Window entrapment trauma in cats: clinical, neurological and clinicopathological findings and outcome (70 cases).

Objectives: Window entrapment in cats can lead to reduced blood flow to the spinal cord, muscles and nerves, resulting in ischaemic neuromyelomyopathy. The severity and duration of entrapment greatly influence clinical and neurological outcomes, as well as prognosis. The aim of the present retrospective multicentric study (2005-2022) was to describe clinical, neurological and selected clinicopathological findings, as well as the outcome of cats trapped in bottom-hung windows, presented to both first-opinion and referral-only clinics.

The use of scenario tree models in support of animal health surveillance: A scoping review.

Background: Scenario tree modelling is a well-known method used to evaluate the confidence of freedom from infection or to assess the sensitivity of a surveillance system in detecting an infection at a certain design prevalence. It facilitates the use of data from various sources and the inclusion of risk factors into calculations, while still obtaining quantitative estimates of surveillance sensitivity and probability of freedom.

Objectives: We conducted a scoping review to identify scenario tree models (STMs) applied to assess freedom from infection in veterinary medicine, characterize their use, parameterisation, reporting and potential limitations.

Artificial Intelligence to Predict the BRAF V595E Mutation in Canine Urinary Bladder Urothelial Carcinomas.

In dogs, the mutation (V595E) is common in bladder and prostate cancer and represents a specific diagnostic marker. Recent advantages in artificial intelligence (AI) offer new opportunities in the field of tumour marker detection. While AI histology studies have been conducted in humans to detect mutation in cancer, comparable studies in animals are lacking.