ABSTRACT
OBJECTIVES: To summarise the clinical presentation and outcomes in a series of miniature schnauzers diagnosed with histiocytic sarcoma. MATERIALS AND METHODS: Retrospective review of medical records of miniature schnauzers diagnosed with histiocytic sarcoma between 2008 and 2019 at two referral centres in the UK. Signalment, clinical signs at initial presentation, imaging results and clinico- and histopathological findings, treatment type and outcome were recorded. Progression-free survival and overall survival time were calculated. RESULTS: Thirty dogs were included. Twenty-four of 29 dogs undergoing imaging of the thorax had lung and/or mediastinal involvement. The median overall survival time for dogs that were not euthanased within 3 days of diagnosis was 117 days (range 10 to 790). Three dogs underwent surgery; 13 received treatment with lomustine as a sole therapy - with partial responses documented on imaging in five of six dogs and 11 of 13 showing clinical improvement. CLINICAL SIGNIFICANCE: Histiocytic sarcoma should be considered as a differential diagnosis for miniature schnauzers with pulmonary masses. Although responses to treatment were common, they were usually short-lived because of the aggressive nature of the disease.
Subject(s)
Dog Diseases , Histiocytic Sarcoma/veterinary , Animals , Dogs , Lomustine , Retrospective StudiesABSTRACT
Understanding the numerous functions of RNAs depends critically on the knowledge of their three-dimensional (3D) structure. In contrast to the protein field, a much smaller number of RNA 3D structures have been assessed using X-ray crystallography, NMR spectroscopy, and cryomicroscopy. This has led to a great demand to obtain the RNA 3D structures using prediction methods. The 3D structure prediction, especially of large RNAs, still remains a significant challenge and there is still a great demand for high-resolution structure prediction methods. In this chapter, we describe RNAComposer, a method and server for the automated prediction of RNA 3D structures based on the knowledge of secondary structure. Its applications are supported by other automated servers: RNA FRABASE and RNApdbee, developed to search and analyze secondary and 3D structures. Another method, RNAlyzer, offers new way to analyze and visualize quality of RNA 3D models. Scope and limitations of RNAComposer in application for an automated prediction of riboswitches' 3D structure will be presented and discussed. Analysis of the cyclic di-GMP-II riboswitch from Clostridium acetobutylicum (PDB ID 3Q3Z) as an example allows for 3D structure prediction of related riboswitches from Clostridium difficile 4, Bacillus halodurans 1, and Thermus aquaticus Y5.1 of yet unknown structures.
