Synthesis of the dopamine D2/D3 receptor agonist (+)-PHNO via supercritical fluid chromatography: preliminary PET imaging study with [3-C]-(+)PHNO

Carbon-11 labeled (+)-4-[1-¹¹C]propyl-3,4,4a,5,6,10b-hexahydro-2H-naphtho[1,2-b][1,4]oxazin-9-ol ([1-¹¹C]-(+)-PHNO) is a dopamine D₃-preferring agonist radiopharmaceutical used for medical imaging by positron emission tomography (PET). We report the synthesis of (+)-PHNO using supercritical fluid chromatography for enantiomeric resolution of its norpropyl derivative, HNO, followed by propylation. (+)-HNO was used to prepare the radiolabeling precursor, (+)-trans-4-acetyl-9-triisopropylsilyloxy-2,3,4a,5,6,10b-hexahydro-4H-naphth[1,2b][1,4]oxazine, in 12 steps. Modifications to the labeling procedure were made to ensure consistent preparation of [3-¹¹C]-(+)-PHNO via [¹¹C]CH₃I. A preliminary PET imaging study was carried out with this tracer in an attempt to image dopamine receptors in brown adipose tissue (brown fat) in vivo.     

Detection of femtomole and sub-femtomole levels of peptides by tandem magnetic sector/reflectron time-of-flight mass spectrometry and matrix-assisted laser desorption ionization

This article describes results of low-level (sub-femtomole) detection of peptides by matrix-assisted laser desorption ionization. The matrix-assisted laser desorption ionization method can be used for low-level detection of the parent ion, either [M + H]⁺ or [M + Na]⁺, and collision-induced dissociation of the parent ion can be performed at the picomole level. The instrument used for these studies is a novel high-performance magnetic sector (electric(E)/magnetic(B) sector)/reflectron time-of-flight (TOP) tandem mass spectrometer (EB/TOF).     

Determination of ion mobility collision cross sections for unresolved isomeric mixtures using tandem mass spectrometry and chemometric deconvolution

Ion mobility (IM) is an important analytical technique for determining ion collision cross section (CCS) values in the gas-phase and gaining insight into molecular structures and conformations. However, limited instrument resolving powers for IM may restrict adequate characterization of conformationally similar ions, such as structural isomers, and reduce the accuracy of IM-based CCS calculations. Recently, we introduced an automated technique for extracting “pure” IM and collision-induced dissociation (CID) mass spectra of IM overlapping species using chemometric deconvolution of post-IM/CID mass spectrometry (MS) data [J. Am. Soc. Mass Spectrom., 2014, 25, 1810–1819]. Here we extend those capabilities to demonstrate how extracted IM profiles can be used to calculate accurate CCS values of peptide isomer ions which are not fully resolved by IM. We show that CCS values obtained from deconvoluted IM spectra match with CCS values measured from the individually analyzed corresponding peptides on uniform field IM instrumentation. We introduce an approach that utilizes experimentally determined IM arrival time (AT) “shift factors” to compensate for ion acceleration variations during post-IM/CID and significantly improve the accuracy of the calculated CCS values. Also, we discuss details of this IM deconvolution approach and compare empirical CCS values from traveling wave (TW)IM-MS and drift tube (DT)IM-MS with theoretically calculated CCS values using the projected superposition approximation (PSA). For example, experimentally measured deconvoluted TWIM-MS mean CCS values for doubly-protonated RYGGFM, RMFGYG, MFRYGG, and FRMYGG peptide isomers were 288.₈ Å², 295.₁ Å², 296.₈ Å², and 300.₁ Å²; all four of these CCS values were within 1.5% of independently measured DTIM-MS values.     

Trajectory-tracking of 6-RSS Stewart-Gough manipulator by feedback-linearization control using a novel inverse dynamic model based on the force distribution algorithm

ABSTRACT

6-RSS Stewart-Gough parallel manipulator contains six crank-rod limbs connecting the base and moving platforms to each other, forming a 6DOF manipulator. In this paper, we introduce a novel decoupled inverse dynamic model for this manipulator based on the Force Distribution Algorithm. The performance of the proposed model was evaluated in tracking a complex trajectory (of multiple segments with simultaneous translational and rotational motions) using feedback-linearization control in the joint space and compared with that of the Lagrangian inverse dynamic model. Results showed that this model leads to a better performance in feedback-linearization control, especially when the reference trajectory is quantized, and with less calculation burden in comparison with the Lagrangian model. The control system employing both models showed robustness against payload uncertainty on the moving platform (150% of the moving platform’s mass). The performance assessment and the robustness approval were performed in simulation using a Simscape model specifically built for this purpose in the Simulink environment.     

Power optimization for connectivity problems

Given a graph with costs on the edges, the power of a node is the maximum cost of an edge leaving it, and the power of the graph is the sum of the powers of the nodes of this graph. Motivated by applications in wireless multi-hop networks, we consider four fundamental problems under the power minimization criteria: the Min-Power b-Edge-Cover problem (MPb-EC) where the goal is to find a min-power subgraph so that the degree of every node v is at least some given integer b(v), the Min-Power k-node Connected Spanning Subgraph problem (MPk-CSS), Min-Power k-edge Connected Spanning Subgraph problem (MPk-CSS), and finally the Min-Power k-Edge-Disjoint Paths problem in directed graphs (MPk-EDP). We give an O(log⁴ n)-approximation algorithm for MPb-EC. This gives an O(log⁴ n)-approximation algorithm for MPk-CSS for most values of k, improving the best previously known O(k)-approximation guarantee. In contrast, we obtain an approximation algorithm for ECSS, and for its variant in directed graphs (i.e., MPk-EDP), we establish the following inapproximability threshold: MPk-EDP cannot be approximated within O(2^log1-ε n) for any fixed ε > 0, unless NP-hard problems can be solved in quasi-polynomial time. This paper was done when V. S. Mirrokni was at Computer Science and Artificial Intelligence Laboratory, MIT.