Breast cancer frequency in human and other mammal female populations has worryingly increased lately. The acute necessity for taxonomy of the aetiological factors along with seeking for new diagnostic tools and therapy procedures aimed at reducing mortality have yielded in an intense research effort worldwide. Surgery is a regular method to counteract extensive development of breast cancer and prevent metastases provided that negative surgical margins are achieved. This highly technical challenge requires fast, extremely sensitive and selective discrimination between malignant and benign tissues even down to molecular level. The particular advantages of Raman spectroscopy, such as high chemical specificity, and the ability to measure raw samples and optical responses in the visible or near-infrared spectral range, have recently recommended it as a means with elevated potential in precise diagnostic in oncology surgery. This review spans mainly the latter 10 years of exceptional efforts of scientists implementing Raman spectroscopy as a nearly real-time diagnostic tool for clean margins assessment in mastectomy and lumpectomy. Although greatly contributing to medical discoveries for the wealth of humanity, animals as patients have benefitted less from advances in surgery diagnostic using Raman spectroscopy. This work also dedicates a few lines to applications of surface enhanced Raman spectroscopy in veterinary oncological surgery.

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In this work, we study the sensing properties of multi-layer graphene combined with pyrrole in order to elaborate low-cost, high-sensitive material for cortisol detection. Graphene nanoplatelets and pyrrole were dispersed in a solution containing 1M HNO3 by using a powerful ultrasound probe for 10 min, then centrifuged for 30 min at 4000 rpm; polymerization was performed by cyclic voltammetry. The graphene–pyrrole composite was tested to ultra-low levels of cortisol in artificial saliva, consistent to the levels excreted in human salivary samples. The composite was further investigated by Raman spectroscopy and we modeled the interaction between the sensitive layer and cortisol using MarvinBeans software. It shows a good sensitivity for salivary values of cortisol cyclic voltammetry being able to detect a level down to 0.5 ng/mL cortisol.

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