Abstract. Standard Raman spectroscopy (SRS) is a noninvasive technique that is used in the biomedical field to discriminate between normal and cancer cells. However, the presence of a strong fluorescence background detracts from the use of SRS in real-time clinical applications. Recently, we have reported a novel modulated Raman spectroscopy (MRS) technique to extract the Raman spectra from the background. In this paper, we present the first application of MRS to the identification of human urothelial cells (SV-HUC-1) and bladder cancer cells (MGH) in urine samples. These results are compared to those obtained by SRS. Classification using the principal component analysis clearly shows that MRS allows discrimination between Raman spectra of SV-HUC-1 and MGH cells with high sensitivity (98%) and specificity (95%). MRS is also used to distinguish between SV-HUC-1 and MGH cells after exposure to urine for up to 6 h. We observe a marked change in the MRS of SV-HUC-1 and MGH cells with time in urine, indicating that the conditions of sample collection will be important for the application of this methodology to clinical urine samples. C 2011 Society of Photo-Optical Instrumentation Engineers (SPIE).

An accurate prognostic model is extremely important in severe traumatic brain injury (TBI) for both patient management and research. Clinical prediction models must be validated both internally and externally before they are considered widely applicable. Our aim is to independently externally validate two prediction models, one developed by the Corticosteroid Randomization After Significant Head injury (CRASH) trial investigators, and the other from the International Mission for Prognosis and Analysis of Clinical Trials in Traumatic Brain Injury (IMPACT) group. We used a cohort of 300 patients with severe TBI (Glasgow Coma Score [GCS] ≤8) consecutively admitted to the National Neuroscience Institute (NNI), Singapore, between February 2006 and December 2009. The CRASH models (base and CT) predict 14 day mortality and 6 month unfavorable outcome. The IMPACT models (core, extended, and laboratory) estimate 6 month mortality and unfavorable outcome. Validation was based on measures of discrimination and calibration. Discrimination was assessed using the area under the receiving operating characteristic curve (AUC), and calibration was assessed using the Hosmer-Lemeshow (H-L) goodness-of-fit test and Cox calibration regression analysis. In the NNI database, the overall observed 14 day mortality was 47.7%, and the observed 6 month unfavorable outcome was 71.0%. The CRASH base model and all three IMPACT models gave an underestimate of the observed values in our cohort when used to predict outcome. Using the CRASH CT model, the predicted 14 day mortality of 46.6% approximated the observed outcome, whereas the predicted 6 month unfavorable outcome was an overestimate at 74.8%. Overall, both the CRASH and IMPACT models showed good discrimination, with AUCs ranging from 0.80 to 0.89, and good overall calibration. We conclude that both the CRASH and IMPACT models satisfactorily predicted outcome in our patients with severe TBI.

Left atrial strain adds independent and incremental predictive value to current risk-prediction models for AF following cryptogenic CVA. Further studies should examine the implications of these findings for AF monitoring or empiric anticoagulation.

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Docetaxel chemotherapy in hormone-naïve mPC has significant toxicities, but has a similar effect on time to progression and overall survival as seen in randomised trials. Chemotherapy should be started at ≥3 weeks after ADT.