Rotaviruses are highly infectious and typically transmitted by fecal-oral route via in the tropics and leading the cause of diarrheal deaths in children of developing countries, besides causing significant economic impacts like neonatal disease agents of domestic animals. This present report aims to present the clinical and diagnostic findings of two confirmed cases of rotavirus (RV) infection in orphaned Leopardus tigrinus (Schreber, 1775) and Leopardus pardalis (Linnaeus, 1758), the first register of the infection by group A rotavirus in these species. Both felids were rescued in the Pará State Amazon Brazil by the IBAMA (the Brazilian Institute of Environment and Renewable Natural Resources), and treated by veterinarians into intensive care ward in a public Environmental Park of Belém city. After the adaptation period to the quarantine, these animals showed non-specific symptoms of acute fulminant gastroenteritis. Rotavirus group A antigen was identified in blood and faecal samples of L. tigrinus analyzed by immunochromatography (ICG) and immunoassay methods (ELISA) at the Virology Laboratory of the Institute Evandro Chagas. The animals died within few days during the clinical exacerbation unresponsive to current treatment, its necropsies and histopathological analysis were performed in the Laboratory of Veterinary Pathology of the Federal Rural University of Amazonia (UFRA). Despite the compatible pathologic findings of rotavirus infection in both animals, the atypical hemorrhagic character was a curious finding, considering the presumed etiology.

Predatory research field in science is when an emerging scientific topic destroys current topics and characterizes a main scientific change. Predatory research field can be a basic driver of scientific and technological change that generates a 'creative destruction' in science and society in contexts of knowledge-based competition and rapid changes. The prediction of proposed theory of predatory research fields is that it destroys with a fast growth other research fields. The theoretical approach is tested here in research fields of large language models (LLM) by analyzing the transformers (a deep learning architecture based on the multi-head attention mechanism) proposed in 2017 and from November 2022 started main applications in generative artificial intelligence with innovations of BERT, ChatGPT, Microsoft Copilot (launched on February 7, 2023) and other natural language processing tools driven by AI technology for engaging conversations, gain insights, automate tasks, etc., etc. Statistical evidence suggests that growth rate of transformer technologies is 80.58%, a high level compared to all other research fields in machine learning (having a growth rate of 13.83%). Moreover, predatory research field of transformers has a destructive power such that all other domains in LLM from 2021 to 2023 have a general reduction of scientific growth. The impact of transformers is much more drastic of previous radical technologies such as CNN having a temporal growth rate of 0.16%, lower than 0.38% by transformers, ceteris paribus. These analysis reveals that transformers have characteristics to generate a radical scientific and technological change in a not-too-distant future. Overall, then, the study suggests that predatory research field on emerging topics and technologies can generate path-breaking innovations and the examination here can clarify the essential elements of the science dynamics for a better theory of scientific and technological change, providing also main implications for knowledge policy to support promising research fields and technologies to guide economic and social change.