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To study the interaction of human pathogens with their host target structures, human tissue models based on primary cells are considered suitable. Complex tissue models of the human airways have been used as infection models for various viral and bacterial pathogens. The Gram-negative bacterium Bordetella pertussis is of relevant clinical interest since whooping cough has developed into a resurgent infectious disease. In the present study, we created three-dimensional tissue models of the human ciliated nasal and tracheo-bronchial mucosa. We compared the innate immune response of these models towards the B. pertussis virulence factor adenylate cyclase toxin (CyaA) and its enzymatically inactive but fully pore-forming toxoid CyaA-AC\(^-\). Applying molecular biological, histological, and microbiological assays, we found that 1 µg/ml CyaA elevated the intracellular cAMP level but did not disturb the epithelial barrier integrity of nasal and tracheo-bronchial airway mucosa tissue models. Interestingly, CyaA significantly increased interleukin 6, interleukin 8, and human beta defensin 2 secretion in nasal tissue models, whereas tracheo-bronchial tissue models were not significantly affected compared to the controls. Subsequently, we investigated the interaction of B. pertussis with both differentiated primary nasal and tracheo-bronchial tissue models and demonstrated bacterial adherence and invasion without observing host cell type-specific significant differences. Even though the nasal and the tracheo-bronchial mucosa appear similar from a histological perspective, they are differentially susceptible to B. pertussis CyaA in vitro. Our finding that nasal tissue models showed an increased innate immune response towards the B. pertussis virulence factor CyaA compared to tracheo-bronchial tissue models may reflect the key role of the nasal airway mucosa as the first line of defense against airborne pathogens.
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.