Histopathology remains the cornerstone for diagnosing canine mammary tumors (CMTs). Recently, 2 classification systems (the World Health Organization [WHO] classification of 1999 and the proposal of 2011) and 2 grading methods based on the human Nottingham grade have been used by pathologists. Despite some evidence that the histological subtype and grade are prognostic factors, there is no comprehensive comparative study of these classification and grading systems in the same series of CMTs. In this study, the 2 classifications and the 2 grading methods were simultaneously applied to a cohort of 134 female dogs with CMTs. In 85 animals with malignant tumors, univariable and multivariable survival analyses were performed. Using the 2 systems, the proportion of benign (161/305, 53%) and malignant (144/305, 47%) tumors was similar and no significant differences existed in categorization of benign tumors. However, the 2011 classification subdivided malignant tumors in more categories—namely, those classified as complex, solid, and tubulopapillary carcinomas by the WHO system. Histological subtype according to both systems was significantly associated with survival. Carcinomas arising in benign tumors, complex carcinomas, and mixed carcinomas were associated with a better prognosis. In contrast, carcinosarcomas and comedocarcinomas had a high risk of tumor-related death. Slight differences existed between the 2 grading methods, and grade was related to survival only in univariable analysis. In this cohort, age, completeness of surgical margins, and 2 index formulas adapted from human breast cancer studies (including tumor size, grade, and vascular/lymph node invasion) were independent prognostic factors.

Kidney ailments, as chronic kidney disease, kidney stones and polycystic kidney disease, recognized as a comorbidity of diabetes and hypertension, are strongly linked to higher risk of cardiovascular diseases, infection and cancer. Therefore, they are considered a global public health problem, contributing to the global major burden of noncommunicable diseases, and having a direct impact on high global mortality and morbidity. [1,2] It is estimated that the prevalence and associated burden of kidney disease is responsible for 5-10 million deaths per year worldwide. [2] The quantification of biomarkers present in various body fluids represents a versatile tool for diagnosis, prognosis, monitoring, therapy and disease management. [3] Currently, the most common body fluids used for biomarkers detection are blood, urine and saliva. [3] However, interstitial skin fluid (ISF), which is formed by blood transcapillary filtration is gaining increasing relevance in this realm. [4] Surrounding the capillary beds in the connective tissue, the ISF contains systemic biomarkers and its composition varies along Urea, the main nitrogenous waste product of protein metabolism, is eliminated almost exclusively by the kidney, and hence, displays considerable clinical significance in the assessment of kidney disorders. The aim of this study is to prepare and investigate the potential of swellable cross-linked gelatin methacryloyl (c-GelMA) microneedles (MNs) as a platform for minimally invasive extraction of interstitial skin fluid (ISF) toward straightforward point-of-care healthcare monitoring of renal complaints, by quantification of urea. c-GelMA MNs are successfully prepared by photo-cross-linking and micromolding, faithfully replicating the master molds (387 ± 16 µm height, 200 µm base and 500 µm tip-to-tip distance). These MN patches display good mechanical properties, withstanding more than 0.15 N per needle without breaking. Ex vivo skin insertion assays reveal that the MNs penetrate up to 237 µm depth, reaching the dermis, where they should extract ISF considering a real application. In an in vitro application using an agarose skin model system, the c-GelMA MNs are able to efficiently recover urea (>98%). Additionally, these MNs exhibit noncytotoxic effects toward human keratinocytes. These findings suggest that c-GelMA MNs are promising devices for sampling ISF and offline analysis of urea, opening new avenues for simple point-of-care healthcare monitoring.

No abstract

No abstract

No abstract