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Record W2021489331 · doi:10.1002/jrs.1624

Interactions of lactoferricin B derivatives with model cell membrane studied by Raman spectroscopy

2006· article· en· W2021489331 on OpenAlexafffund
Anatoli Ianoul, Harrison J. Westwick, L. Nowacka, Bryan D. Quan

Bibliographic record

VenueJournal of Raman Spectroscopy · 2006
Typearticle
Languageen
FieldImmunology and Microbiology
TopicAntimicrobial Peptides and Activities
Canadian institutionsCarleton University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsChemistryVesicleRaman spectroscopyMembraneCrystallographyPeptideLipid bilayerCooperativityRandom coilBiophysicsAmideBiochemistryCircular dichroismBiology

Abstract

fetched live from OpenAlex

Abstract In this work, we employed Raman spectroscopy to study the effect of the antimicrobial peptide lactoferricin B (LfB) on model cell membranes. We used two derivatives of LfB (RRWQWRMKKLG and RRWQWR) with broad‐spectrum activity against gram‐positive and gram‐negative bacteria, fungus, viruses and tumors. Raman spectra of the peptides showed no conformational change in the temperature range 4–60 °C. The positions of the amide I and amide III bands suggest that in an aqueous solution these peptides preferentially adopt a random coil‐like conformation. We also investigated the effect the peptides had on the melting behavior of model cell membranes composed of zwitterionic lipid dipalmitoylglycero‐phosphocholine (DPPC) and anionic lipid dipalmitoylglycero‐phosphoglycerol (DPPG). Raman CH stretching bands were used to follow the melting of the lipid vesicles. We found that the melting of DPPC lipid vesicles is not affected by the presence of the peptides, while the presence of the peptides reduced cooperativity of the phase transition for anionic DPPG vesicle, suggesting that both peptides interact strongly and specifically with this model cell membrane composed of anionic lipid. Copyright © 2006 John Wiley & Sons, Ltd.

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)0.000
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 score0.035
Threshold uncertainty score0.946

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.007
GPT teacher head0.234
Teacher spread0.227 · 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.

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

Citations9
Published2006
Admission routes2
Has abstractyes

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