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Record W4362574992 · doi:10.22215/etd/2022-15390

Time-course proteomic study of Acinetobacter baumannii after exposure to oxidative stress

2022· dissertation· en· W4362574992 on OpenAlexaff
Vanessa Gallo

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAntibiotic Resistance in Bacteria
Canadian institutionsCarleton University
Fundersnot available
KeywordsAcinetobacter baumanniiVirulenceMicrobiologyOxidative stressBiologyProteomicsPathogenBacteriaMultiple drug resistanceAntibioticsComputational biologyGeneGeneticsBiochemistry

Abstract

fetched live from OpenAlex

Acinetobacter baumannii is an opportunistic nosocomial Gram-negative bacterium responsible for infectious diseases.Due to its rapidly growing multidrug resistance (MDR), there is a need to improve understanding of host-pathogen interactions to identify targets for the development of novel therapeutics.Characterizing bacterial responses to a stress condition representative of a host environment was hypothesized to provide improved understanding of A. baumannii pathogenesis.To this end, an in vitro time-course proteomic study evaluating the impact of oxidative stress on two clinical strains exhibiting different levels of virulence was performed using mass spectrometry.After exposure to hydrogen peroxide, 38 proteins and 181 proteins were observed to have different abundance levels in strain Lac-4 and Lac-5, respectively.The putative localization, pathway and molecular function of these proteins were assessed.Proteins that changed abundance levels were of interest as they indicate potential response to stress and could lead to targets for future therapeutic development.iii

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.005
GPT teacher head0.265
Teacher spread0.260 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations0
Published2022
Admission routes1
Has abstractyes

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