TRAIL-mediated armA upregulation enhances the drug resistance of Klebsiella pneumoniae by activating the PI3K/AKT/mTOR signaling pathway
Bibliographic record
Abstract
Objective: This study aimed to investigate the roles and mechanisms of tumor necrosis factor-related apoptosis-inducing ligand (TRAIL) in the drug resistance of Klebsiella pneumoniae, focusing on its regulation of the aminoglycoside resistance methylase (armA) and the phosphatidylinositol-3-kinase (PI3K)/protein kinase B (AKT)/ mammalian target of rapamycin (mTOR) signaling pathway.Methods: A549 cells were infected with drug-resistant Klebsiella pneumoniae and treated with meropenem.TRAIL overexpression and knockdown were performed using plasmids and small interfering RNA, respectively.Cell viability, apoptosis, and the levels of inflammatory cytokines including tumor necrosis factor- (TNF-), interleukin-6 (IL-6), and interleukin-1 (IL-1) were assessed.The mRNA expression of armA was examined using reverse transcription quantitative polymerase chain reaction (RT-qPCR).The expression of key proteins in the PI3K/AKT/mTOR pathway was evaluated using western blots.Results: Drugresistant Klebsiella pneumoniae infection reduced A549 cell viability, promoted apoptosis, and increased TNF-, IL-6, and IL-1 levels.Meropenem treatment failed to reverse these effects, confirming the drug resistance.TRAIL overexpression exacerbated Klebsiella pneumoniae infection-induced viability inhibition, apoptosis, and inflammation, suggesting that TRAIL enhances the drug resistance of Klebsiella pneumoniae.In contrast, TRAIL knockdown showed the opposite results.TRAIL overexpression upregulated armA expression and activated the PI3K/AKT/ mTOR pathway, but armA inhibition reversed TRAIL-mediated drug resistance and PI3K/AKT/mTOR activation.Conclusion: TRAIL-mediated armA upregulation enhanced the drug resistance of Klebsiella pneumoniae by activating the PI3K/AKT/mTOR signaling pathway.These findings provide new insight into the drug resistance mechanisms of Klebsiella pneumoniae.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".