Наша группа организует более 3000 глобальных конференций Ежегодные мероприятия в США, Европе и США. Азия при поддержке еще 1000 научных обществ и публикует более 700 Открытого доступа Журналы, в которых представлены более 50 000 выдающихся деятелей, авторитетных учёных, входящих в редколлегии.
Журналы открытого доступа набирают больше читателей и цитируемости
700 журналов и 15 000 000 читателей Каждый журнал получает более 25 000 читателей
Landulfo Silveira
Raman scattering has been employed for a while to examine the chemical makeup of biological systems. In the past ten years, Raman scattering has been extensively used in cancer screening, diagnosis, and intraoperative surgical guidance because to its high chemical specificity and noninvasive detection capacity. Coherent Raman scattering and surface-enhanced Raman scattering have lately been used in the study of cancer to overcome the weak signal of spontaneous Raman scattering. This study focuses on cutting-edge research on Raman scattering’s use to cancer diagnostics and its potential to go from the bench to the bedside. Clinical oncology still faces many obstacles when it comes to early cancer detection. Skin lesion detection has recently been done using Raman spectroscopy. The use of FT-Raman spectroscopy, a contemporary analytical method, for cancer diagnosis will benefit the patient in a number of ways, including real-time and less intrusive diagnosis. The main goal of this research was to identify spectral differences between benign and malignant (basal cell carcinoma - BCC) skin tissues using FT-Raman spectroscopy. These spectrum shifts can reveal crucial details about the metabolic changes that occur in these two different types of tissues. We compared eight sets of samples histopathologically identified as BCC with five sets of samples identified as benign tissue by FT-Raman analysis. We discovered that the shift regions between 1220 and 1300 cm-1 and between 1640 and 1680 cm-1 were where these samples’ primary spectrum differences were. The amide III and amide I vibrations, respectively, are represented by the vibration bands in these locations. With 100% sensitivity and specificity, principal component analysis performed on all 13 samples could determine the type of tissue.