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Record W2141682747 · doi:10.1002/psc.1319

Bacterial membrane lipids in the action of antimicrobial agents

2010· review· en· W2141682747 on OpenAlex
Richard M. Epand

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

VenueJournal of Peptide Science · 2010
Typereview
Languageen
FieldImmunology and Microbiology
TopicAntimicrobial Peptides and Activities
Canadian institutionsMcMaster University
FundersCanadian Institutes of Health Research
KeywordsAntimicrobialBacteriaCationic polymerizationBacterial cell structureAntimicrobial peptidesMembraneChemistryMembrane lipidsCell membraneBiochemistryLipid APeptideCellGram-negative bacteriaMicrobiologyBiologyEscherichia coliOrganic chemistry

Abstract

fetched live from OpenAlex

Many antimicrobial agents that target bacteria are cationic and can interact with the anionic lipid components that are exposed on the bacterial membrane. Bacteria vary widely in the nature of the major lipid components that are in the cell membrane. Those bacteria with both anionic as well as zwitterionic or neutral lipids can be induced to form domains in the presence of antimicrobial peptides possessing several cationic charges. This segregation of anionic and zwitterionic lipids into domains can result in the arrest of cell growth or in cell death. Such agents are generally more toxic to Gram-negative bacteria, than to Gram-positive ones. These findings emphasize the importance of the lipid composition of bacterial membranes in determining the susceptibility of the organism to the action of certain antimicrobial agents.

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)0.003
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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.974
Threshold uncertainty score0.732

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.002
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 head0.049
GPT teacher head0.327
Teacher spread0.278 · 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