A Performance Comparison of Different YOLOv7 Networks for High-Accuracy Cell Classification in Bronchoalveolar Lavage Fluid Utilising the Adam Optimiser and Label Smoothing.

Accurate classification of cells in bronchoalveolar lavage (BAL) fluid is essential for the assessment of lung disease in pneumology and critical care medicine. However, the effectiveness of BAL fluid analysis is highly dependent on individual expertise. Our research is focused on improving the accuracy and efficiency of BAL cell classification using the "You Only Look Once" (YOLO) algorithm to reduce variability and increase the accuracy of cell detection in BALF analysis.

Late stage melanoma is hallmarked by low NLGN4X expression leading to HIF1A accumulation.

Background: Despite ongoing research and recent advances in therapy, metastatic melanoma remains one of the cancers with the worst prognosis. Here we studied the postsynaptic cell adhesion molecule Neuroligin 4X (NLGN4X) and investigated its role in melanoma progression.

Methods: We analysed histologic samples to assess the expression and predictive value of NLGN4X in human melanoma.

[Diagnostics of Interstitial Lung Diseases - Practical Instructions with a Focus on Rheumatologic Systemic Diseases].

Interstitial lung diseases (ILD) are etiologically heterogeneous with unknown and known causes like rheumatologic systemic diseases differing in their therapeutic and prognostic consequences. In consensus between pulmonologists, rheumatologists, radiologists, and pathologists, we developed practical instructions for ILD diagnosis in rheumatologic systemic diseases, in particular because ILD can present in early stages of rheumatic systemic diseases. ILD diagnosis is based on clinical assessment results including a detailed medical history, physical examination, focused laboratory tests, radiology with a high-resolution computed tomography, lung function, and histopathology also to differentiate it from cardiac and infection associated lung diseases.