Differentiation of alloreactive versus CD3/CD28 stimulated T-lymphocytes using Raman spectroscopy: a greater specificity for noninvasive acute renal allograft rejection detection.

Acute rejection (AR) remains problematic in renal transplantation. As a marker, serum creatinine is limited, warranting a more effective screening tool. Raman spectroscopy (RS) can detect T-cell activation with high sensitivity. In this study we explore its specificity. Seventy-five inactivated, 40 alloantigen-activated, and 75 CD3/CD28-activated T cells were analyzed using RS. CD3/CD28-activated peak magnitudes (PM) were 4.3% to 23.9% lower than inactivated PM at positions: 903, 1031, 1069, 1093, 1155, 1326, and 1449 cm(-1), with a difference in peak ratio (PR) observed at the 1182:1195 cm(-1) position (0.91 +/- 0.06 vs. 1.2 +/- 0.01, respectively: P = 0.006). Differences in CD3/CD28- and alloantigen-activated PM were observed at: 903, 1031, 1093, 1155, 1326, and 1449 cm(-1), with no PR differences at the 1182:1195 cm(-1) position (0.91 +/- 0.06 vs. 0.86 +/- 0.09: P = 0.8). Spectral signature separation of CD3/CD28-and alloantigen-activated groups was 100% specific and sensitive. We conclude that RS can differentiate T cells activated by different stimuli with high sensitivity and specificity.

Raman spectroscopic differentiation of activated versus non-activated T lymphocytes: an in vitro study of an acute allograft rejection model.

Acute rejection (AR) remains a significant complication in renal transplant patients. Using serum creatinine for AR screening has proven problematic, and thus a noninvasive, highly sensitive and specific test is needed. T cells from human peripheral blood were analyzed using Raman spectroscopy. Fifty-one Mixed Lymphocyte Culture (MLC) activated T cells (ATC), 28 Mitomycin C inactivated T cells (ITC), and 35 resting T cells (RTC), were studied utilizing 785 and 514.5 nm wavelengths. Statistical analysis following subtraction of fluorescence used Student's t test to quantify peak ratio differences and discriminant function analysis (DFA), with three distinct sectors assigned for grouping purposes: Sector I, ITC; Sector II, ATC; Sector III, RTC. Differences between ATC and non-activated T cells (ITC and RTC) were found at 1182 and 1195 cm-1 peak positions for both wavelengths. Significant differences in peak ratios for 785 and 514.5 nm wavelengths existed between ATC and RTC (p=0.001 and p=0.006, respectively) and ATC and ITC (p=0.001 and p=0.001, respectively), with a trend in differences observed between ITC and RTC (p=0.07 and p=0.08, respectively). Analysis of the DFA-derived sector distribution for the 785 and 514.5 nm wavelengths revealed a sensitivity of 95.7% and 89.3%, respectively, and a specificity of 100% and 93.8%, respectively. This data suggests that Raman spectroscopy can detect significant differences between activated and nonactivated T cells based upon cell-surface receptor expression, thereby establishing unique signatures that can aid in the development of a noninvasive AR screening tool with high sensitivity and specificity.

Evaluation of pancreatic cancer with Raman spectroscopy in a mouse model.

OBJECTIVES: Detection of neoplastic changes using optical spectroscopy has been an active area of research in recent times. Raman spectroscopy is a vibrational spectroscopic technique that can be used to diagnose various tumors with high sensitivity and specificity. We evaluated the ability of Raman spectroscopy to differentiate normal pancreatic tissue from malignant tumors in a mouse model. METHODS: We collected 920 spectra, 475 from 31 normal pancreatic tissue and 445 from 29 tumor nodules using a 785-nm near-infrared laser excitation. Discriminant function analysis was used for classification of normal and tumor samples. RESULTS: Using principal component analysis, we were able to highlight subtle chemical differences in normal and malignant tissue. Using histopathology as the gold standard, Raman analysis gave sensitivities between 91% and 96% and specificities between 88% and 96%. CONCLUSIONS: Raman spectroscopy along with discriminant function analysis is a useful method to detect cancerous changes in the pancreas. Pancreatic tumors were characterized by increased collagen content and decreased DNA, RNA, and lipids components compared with normal pancreatic tissue.

Raman spectroscopy can differentiate malignant tumors from normal breast tissue and detect early neoplastic changes in a mouse model.

Raman spectroscopy shows potential in differentiating tumors from normal tissue. We used Raman spectroscopy with near-infrared light excitation to study normal breast tissue and tumors from 11 mice injected with a cancer cell line. Spectra were collected from 17 tumors, 18 samples of adjacent breast tissue and lymph nodes, and 17 tissue samples from the contralateral breast and its adjacent lymph nodes. Discriminant function analysis was used for classification with principal component analysis scores as input data. Tissues were examined by light microscopy following formalin fixation and hematoxylin and eosin staining. Discriminant function analysis and histology agreed on the diagnosis of all contralateral normal, tumor, and mastitis samples, except one tumor which was found to be more similar to normal tissue. Normal tissue adjacent to each tumor was examined as a separate data group called tumor bed. Scattered morphologically suspicious atypical cells not definite for tumor were present in the tumor bed samples. Classification of tumor bed tissue showed that some tumor bed tissues are diagnostically different from normal, tumor, and mastitis tissue. This may reflect malignant molecular alterations prior to morphologic changes, as expected in preneoplastic processes. Raman spectroscopy not only distinguishes tumor from normal breast tissue, but also detects early neoplastic changes prior to definite morphologic alteration.

Where is the shot noise of a quantum point contact?

Reznikov et al. [Phys. Rev. Lett. 75, 3340 (1995)]] have presented definitive observations of nonequilibrium noise in a quantum point contact. Especially puzzling is the "anomalous" peak structure of the excess noise measured at constant current; to date it remains unexplained. We show that their experiment directly reveals the deep link between conservation principles in the electron gas and its low-dimensional, mesoscopic behavior. The keys to that connection are gauge invariance and the compressibility sum rule. These are central not only to the experiment of Reznikov et al., but to the very nature of all mesoscopic transport.