Recipients of MBL-deficient livers have almost a 3-fold greater likelihood of developing CSI and may benefit from MBL replacement.
BackgroundWith the introduction of the first high-throughput qPCR instrument on the market it became possible to perform thousands of reactions in a single run compared to the previous hundreds. In the high-throughput reaction, only limited volumes of highly concentrated cDNA or DNA samples can be added. This necessity can be solved by pre-amplification, which became a part of the high-throughput experimental workflow. Here, we focused our attention on the limits of the specific target pre-amplification reaction and propose the optimal, general setup for gene expression experiment using BioMark instrument (Fluidigm).ResultsFor evaluating different pre-amplification factors following conditions were combined: four human blood samples from healthy donors and five transcripts having high to low expression levels; each cDNA sample was pre-amplified at four cycles (15, 18, 21, and 24) and five concentrations (equivalent to 0.078 ng, 0.32 ng, 1.25 ng, 5 ng, and 20 ng of total RNA). Factors identified as critical for a success of cDNA pre-amplification were cycle of pre-amplification, total RNA concentration, and type of gene. The selected pre-amplification reactions were further tested for optimal Cq distribution in a BioMark Array. The following concentrations combined with pre-amplification cycles were optimal for good quality samples: 20 ng of total RNA with 15 cycles of pre-amplification, 20x and 40x diluted; and 5 ng and 20 ng of total RNA with 18 cycles of pre-amplification, both 20x and 40x diluted.ConclusionsWe set up upper limits for the bulk gene expression experiment using gene expression Dynamic Array and provided an easy-to-obtain tool for measuring of pre-amplification success. We also showed that variability of the pre-amplification, introduced into the experimental workflow of reverse transcription-qPCR, is lower than variability caused by the reverse transcription step.Electronic supplementary materialThe online version of this article (doi:10.1186/s12867-015-0033-9) contains supplementary material, which is available to authorized users.
Background: This study evaluated the use of several risk prediction models in estimating short- and long-term mortality following hip fracture in an Australian population. Methods: Data from 195 patients were retrospectively analysed and applied to three models of interest: the Nottingham Hip Fracture Score, the Age-Adjusted Charlson Comorbidity Index and the Physiological and Operative Severity Score for enUmeration of Mortality and Morbidity. The performance of these models was assessed with receiver operating characteristic curve as well as logistic regression modelling. Results: The median age of participants was 83 years and 69% were women. Ten percent of patients were deceased by 30 days, 25% at 6 months and 31% at 12 months post-operatively. While there was no statistically significant difference between the models, the Age-Adjusted Charlson Comorbidity Index had the largest area under the receiver operating characteristic curve for within 30 day and 12 month mortality, while the Nottingham Hip Fracture Score was largest for 6-month mortality. There was no evidence to suggest that the models were selecting a specific subgroup of our population, therefore, no indication was present to suggest that using multiple models would improve mortality prediction. Conclusions: While there was no statistically significant difference in mortality prediction, the Nottingham Hip Fracture Score is perhaps the best suited clinically, due to its ease of implementation. Larger prospective data collection across a variety of sites and its role in guiding clinical management remains an area of interest.
ABSTRACT:CYP2C9 is distinguished by a preference for substrates bearing a negative charge at physiological pH. Previous studies have suggested that CYP2C9 residues R97 and K72 may play roles in determining preference for anionic substrates by interaction at the active site or in the access channel. The aim of the present study was to assess the role of these two residues in determining substrate selectivity. R97 and K72 were substituted with negative, uncharged polar and hydrophobic residues using a degenerate polymerase chain reaction-directed strategy. Wild-type and mutant enzymes were expressed in bicistronic format with human cytochrome P450 reductase in Escherichia coli. Mutation of R97 led to a loss of holoenzyme expression for R97A, R97V, R97L, R97T, and R97E mutants. Low levels of hemoprotein were detected for R97Q, R97K, R97I, and R97P mutants. Significant apoenzyme was observed, suggesting that heme insertion or protein stability was compromised in R97 mutants. These observations are consistent with a structural role for R97 in addition to any role in substrate binding. By contrast, all K72 mutants examined (K72E, K72Q, K72V, and K72L) could be expressed as hemoprotein at levels comparable to wild-type. Type I binding spectra were obtained with wildtype and K72 mutants using diclofenac and ibuprofen. Mutation of K72 had little or no effect on the interaction with these substrates, arguing against a critical role in determining substrate specificity. Thus, neither residue appears to play a role in determining substrate specificity, but a structural role for R97 can be proposed consistent with recently published crystallographic data for CYP2C9 and CYP2C5.The cytochrome P450 (P450 1 ) group of enzymes are the predominant catalysts of phase I xenobiotic metabolism in humans and other mammals, catalyzing a variety of monooxygenation reactions including, among others, aliphatic and aromatic hydroxylation, epoxidation, N-and O-dealkylation, and N-and S-oxidation. In humans, approximately 15 enzymes from the CYP1-3 families are responsible for the metabolic clearance of most lipophilic chemicals. Among this group, forms from the same subfamily show discrete but often overlapping substrate specificities.CYP2C9, one of the most important forms in overall drug metabolism, is distinguished from other human CYP2C forms by a preference for substrates bearing a negative charge at physiological pH (Smith and Jones, 1992;Mancy et al., 1995); however, neutral or positively charged substrates may also be substrates. Various models have been developed to explain the preference for anionic substrates.Mansuy and colleagues originally proposed a pharmacophore model based on examination of tienilic acid derivatives and other CYP2C9 substrates (Mancy et al., 1995). In this model, a positively charged residue bordering the substrate binding site was proposed to interact electrostatically with the negative center on the substrate.Homology modeling of the CYP2C9 protein based on crystal structures available for other P450 enzyme...
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