<i>Pseudomonas aeruginosa-</i> mediated cardiac dysfunction is driven by extracellular vesicles released during infection
Bibliographic record
Abstract
Abstract Pseudomonas aeruginosa (P.a.) is a gram-negative, opportunistic bacterium abundantly present in the environment. Often P.a. infections cause severe pneumonia, if left untreated. Surprisingly, up to 30% of patients admitted to the hospital for community- acquired pneumonia develop adverse cardiovascular complications such as myocardial infarction, arrhythmia, left ventricular dysfunction, and heart failure. However, the underlying mechanism of infection-mediated cardiac dysfunction is not yet known. Recently, we demonstrated that P.a. infection of the lungs led to severe cardiac electrical abnormalities and left ventricular dysfunction with limited P.a. dissemination to the heart tissue. To understand the mechanism of cardiac dysfunction during P.a. infection, we utilized both in vitro and in vivo models. Our results revealed that inflammatory cytokines contribute but are not solely responsible for severe contractile dysfunction in human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs). Instead, exposure of hiPSC-CMs with conditioned media from P.a. infected human monocyte-derived macrophages (hMDMs) was sufficient to cause severe contractile dysfunction and arrhythmia in hiPSC-CMs. Specifically, exosomes released from infected hMDMs and bacterial outer membrane vesicles (OMVs) are the major drivers of cardiomyocyte contractile dysfunction. By using LC-MS/MS, we identified bacterial proteins, including toxins that are packaged in the exosomes and OMVs, which are responsible for contractile dysfunction. Furthermore, we demonstrated that systemic delivery of bacterial OMVs to mice caused severe cardiac dysfunction, mimicking the natural bacterial infection. In summary, we conclude that OMVs released during infection enter circulation and drive cardiac dysfunction.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".