We have now constructed different plasmids to demonstrate that this tag is also efficient in increasing expression of fluorescent proteins in different Grampositive bacteria, such as Lactococcus lactis, Bacillus subtilis and Staphylococcus aureus. In order to understand how the efficiency of protein translation is improved, we have determined the molecular requirements of the sequence encoding the itag that ensure the expression of the fluorescent proteins. We have identified additional 10 amino acid tags, derived from different pneumococcal proteins, which could also increase expression of fluorescent proteins by decreasing of the stability of the structure of 59 end of the transcribed mRNA molecule.Our results were consistent with Rodrigues’s prospective study enrolling 1050 patients with AMI. They compared incidence and mortality of AKI after AMI between KDIGO and RIFLE criteria and found that KDIGO criteria detected substantially more AKI patients than RIFLE. Patients diagnosed as AKI by KDIGO but not RIFLE criteria had a significantly higher early and late mortality. The author suggested KDIGO criteria were more suitable for AKI diagnosis in AMI patients than RIFLE.

This implies a detailed knowledge not only of the function of proteins required for the infection process, but also of their localization and role in complex molecular machineries. The availability of genetic and cell biology tools that allow controlled expression of proteins of interest, as well as the study of their localization, is therefore particularly important for the study of bacterial pathogens. We have recently described tools that can contribute to the study of the pneumococcal biology by ensuring the expression of fusions of S. pneumoniae proteins to different fluorescent proteins, namely mCherry, Citrine, CFP and GFP. This was achieved through the introduction of an upstream tag, named “itag”, which increased the efficiency of protein translation.

Using 3 criteria to compare their ICI 182780 prognostic power, studies on cardiac surgery-related to AKI got the same results. However, Roy et al’s results demonstrate that the RIFLE and KDIGO classification systems have only marginally superior prognostic ability when compared to WRF and AKIN to predict the composite outcomes. One potential explanations for this discrepancy maybe they present no analysis of those additional diagnosed cased by KDIGO criteria. Altogether, there is little evidence assessing and comparing the three criteria so far. Similar to other studies, our study found those missed diagnosed AKI patients who died during hospitalization were mostly in Stage 1, demonstrating even slight changes in SCr would have impact on prognosis in CRS type 1 patients.