Improved automated spot counting and modeling with bias correction.

A complete workflow was presented for estimating the concentration of microorganisms in biological samples by automatically counting spots that represent viral plaque forming units (PFU) bacterial colony forming units (CFU), or spot forming units (SFU) in images, and modeling the counts. The workflow was designed for processing images from dilution series but can also be applied to stand-alone images. The accuracy of the methods was greatly improved by adding a newly developed bias correction method.

US Initiative to Eliminate Racial and Ethnic Disparities in Health: The Impact on the Outcomes of ST-Segment-Elevation Myocardial Infarction in New Jersey.

Background In 1998, President Clinton launched a federal initiative to eliminate racial and ethnic health disparities. The impact on the outcomes of ST-segment-elevation myocardial infarction has not been well studied. Methods and Results ST-segment-elevation myocardial infarction outcomes from 1994 to 2015 were studied in 7942 Black, 27 665 Hispanic, and 88 727 White patients with first admission of ST-segment-elevation myocardial infarction using the Myocardial Infarction Data Acquisition System.