Enhancing electrochemical detection through machine learning-driven prediction for canine mammary tumor biomarker with green silver nanoparticles.

This study developed an innovative biosensor strategy for the sensitive and selective detection of canine mammary tumor biomarkers, cancer antigen 15-3 (CA 15-3) and mucin 1 (MUC-1), integrating green silver nanoparticles (GAgNPs) with machine learning (ML) algorithms to achieve high diagnostic accuracy and potential for noninvasive early detection. The GAgNPs-enhanced electrochemical biosensor demonstrated selective detection of CA 15-3 in serum and MUC-1 in tissue homogenates, with limits of detection (LODs) of 0.07 and 0.

Amounts of tissue magnesium and some trace elements in cats with mammary tumors related to various clinicopathological parameters.

Background: Mammary tumors are one of the major malignancies seen in cats. Researchers have indicated the similarity between the epidemiological and clinicopathological patterns of feline mammary tumors and human breast cancer (HBC). In recent years, the investigation of trace elements in cancer tissues becomes prevalent in HBC due to the role of these elements in biochemical and physiological processes.

The response of the canine mammary simple carcinoma and carcinosarcoma cells to 5-aminolaevulinic acid-based photodynamic therapy: An in vitro study.

Backgrounds: Canine mammary gland tumors (CMGTs) are heterogeneous tumors and share many similar features with human breast cancer. Despite the improvement of current treatment options, new treatment modalities are required to effectively kill tumor cells without general toxicity in the treatment of CMGTs. Photodynamic therapy (PDT) is a promising method for cancer treatment.