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Record W4378234186 · doi:10.3390/biomedicines11061515

Modulation of Klebsiella pneumoniae Outer Membrane Vesicle Protein Cargo under Antibiotic Treatment

2023· article· en· W4378234186 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

VenueBiomedicines · 2023
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAntibiotic Resistance in Bacteria
Canadian institutionsUniversité Laval
FundersFundação Oswaldo CruzConselho Nacional de Desenvolvimento Científico e TecnológicoCoordenação de Aperfeiçoamento de Pessoal de Nível Superior
KeywordsKlebsiella pneumoniaeMicrobiologyBacterial outer membraneAntibioticsModulation (music)ChemistryBiologyEscherichia coliBiochemistryGenePhysics

Abstract

fetched live from OpenAlex

Klebsiella pneumoniae is a nosocomial pathogen and an important propagator of multidrug-resistant (MDR) and extensively drug-resistant (XDR) strains. Like other Gram-negative bacteria, they secrete outer membrane vesicles (OMVs) that distribute virulence and resistance factors. Here, we subjected a K. pneumoniae-XDR to subinhibitory concentrations of meropenem, amikacin, polymyxin B, and a combination of these agents to evaluate changes in the protein cargo of OMVs through liquid chromatography–tandem mass spectrometry (LC-MS/MS). Genome sequencing of the clinical isolate K. pneumoniae strain HCD1 (KpHCD1) revealed the presence of 41 resistance genes and 159 virulence factors. We identified 64 proteins in KpHCD1-OMVs modulated with different antibiotic treatments involved in processing genetic information, environmental information, cell envelope formation, energy metabolism, and drug resistance. The OMV proteome expression profile suggests that OMVs may be associated with pathogenicity, survival, stress response, and resistance dissemination.

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 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 score0.139
Threshold uncertainty score0.485

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.017
GPT teacher head0.269
Teacher spread0.252 · 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