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Short Antimicrobial Peptides and Peptide Scaffolds as Promising Antibacterial Agents

2016· review· en· W2342247785 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.

Bibliographic record

VenueCurrent Topics in Medicinal Chemistry · 2016
Typereview
Languageen
FieldImmunology and Microbiology
TopicAntimicrobial Peptides and Activities
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsAntimicrobialAntimicrobial peptidesPeptidomimeticAntibioticsPeptideBacteriaCombinatorial chemistryChemistryBiologyComputational biologyMicrobiologyBiochemistry

Abstract

fetched live from OpenAlex

Antimicrobial peptides have recently garnered significant attention as an emerging source of potential antibiotics, due to the swift emergence of multidrug-resistant bacteria and a dwindling antibiotic pipeline. The vast majority of antimicrobial peptides are long, comprised of more than 10 amino acids, resulting in significant production costs for their synthesis while simultaneously displaying metabolic instability and relatively poor pharmacological profiles. To counter these problems, efforts have been shifted to shorter molecules and the development of new peptidomimetic approaches. In this paper, we review promising short, naturally-isolated or synthetic, antimicrobial peptides, along with their mimics, and discuss their merits as potential antibacterial 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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.967
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.040
GPT teacher head0.333
Teacher spread0.293 · 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