Gross and Microscopic Morphological Anatomical Study of the Guinea Pig (Cavia porcellus) and the Capybara (Hydrochoerus hydrochaeris), Aimed at the Preparation of a Comparative Anatomical Atlas of the Different Systems

In recent years, there has been an exponential increase in the so-called “new pets”, including the domestic guinea pig (Cavia porcellus) and the capybara (Hydrochoerus hydrochaeris), two closely related Caviid rodents native to South America. Both historically bred for food purposes, they have more recently become increasingly popular as pets in the European and American continents, respectively. This led to an increasing veterinary interest in deepening the knowledge regarding their normal anatomy, as a basic contribution to other fields of veterinary medicine, including diagnostic imaging, surgery, and pathological anatomy. Being part of a bilateral framework co-tutelage agreement leading to a joint Doctoral Degree between the Alma Mater Studiorum of Bologna, Italy and the Universidad Nacional del Litoral of Santa Fe, Argentina, this research project was partly carried out in Italy (study of guinea pigs) and partly in Argentina (study of capybaras). It consisted in the macroscopic study, through anatomical dissections of carcasses of both species as well as the use of anatomical casts, and in the histological study of the various systems in the two species, and was aimed at creating a gross and microscopic comparative anatomical atlas. From the gross and microscopic morphological and morphometrical anatomical study of the different system of the guinea pig and capybara, several analogies and differences emerged. The creation of a comparative anatomical atlas of gross and microscopic anatomy of the capybara and the guinea pig might prove useful for clinical, zootechnical and research purposes.

Anatomical biomarkers of body composition in oncological population: application and development of artificial intelligences

In the Era of precision medicine and big medical data sharing, it is necessary to solve the work-flow of digital radiological big data in a productive and effective way. In particular, nowadays, it is possible to extract information “hidden” in digital images, in order to create diagnostic algorithms helping clinicians to set up more personalized therapies, which are in particular targets of modern oncological medicine. Digital images generated by the patient have a “texture” structure that is not visible but encrypted; it is “hidden” because it cannot be recognized by sight alone. Thanks to artificial intelligence, pre- and post-processing software and generation of mathematical calculation algorithms, we could perform a classification based on non-visible data contained in radiological images. Being able to calculate the volume of tissue body composition could lead to creating clasterized classes of patients inserted in standard morphological reference tables, based on human anatomy distinguished by gender and age, and maybe in future also by race. Furthermore, the branch of “morpho-radiology" is a useful modality to solve problems regarding personalized therapies, which is particularly needed in the oncological field. Actually oncological therapies are no longer based on generic drugs but on target personalized therapy. The lack of gender and age therapies table could be filled thanks to morpho-radiology data analysis application.