Massive transfusion: an evidence-based review of recent developments.

The design and implementation of massive transfusion protocols with ratio-based transfusion of blood and blood products are important and active areas of investigation. A significant yet controversial body of literature exists to support the use of hemostatic resuscitation in massive transfusion and new data to support the use of adjuncts, such as recombinant factor VIIa and tranexamic acid. We review the developments in massive transfusion research during the past 5 years, including protocol implementation, hemostatic resuscitation, the use of tranexamic acid, and goal-directed therapy for coagulopathy. Furthermore, we provide a level of evidence analysis of the data surrounding the use of component therapy and recombinant factor VIIa in massive transfusion, summary recommendations for the various agents of resuscitation, and new methods of goal-directed therapy.

Characterization and diagnostic value of amino acid side chain neutral losses following electron-transfer dissociation.

Using a large set of high mass accuracy and resolution ETD tandem mass spectra, we characterized ETD-induced neutral losses. From these data we deduced the chemical formula for 20 of these losses. Many of them have been previously observed in electron-capture dissociation (ECD) spectra, such as losses of the side chains of arginine, aspartic acid, glutamic acid, glutamine, asparagine, leucine, histidine, and carbamidomethylated cysteine residues. With this information, we examined the diagnostic value of these amino acid-specific losses. Among 1285 peptide-spectrum matches, 92.5% have agreement between neutral loss-derived peptide amino acid composition and the peptide sequences. Moreover, we show that peptides can be uniquely identified by using only the accurate precursor mass and amino acid composition based on neutral losses; the median number of sequence candidates from an accurate mass query is reduced from 21 to 8 by adding side chain loss information. Besides increasing confidence in peptide identification, our findings suggest the potential use of these diagnostic losses in ETD spectra to improve false discovery rate estimation and to enhance the performance of scoring functions in database search algorithms.