High‐field asymmetric waveform ion mobility spectrometry (FAIMS) coupled with high‐resolution electron transfer dissociation mass spectrometry for the analysis of isobaric phosphopeptides

We have applied high‐field asymmetric waveform ion mobility spectrometry (FAIMS) to the analysis of the phosphopeptides APLpSFRGSLPKSYVK, APLSFRGpSLPKSYVK, and APLSFRGSLPKpSYVK. The peptides have identical amino acid sequences and differ only in the site of phosphorylation. The results show that FAIMS is capable of at least partially separating these species. Separation was confirmed by coupling FAIMS with high‐resolution electron transfer dissociation (ETD) mass spectrometry. Phosphorylation is retained on the ETD peptide fragments thereby allowing assignment of the site of the modification. Co‐eluting phosphopeptides which differ only in the site of modification are frequently observed in liquid chromatography/tandem mass spectrometry phosphoproteomics experiments, and therefore these proof‐of‐principle results have implications for the application of FAIMS in that field. Copyright © 2009 John Wiley & Sons, Ltd.     

Automated Spleen Injury Detection Using 3D Active Contours and Machine Learning

The spleen is one of the most frequently injured organs in blunt abdominal trauma. Computed tomography (CT) is the imaging modality of choice to assess patients with blunt spleen trauma, which may include lacerations, subcapsular or parenchymal hematomas, active hemorrhage, and vascular injuries. While computer-assisted diagnosis systems exist for other conditions assessed using CT scans, the current method to detect spleen injuries involves the manual review of scans by radiologists, which is a time-consuming and repetitive process. In this study, we propose an automated spleen injury detection method using machine learning. CT scans from patients experiencing traumatic injuries were collected from Michigan Medicine and the Crash Injury Research Engineering Network (CIREN) dataset. Ninety-nine scans of healthy and lacerated spleens were split into disjoint training and test sets, with random forest (RF), naive Bayes, SVM, k-nearest neighbors (k-NN) ensemble, and subspace discriminant ensemble models trained via 5-fold cross validation. Of these models, random forest performed the best, achieving an Area Under the receiver operating characteristic Curve (AUC) of 0.91 and an F1 score of 0.80 on the test set. These results suggest that an automated, quantitative assessment of traumatic spleen injury has the potential to enable faster triage and improve patient outcomes.     

Importance of palladium-carbon bond energies in direct arylation of polyfluorinated benzenes

Fagnou et al. reported direct arylation reactions that use palladium catalysts to couple Ar(1)-X to Ar(2)-H with the aid of a coordinated base. These reactions are particularly favourable for polyfluorinated arenes Ar(2)-H (see S. I. Gorelsky, D. Lapointe and K. Fagnou, J. Am. Chem. Soc. 2008, 130, 10848). In this paper, we show by means of a DFT analysis how the energetics and activation energies vary with fluorine substitution and examine the structures of intermediates and transition states. The reactant is modelled by Pd(OAc)(Ph)(PMe(3))(DMA) (DMA = dimethylacetamide). The sequence consists of (a) replacement of DMA by arene, (b) Concerted Deprotonation Metallation (CMD), (c) decoordination of AcOH, (d) reductive elimination of biaryl. Many of the variations are dominated by the number of fluorine substituents ortho to the C-H bond and fall into three groups labelled accordingly: Set0Fo, Set1Fo, and Set2Fo. In the first step a coordinated solvent is replaced by the arene. The arenes of Set0Fo and Set1Fo coordinate in a conventional η(2)-CH=CH mode, whereas the arenes of Set2Fo coordinate in an η(1)-CH mode assisted by an OH-C hydrogen bond from the coordinated acetate. Both the energy barriers to CMD and the product energies fall into the three typical sets with the highest barrier and highest product energy being for Set0Fo. They correlate more satisfactorily with the variations in Pd-C bond energies than with the C-H acidities. The barriers to reductive elimination from Pd(Ph)(Ar(F))(PMe(3))(AcOH) increase systematically from Set0Fo to Set2Fo as the Pd-C bond becomes stronger in a regular fashion from Set0Fo to Set2Fo. Again there is a strong correlation between the energy barriers to reductive elimination and the Pd-C bond energies. It is found overall that the key aspects of the reactions are: (a) the lowering of the energy of the CMD step by the ortho fluorine substituents, (b) the regioselective activation of C-H bonds ortho to fluorine which is also determined at the CMD step, (c) the decoordination of AcOH, which maintains the transition state for reductive elimination at low Gibbs free energy. The presence of fluorine increases the effectiveness of the reaction in the sense of points a and b via the increasing strength of the palladium-carbon bond.     

Catalytic mechanism of Golgi-resident human tyrosylprotein sulfotransferase-2: A mass spectrometry approach

Human tyrosylprotein sulfotransferases catalyze the transfer of a sulfuryl moiety from the universal sulfate donor PAPS to the hydroxyl substituent of tyrosine residues in proteins and peptides to yield tyrosine sulfated products and PAP. Tyrosine sulfation occurs in the trans-Golgi network, affecting an estimated 1% of the tyrosine residues in all secreted and membrane-bound proteins in higher order eukaryotes. In this study, an effective LC-MS-based TPST kinetics assay was developed and utilized to measure the kinetic properties of human TPST-2 and investigate its catalytic mechanism when G protein-coupled CC-chemokine receptor 8 (CCR8) peptides were used as acceptor substrates. Through initial rate kinetics, product inhibition studies, and radioactive-labeling experiments, our data strongly suggest a two-site ping-pong model for TPST-2 action. In this mechanistic model, the enzyme allows independent binding of substrates to two distinct sites, and involves the formation of a sulfated enzyme covalent intermediate. Some insights on the important amino acid residues at the catalytic site of TPST-2 and its covalent intermediate are also presented. To our knowledge, this is the first detailed study of the reaction kinetics and mechanism reported for human TPST-2 or any other Golgi-resident sulfotransferase.     

CE‐ESI‐TOF/MS for human growth hormone analysis

CE is a powerful analytical tool used to separate intact biomolecules such as proteins. The coupling of CE with TOF/MS produces a very promising method that can be used to detect and identify proteins in different matrices. This paper describes an efficient, rapid, and simple CE‐ESI‐TOF/MS procedure for the analysis of endogenous human growth hormone and recombinant human growth hormone without sample preparation. Operational factors were optimized using an experimental design, and the method was successfully applied to distinguish human growth hormone and recombinant human growth hormone in unknown samples.     

Structural study of acetogenins by tandem mass spectrometry under high and low collision energy

Collision‐induced dissociation experiments of seven annonaceous acetogenins were carried out under high and low collision energy conditions. Each compound was studied as protonated or deprotonated and lithium‐ or sodium‐ cationized molecules, using ElectroSpray Ionisation (ESI) with a hybrid linear trap/orbitrap mass spectrometer (LTQ‐Orbitrap®). The same ion species were studied with a Matrix‐Assisted Laser Desorption Ionisation (MALDI) tandem mass spectrometer in a high collision energy regime (1 or 2 keV). Although each of the techniques showed some limitations in the detection of functional groups, unambiguous structural identification of the acetogenins was obtained. MALDI ToF‐ToF has the advantage over ESI‐based methods to provide mass spectra rich in informative fragments which allows the confirmation of some functional groups position. By contrast, ESI‐LTQ‐Orbitrap® analysis has the advantage over MALDI that the mass spectra are relatively simple with only fragments close to the functional groups. However, this technique needs to carry out experiments both in negative and positive ionization modes. Copyright © 2010 John Wiley & Sons, Ltd.     

A Physical Organic Approach towards Statistical Modeling of Tetrazole and Azide Decomposition**

Nitrogen atom-rich heterocycles and organic azides have found extensive use in many sectors of modern chemistry from drug discovery to energetic materials. The prediction and understanding of their energetic properties are thus key to the safe and effective application of these compounds. In this work, we disclose the use of multivariate linear regression modeling for the prediction of the decomposition temperature and impact sensitivity of structurally diverse tetrazoles and organic azides. We report a data-driven approach for property prediction featuring a collection of quantum mechanical parameters and computational workflows. The statistical models reported herein carry predictive accuracy as well as chemical interpretability. Model validation was successfully accomplished via tetrazole test sets with parameters generated exclusively in silico. Mechanistic analysis of the statistical models indicated distinct divergent pathways of thermal and impact-initiated decomposition.     

ParNes: a rapidly convergent algorithm for accurate recovery of sparse and approximately sparse signals

In this article, we propose an algorithm, nesta-lasso, for the lasso problem, i.e., an underdetermined linear least-squares problem with a 1-norm constraint on the solution. We prove under the assumption of the restricted isometry property (rip) and a sparsity condition on the solution, that nesta-lasso is guaranteed to be almost always locally linearly convergent. As in the case of the algorithm nesta, proposed by Becker, Bobin, and Candès, we rely on Nesterov’s accelerated proximal gradient method, which takes $O(\sqrt {1/\varepsilon })$ iterations to come within $\varepsilon > 0$ of the optimal value. We introduce a modification to Nesterov’s method that regularly updates the prox-center in a provably optimal manner. The aforementioned linear convergence is in part due to this modification. In the second part of this article, we attempt to solve the basis pursuit denoising (bpdn) problem (i.e., approximating the minimum 1-norm solution to an underdetermined least squares problem) by using nesta-lasso in conjunction with the Pareto root-finding method employed by van den Berg and Friedlander in their spgl1 solver. The resulting algorithm is called parnes. We provide numerical evidence to show that it is comparable to currently available solvers.