Tracheal ultrasonography was performed to measure the width of the tracheal ring shadow and to assess the clinical relevance of these measurements for identifying tracheal collapse. The first tracheal ring width (FTRW) and thoracic inlet tracheal ring width (TITRW) were measured on both expiration and inspiration. The mean of the FTRW width (129 dogs) was greater in expiration (10.97 +/- 1.02 mm, p = 0.001) than that in inspiration (9.86 +/- 1.03 mm). For 51 normal dogs, the mean of the TITRW width was greater in expiration (9.05 +/- 1.52 mm, p = 0.001) than in inspiration (8.02 +/- 1.43 mm). For 78 tracheal collapse dogs, the mean of the TITRW width was greater in expiration (15.89 +/- 1.01 mm, p = 0.001) than in inspiration (14.85 +/- 1.17 mm). The TITRW/FTRW ratio of the normal dogs was higher (p = 0.001) in expiration (0.81 +/- 0.09) than that in inspiration (0.79 +/- 0.10). When compared between the normal and tracheal collapse dogs, the TITRW/FTRW ratio was also increased (p = 0.001) both in expiration (1.54 +/- 0.09) and inspiration (1.47 +/- 0.08), respectively. Based on these results, the cutoff level of the TITRW/FTRW ratio was statistically analyzed according to the receiver operating characteristic curve and it could be set at 1.16 in expiration and at 1.13 in inspiration. We have demonstrated that tracheal ultrasonography is a useful technique for the evaluation of tracheal collapse and it can be a supportive tool together with the radiographic findings for making the correct diagnosis.
Animals ; Dog Diseases/diagnosis/pathology/*ultrasonography ; Dogs ; Female ; Male ; Radiography, Thoracic/*veterinary ; Sensitivity and Specificity ; Trachea/*pathology/radiography ; Tracheal Stenosis/diagnosis/pathology/veterinary

Background: Proteomics and genomics studies have contributed to understanding the pathogenesis of chronic obstructive pulmonary disease (COPD), but previous studies have limitations. Here, using a machine learning (ML) algorithm, we attempted to identify pathways in cultured bronchial epithelial cells of COPD patients that were significantly affected when the cells were exposed to a cigarette smoke extract (CSE). Methods: Small airway epithelial cells were collected from patients with COPD and those without COPD who underwent bronchoscopy. After expansion through primary cell culture, the cells were treated with or without CSEs, and the proteomics of the cells were analyzed by mass spectrometry. ML-based feature selection was used to determine the most distinctive patterns in the proteomes of COPD and non-COPD cells after exposure to smoke extract.Publicly available single-cell RNA sequencing data from patients with COPD (GSE136831) were used to analyze and validate our findings. Results: Five patients with COPD and five without COPD were enrolled, and 7,953 proteins were detected. Ferroptosis was enriched in both COPD and non-COPD epithelial cells after their exposure to smoke extract. However, the ML-based analysis identified ferroptosis as the most dramatically different response between COPD and non-COPD epithelial cells, adjusted P value = 4.172 × 10−6 , showing that epithelial cells from COPD patients are particularly vulnerable to the effects of smoke. Single-cell RNA sequencing data showed that in cells from COPD patients, ferroptosis is enriched in basal, goblet, and club cells in COPD but not in other cell types. Conclusion Our ML-based feature selection from proteomic data reveals ferroptosis to be the most distinctive feature of cultured COPD epithelial cells compared to non-COPD epithelial cells upon exposure to smoke extract.