Microarray analysis and phenotypic response of<i>Pseudomonas aeruginosa</i>PAO1 under hyperbaric oxyhelium conditions
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".