Impact of Bacterial Toxins in the Lungs
Bibliographic record
Abstract
Bacterial toxins play a key role in the pathogenesis of lung disease. Based on their structural and functional properties, they employ various strategies to modulate lung barrier function and to impair host defense in order to promote infection. Although in general, these toxins target common cellular signaling pathways and host compartments, toxin- and cell-specific effects have also been reported. Toxins can affect resident pulmonary cells involved in alveolar fluid clearance (AFC) and barrier function through impairing vectorial Na+ transport and through cytoskeletal collapse, as such, destroying cell-cell adhesions. The resulting loss of alveolar-capillary barrier integrity and fluid clearance capacity will induce capillary leak and foster edema formation, which will in turn impair gas exchange and endanger the survival of the host. Toxins modulate or neutralize protective host cell mechanisms of both the innate and adaptive immunity response during chronic infection. In particular, toxins can either recruit or kill central players of the lung’s innate immune responses to pathogenic attacks, i.e., alveolar macrophages (AMs) and neutrophils. Pulmonary disorders resulting from these toxin actions include, e.g., acute lung injury (ALI), the acute respiratory syndrome (ARDS), and severe pneumonia. When acute infection converts to persistence, i.e., colonization and chronic infection, lung diseases, such as bronchitis, chronic obstructive pulmonary disease (COPD), and cystic fibrosis (CF) can arise. The aim of this review is to discuss the impact of bacterial toxins in the lungs and the resulting outcomes for pathogenesis, their roles in promoting bacterial dissemination, and bacterial survival in disease progression.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".