251 · 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 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

Citations14
Published2016
Admission routes1
Has abstractyes

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