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Current urinary bladder cancer diagnosis is commonly based on a biopsy obtained during cystoscopy. This invasive method causes discomfort and pain in patients. Recently, taurine and several other compounds such as L-phenylalanine and hippuric acid in urine were found to be indicators of bladder cancer. However, because of a lack of sensitive and accurate analytical techniques, it is impossible to detect these compounds in urine at low levels. In this study, using liquid chromatography-tandem mass spectrometry (LC-MS/MS), a noninvasive method was developed to separate and detect these compounds in urine. (15)N(2)-L-glutamine was used as the internal standard, and creatinine acted as an indicator for urine dilution. A phenyl-hexyl column was used for the separation at an isocratic condition of 0.2% formic acid in water and 0.2% formic acid in methanol. Analytes were detected in multiple-reaction monitoring with positive ionization mode. The limit of detection range is 0.18-6 nM and the limit of quantitation ranges from 0.6 to 17.6 nM. The parameters affecting separation and quantification were also investigated and optimized. Proper clinical validation of these biomarkers can be done using this reliable, fast, and simple method. Furthermore, with simple modifications, this method could be applied to other physiological fluids and other types of diseases.

This detailed study shows that the aforementioned urinary metabolites are not reliable biomarkers for prostate cancer detection or for differentiating the aggressiveness of prostate cancer.

Human urine recently became a popular medium for metabolomics biomarker discovery because its collection is non-invasive. Sometimes renal dilution of urine can be problematic in this type of urinary biomarker analysis. Currently, various normalization techniques such as creatinine ratio, osmolality, specific gravity, dry mass, urine volume, and area under the curve are used to account for the renal dilution. However, these normalization techniques have their own drawbacks. In this project, mass spectrometry-based urinary metabolomic data obtained from prostate cancer (n=56), bladder cancer (n=57) and control (n=69) groups were analyzed using statistical normalization techniques. The normalization techniques investigated in this study are Creatinine Ratio, Log Value, Linear Baseline, Cyclic Loess, Quantile, Probabilistic Quotient, Auto Scaling, Pareto Scaling, and Variance Stabilizing Normalization. The appropriate summary statistics for comparison of normalization techniques were created using variances, coefficients of variation, and boxplots. For each normalization technique, a principal component analysis was performed to identify clusters based on cancer type. In addition, hypothesis tests were conducted to determine if the normalized biomarkers could be used to differentiate between the cancer types. The results indicate that the determination of statistical significance can be dependent upon which normalization method is utilized. Therefore, careful consideration should go into choosing an appropriate normalization technique as no method had universally superior performance.

Laser micromachining has emerged as a promising technique for mass production of microfluidic devices. However, control and optimization of process parameters, and design of substrate materials are still ongoing challenges for the widespread application of laser micromachining. This article reports a systematic study on the effect of laser system parameters and thermo-physical properties of substrate materials on laser micromachining. Three dimensional transient heat conduction equation with a Gaussian laser heat source was solved using finite element based Multiphysics software COMSOL 5.2a. Large heat convection coefficients were used to consider the rapid phase transition of the material during the laser treatment. The depth of the laser cut was measured by removing material at a pre-set temperature. The grid independent analysis was performed for ensuring the accuracy of the model. The results show that laser power and scanning speed have a strong effect on the channel depth, while the level of focus of the laser beam contributes in determining both the depth and width of the channel. Higher thermal conductivity results deeper in cuts, in contrast the higher specific heat produces shallower channels for a given condition. These findings can help in designing and optimizing process parameters for laser micromachining of microfluidic devices.

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