Characterization of Host and Bacterial Contributions to Lung Barrier Dysfunction Following Co-infection with 2009 Pandemic Influenza and Methicillin Resistant Staphylococcus aureus
Bibliographic record
Abstract
Influenza viruses are a threat to global public health resulting in ~500,000 deaths each year. Despite an intensive vaccination program, influenza infections remain a recurrent, yet unsolved public health problem. Secondary bacterial infections frequently complicate influenza infections during seasonal outbreaks and pandemics, resulting in increased morbidity and mortality. Staphylococcus aureus, including methicillin-resistant S. aureus (MRSA), is frequently associated with these co-infections, including the 2009 influenza pandemic. Damage to alveolar epithelium is a major contributor to severe influenza-bacterial co-infections and can result in gas exchange abnormalities, fluid leakage, and respiratory insufficiency. These deleterious manifestations likely involve both pathogen- and host-mediated mechanisms. However, there is a paucity of information regarding the mechanisms (pathogen- and/or host-mediated) underlying influenza-bacterial co-infection pathogenesis. To address this, we characterized the contributions of viral-, bacterial-, and host-mediated factors to the altered structure and function of alveolar epithelial cells during co-infection with a focus on the 2009 pandemic influenza (pdm2009) and MRSA. Here, we characterized pdm2009 and MRSA replication kinetics, temporal host kinome responses, modulation of MRSA virulence factors, and disruption of alveolar barrier integrity in response to pdm2009-MRSA co-infection. Our results suggest that alveolar barrier disruption during co-infection is mediated primarily through host response dysregulation, resulting in loss of alveolar barrier integrity.
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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".