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Record W2332675663 · doi:10.1139/w11-121

Microarray analysis and phenotypic response of<i>Pseudomonas aeruginosa</i>PAO1 under hyperbaric oxyhelium conditions

2012· article· en· W2332675663 on OpenAlexvenueno aff
Shuanghong Chen, Rui-Yong Chen, XU Xiong-li, Xiao Wei-bin

Bibliographic record

VenueCanadian Journal of Microbiology · 2012
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBacterial biofilms and quorum sensing
Canadian institutionsnot available
Fundersnot available
KeywordsPseudomonas aeruginosaVirulenceBiologyMicrobiologyPhenotypeDownregulation and upregulationBiofilmMicroarray analysis techniquesTranscriptomeQuorum sensingGene expression profilingMicroarrayGene expressionPathogenGeneGeneticsBacteria

Abstract

fetched live from OpenAlex

Pseudomonas aeruginosa is an important opportunistic pathogen associated with multiple diseases including cystic fibrosis and nosocomial infections. Pseudomonas aeruginosa is also the microbe most often isolated from ear and skin infections in divers. Saturation divers often suffer from various skin and mucous disorders, of which P. aeruginosa infections are the most serious and frequent. Previous studies mainly focused on adaptive and regulatory mechanisms of P. aeruginosa virulence in inducing clinical acute and chronic infections under different environmental conditions. However, there are few studies describing the physiological adaptive and regulatory mechanisms of P. aeruginosa in inducing high infectivity in healthy divers under hyperbaric oxyhelium conditions and even fewer studies describing the overall influence of the hyperbaric oxyhelium environment on regulating mRNA and protein expression levels of P. aeruginosa. The present study used transcriptomic and virulence phenotype analysis to identify factors that allow P. aeruginosa to become established in a hyperbaric oxyhelium environment to facilitate infections in divers. Transcriptional profiling of P. aeruginosa grown under steady-state hyperbaric oxyhelium stress conditions showed an upregulation of genes associated with stress-sense/response, protein folding, transcriptional regulation, pili and flagellum metabolism, virulence adaptation, and membrane protein metabolism. Some of these genes (including several two-component systems not previously known to be influenced by hyperbaric oxyhelium) were differentially expressed by P. aeruginosa in response to 72 h of exposure to hyperbaric oxyhelium stress. Detection of the virulence phenotype confirmed the results of cDNA microarrays. Based on these results, we conclude that hyperbaric oxyhelium conditions affect PAO1 gene expression and upregulate the expression of most virulence genes. The data obtained in our study may provide new insight into the molecular mechanism of hyperbaric oxyhelium exposure against P. aeruginosa virulence adaptation.

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: Bench or experimental · Consensus signal: Bench or experimental
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)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.008
GPT teacher head0.215
Teacher spread0.207 · 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 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

Citations4
Published2012
Admission routes1
Has abstractyes

Explore more

Same venueCanadian Journal of Microbiology→Same topicBacterial biofilms and quorum sensing→French-language works237,207→