Magnetic Resonance Signal Amplification by Reversible Exchange of Selective PyFALGEA Oligopeptide Ligands Towards Epidermal Growth Factor Receptors

The biorelevant PyFALGEA oligopeptide ligand, which is selective towards the epidermal growth factor receptor (EGFR), has been successfully employed as a substrate in magnetic resonance signal amplification by reversible exchange (SABRE) experiments. It is demonstrated that PyFALGEA and the iridium catalyst IMes form a PyFALGEA:IMes molecular complex. The interaction between PyFALGEA:IMes and H₂ results in a ternary SABRE complex. Selective 1D EXSY experiments reveal that this complex is labile, which is an essential condition for successful hyperpolarization by SABRE. Polarization transfer from parahydrogen to PyFALGEA is observed leading to significant enhancement of the ¹H NMR signals of PyFALGEA. Different iridium catalysts and peptides are inspected to discuss the influence of their molecular structures on the efficiency of hyperpolarization. It is observed that PyFALGEA oligopeptide hyperpolarization is more efficient when an iridium catalyst with a sterically less demanding NHC ligand system such as IMesBn is employed. Experiments with shorter analogues of PyFALGEA, that is, PyLGEA and PyEA, show that the bulky phenylalanine from the PyFALGEA oligopeptide causes steric hindrance in the SABRE complex, which hampers hyperpolarization with IMes. Finally, a single-scan ¹H NMR SABRE experiment of PyFALGEA with IMesBn revealed a unique pattern of NMR lines in the hydride region, which can be treated as a fingerprint of this important oligopeptide.     

An Exemplar Imidazoline Surfactant for Corrosion Inhibitor Studies: Synthesis,Characterization, and Physicochemical Properties

An optimized one-pot recipe has been developed to synthesize a surfactant molecule, referred to as OMID, consisting of an imidazoline head group and aliphatic tail, which is an exemplar corrosion inhibitor for carbon steel in acidic solutions. As evidenced by gas chromatography, ¹H and ¹³C nuclear magnetic resonance, and Fourier-transform infrared data, a high-purity product was achieved without the use of either a solvent or catalyst. Critical micelle concentration values and corrosion inhibition efficiencies ( η %) were determined in aqueous solutions of hydrochloric acid and sulfuric acid using surface tensiometry and linear polarization resistance measurements, respectively. Hydrolysis of the imidazoline head group as a function of pH (0–11) was explored with ultraviolet–visible absorption spectroscopy. In addition, N 1s and C 1s X-ray photoelectron spectroscopy data were acquired from both surface-adsorbed OMID and a multilayer of the imidazoline head group of OMID. These latter data are highly relevant to those attempting to understand OMID inhibition chemistry.     

Artificial neural network medical decision support tool: predicting transfusion requirements of ER patients.

Blood product transfusion is a financial concern for hospitals and patients. Efficient utilization of this dwindling resource is a critical problem if hospitals are to maximize patient care while minimizing costs. Traditional statistical models do not perform well in this domain. An additional concern is the speed with which transfusion decisions and planning can be made. Rapid assessment in the emergency room (ER) necessarily limits the amount of usable information available (with respect to independent variables available). This study evaluates the efficacy of using artificial neural networks (ANNs) to predict the transfusion requirements of trauma patients using readily available information. A total of 1016 patient records are used to train and test a backpropagation neural network for predicting the transfusion requirements of these patients during the first 2, 2-6, and 6-24 h, and for total transfusions. Sensitivity and specificity analysis are used along with the mean absolute difference between blood units predicted and units transfused to demonstrate that ANNs can accurately predict most ER patient transfusion requirements, while only using information available at the time of entry into the ER.     

The effect of structural features on mechanical properties of loose optical fiber poly(butylene terephthalate) tubes

Results of a study on the modifying mechanical properties of loose optical‐fiber poly(butylene terephthalate) (PBT) tubes, produced during the standard industrial extrusion process, show that heat treatment make the structure of their material to change. The study comprised measurements of mechanical strengths properties of the tubes (tensile strength, compression strength, kinking) and determination of tube material structure [by differential thermal analysis (DTA), wide angle X‐ray scattering analysis (WAXD), and scanning electron microscopy (SEM)]. Results of the study allowed observation that the annealing at 70°C for 34 h of the tubes caused the crystalline α phase to increase in the tube material from ～28.5% to ～31.5% and the structure of the existing crystallites to become more perfect. This made the values of certain mechanical properties of the tubes to increase even by as much as 30%. The tubes following such thermal treatment could be used in cables exposed to heavy‐duty operation in arduous environments, where a larger margin from the standpoint of mechanical properties is required. © 2002 Wiley Periodicals, Inc. J Appl Polym Sci 86: 2130–2134, 2002     

Modeling of systems with overflow multi-rate traffic

The article proposes an analytical method for determining occupancy distribution and blocking probability in systems which are offered overflow traffic composed of multi-service traffic streams. The described analytical model enables determination of parameters of traffic overflowed from primary groups in hierarchically constructed telecommunication networks. The proposed method is based on an appropriate modification of the Kaufman-Roberts recursion for the full-availability group with multi-rate traffic and uses the modified Fredericks & Hayward’s approximation. Additionally, an approximate method for dimensioning systems with multi-service overflow traffic is also presented. The analytical results of the blocking probability and the results obtained in the dimensioning processes calculated using the presented methodology are compared with the data obtained from the system simulation process.     

Knowledge-based search in competitive domains

Artificial intelligence programs operating in competitive domains typically use brute-force search if the domain can be modeled using a search tree or alternately use nonsearch heuristics as in production rule-based expert systems. While brute-force techniques have recently proven to be a viable method for modeling domains with smaller search spaces, such as checkers and chess, the same techniques cannot succeed in more complex domains, such as shogi or go. This research uses a cognitive-based modeling strategy to develop a heuristic search technique based on cognitive thought processes with minimal domain specific knowledge. The cognitive-based search technique provides a significant reduction in search space complexity and, furthermore, enables the search paradigms to be extended to domains that are not typically thought of as search domains such as aerial combat or corporate takeovers.     

Influence of the amount of ferromagnetic addition on the rheological properties of spinning solutions,the structure,the strength,and thermal properties of polyacrylonitrile fibres

The rheological properties of spinning solutions of polyacrylonitrile in dimethyl formamide (DMF) containing various amounts of a ferromagnetic nanoaddition were investigated. The porous structure, the strength and thermal properties of fibers obtained from these solutions were assessed, as well as the uniformity of the nanoaddition distribution on the fiber surface was estimated. © 2008 Wiley Periodicals, Inc. J Appl Polym Sci, 2008     

Elongational viscosity of LDPEs and polystyrenes using entrance loss data

For two low‐density polyethylenes and two polystyrenes, axisymmetric and planar elongational viscosities are estimated using entrance loss data from capillary and slit rheometers, respectively. The elongational viscosity is estimated by optimizing the values of various parameters in the Sarkar–Gupta elongational viscosity model such that the entrance loss predicted by a finite element simulation agrees with the corresponding experimental data. The predicted entrance loss is in good agreement with the experimental data at high flow rates. The difference in the experimental and predicted entrance loss at lower flow rates might have been caused by large error in the experimental data in this range. POLYM. ENG. SCI., 2008. © 2007 Society of Plastics Engineers     

Kinetics of thermal decomposition of unsaturated polyester resins with reduced flammability

In this article, the kinetics of thermal decomposition of unsaturated maleic–phthalic polyester resins, flame‐retarded with zinc hydroxystannate, was studied by thermogravimetric analysis at different heating rates. At the first stage, it was found, on the basis of isoconversional analysis by the methods of Friedman and of Ozawa–Flynn–Wall, that the value of the (apparent) activation energy (E) characteristically changes in three steps during the degradation. Further kinetic studies using nonlinear regression methods revealed the best fits for both pristine and stabilized resins. It was observed that the course of E versus the degree of conversion (α) during degradation of zinc hydroxystannate‐containing resins (α > 0.8) was characterized by higher values of E—this phenomenon can be explained in terms of the flame‐retardation action of zinc hydroxystannate, which is believed to operate primarily in the condensed phase. At the next stage, kinetic analysis by the nonregression method was performed to find the kinetic model [f(α) function] of the decomposition process; hence, for pristine resin, the best fit was found for the Avrami–Yerofeeyev model (nuclei growth), and for stabilized samples, the nth‐order function with catalysis proved to be the best approximation. The obtained kinetic parameters in the form of E, the preexponential factor A, and the model function f(α) allow a prediction of the polyester resin's thermal behavior in an extrapolated range of degree of conversion, time, and temperature. © 2003 Wiley Periodicals, Inc. J Appl Polym Sci 88: 2851–2857, 2003