Early detection of disease is essential for alleviating disease burden, increasing success rate and decreasing mortality rate especially for cancer. To improve disease diagnostics, many candidate biomarkers have been suggested using molecular biology or image analysis techniques over the past decade. The receiver operating characteristics (ROC) curve is a standard technique to evaluate a diagnostic accuracy of biomarkers, but it has some limitations especially for heterogeneous diseases. As an alternative of the ROC curve analysis, we suggest a jittered dot plot (JDP) and JDP-based evaluation measures, above mean difference (AMD) and averaged above mean difference (AAMD). We demonstrate how JDP and AMD or AAMD together better evaluate biomarkers than the standard ROC curve. We analyze real and heterogeneous basal-like breast cancer data.
Cancer autoantibody biomarker discovery and validation using nucleic acid programmable protein array
Whistleblowing in Biomedical Research and Medicine: An Analysis of Ethical Expectations and Dilemmas
In order to further compare porcine and human-derived enzymes, a determination of the enzyme effectiveness was done via digestion simulation. The digestion for both the human and porcine-derived enzymes consisted of three steps: oral, gastric, and intestinal. After the digestion, the absorbance for each enzyme class as well as a dilution curve of the formula used was read and recorded. Using the standard dilution curve and the absorbance values for each unknown, the formula and thus enzyme concentration that was lost through the reaction was able to be calculated.
The effectiveness of both the human and porcine enzymes, determined by the percent of formula lost, was 18.2% and 19.7%, respectively, with an error of 0.6% from the spectrophotometer, and an error of about 10% from the scale used for measuring the enzymes. This error was likely due to the small mass required of the enzymes and can be prevented in the future by performing the experiment at a larger scale.