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Keywords
- Bordetella pertussis (1)
- Head and neck cancers (1)
- airway epithelia (1)
- cancers and neoplasms (1)
- ciliostasis (1)
- lipids (1)
- malignant tumors (1)
- raman spectroscopy (1)
- salivary gland tumors (1)
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- surgical oncology (1)
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- tracheal cytotoxin (1)
Activity of Tracheal Cytotoxin of Bordetella pertussis in a Human Tracheobronchial 3D Tissue Model
(2021)
Bordetella pertussis is a highly contagious pathogen which causes whooping cough in humans. A major pathophysiology of infection is the extrusion of ciliated cells and subsequent disruption of the respiratory mucosa. Tracheal cytotoxin (TCT) is the only virulence factor produced by B. pertussis that has been able to recapitulate this pathology in animal models. This pathophysiology is well characterized in a hamster tracheal model, but human data are lacking due to scarcity of donor material. We assessed the impact of TCT and lipopolysaccharide (LPS) on the functional integrity of the human airway mucosa by using in vitro airway mucosa models developed by co-culturing human tracheobronchial epithelial cells and human tracheobronchial fibroblasts on porcine small intestinal submucosa scaffold under airlift conditions. TCT and LPS either alone and in combination induced blebbing and necrosis of the ciliated epithelia. TCT and LPS induced loss of ciliated epithelial cells and hyper-mucus production which interfered with mucociliary clearance. In addition, the toxins had a disruptive effect on the tight junction organization, significantly reduced transepithelial electrical resistance and increased FITC-Dextran permeability after toxin incubation. In summary, the results indicate that TCT collaborates with LPS to induce the disruption of the human airway mucosa as reported for the hamster tracheal model.
Pilot study on the value of Raman spectroscopy in the entity assignment of salivary gland tumors
(2021)
Background
The entity assignment of salivary gland tumors (SGT) based on histomorphology can be challenging. Raman spectroscopy has been applied to analyze differences in the molecular composition of tissues. The aim of this study was to evaluate the suitability of RS for entity assignment in SGT.
Methods
Raman data were collected in deparaffinized sections of pleomorphic adenomas (PA) and adenoid cystic carcinomas (ACC). Multivariate data and chemometric analysis were completed using the Unscrambler software.
Results
The Raman spectra detected in ACC samples were mostly assigned to nucleic acids, lipids, and amides. In a principal component-based linear discriminant analysis (LDA) 18 of 20 tumor samples were classified correctly.
Conclusion
In this proof of concept study, we show that a reliable SGT diagnosis based on LDA algorithm appears possible, despite variations in the entity-specific mean spectra. However, a standardized workflow for tissue sample preparation, measurement setup, and chemometric algorithms is essential to get reliable results.