Diagnosing clean margins through Raman spectroscopy in human and animal mammary tumour surgery: a short review.

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.

Effects of crevice size on the establishment of macroalgae in subtropical streams.

Considering that in previous studies, the surface roughness (micrometric dimension) showed a weak effect on the colonization of stream macroalgae, we investigated the effects of different crevice sizes (milimetric dimension, a scale slightly higher than previous investigations) on the macroalgal abundance in three streams exposed to full sunlight in southern Brazil. We used smooth sterile glass plates with different shapes: P - plane surface without crevices; S - sinuous surface (depth of crevices with 0.159 mm ± 0.03); N - non-unifom surface (0.498 mm ± 0.09); C - surfaces with convex structures (1.190 mm ± 0.12); and three additional surface types with different patterns of heterogeneity with combinations of glass pieces: P + S (H1); P + S + N (H2) and P + S + N + C (H3). The plates were placed into the streams and after 105 days the percent cover of macroalgal community was measured. No significant differences among treatments were recorded. However, we observed a trend of macroalgae occurs within the crevices in all treatments and this suggests that, for stream macroalgae, the crevice sizes used in this study was still not enough to provide an expressive algal growth, even in the treatment with bigger crevices.

A new method to quantify macroalgae and a practical sampler for experimentation in lotic habitats.

Experimental studies in rivers and streams are extremely difficult to run due to the fact that the conditions of these environments are very complex and provide a high level of heterogeneity, which hinders the precise control and standardization of variables. In this study, we present a practical sampler that was designed to make it easier to conduct research projects involving benthic communities of lotic environments, as well as a new nondestructive technique for quantification of the macroalgal communities typically found in these habitats. The sampler consists of an acrylic square tube in which water flows normally inside. This structure carries a removable glass plaque with a known area and can simulate various ecological situations by changing both biotic and abiotic conditions. Thus, it can mitigate the differences between environmental characteristics where each sampler is exposed. The new technique involves capturing digital images that can monitor a unique macroalgal community in development throughout time and a more precise quantification when compared with other techniques that are widely applied. The sampler is easy to build and the images simple to quantify, allowing the detection of spatial and temporal variations in richness and abundance of investigated communities.