MétaCan
Menu
Back to cohort
Record W3084981380 · doi:10.1093/femspd/ftaa053

Cruzioseptins, antibacterial peptides from <i>Cruziohyla calcarifer</i> skin, as promising leishmanicidal agents

2020· article· en· W3084981380 on OpenAlexfundno aff
Bruno Mendes, Carolina Proaño‐Bolaños, Fernanda Ramos Gadelha, José R. Almeida, Danilo C. Miguel

Bibliographic record

VenuePathogens and Disease · 2020
Typearticle
Languageen
FieldMedicine
TopicResearch on Leishmaniasis Studies
Canadian institutionsnot available
FundersUniversidade Estadual de CampinasQueen's UniversityCoordenação de Aperfeiçoamento de Pessoal de Nível SuperiorQueen's University BelfastUnited Nations Development ProgrammeUnited Nations
KeywordsAmastigoteEC50Antimicrobial peptidesLeishmaniaBiologyAntimicrobialIn vivoIn vitroMicrobiologyLeishmania braziliensisBiofilmLeishmaniasisCutaneous leishmaniasisPharmacologyBiochemistryChemistryParasite hostingBacteriaImmunologyBiotechnology

Abstract

fetched live from OpenAlex

Screenings of natural products have significantly contributed to the discovery of novel leishmanicidal agents. In this study, three known cruzioseptins-antibacterial peptides from Cruziohyla calcarifer skin-were synthesized and evaluated against promastigotes and amastigotes stages of Leishmania (L.) amazonensis and L. (V.) braziliensis. EC50 ranged from 9.17 to 74.82 μM, being cruzioseptin-1 the most active and selective compound, with selectivity index > 10 for both promastigotes and amastigotes of L. (V.) braziliensis. In vitro infections incubated with cruzioseptins at 50 μM showed up to ∼86% reduction in the amastigote number. Cruzioseptins were able to destabilize the parasite's cell membrane, allowing the incorporation of a DNA-fluorescent dye. Our data also demonstrated that hydrophobicity and charge appear to be advantageous features for enhancing parasiticidal activity. Antimicrobial cruzioseptins are suitable candidates and alternative molecules that deserve further in vivo investigation focusing on the development of novel antileishmanial therapies.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.571
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 integrity0.0000.000
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 head0.035
GPT teacher head0.293
Teacher spread0.258 · 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.

Study designObservational
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

Citations14
Published2020
Admission routes1
Has abstractyes

Explore more

Same venuePathogens and DiseaseSame topicResearch on Leishmaniasis StudiesFrench-language works237,207