Osteopontin: A Uranium Phosphorylated Binding‐Site Characterization

Herein, we describe the structural investigation of one possible uranyl binding site inside a nonstructured protein. This approach couples spectroscopy, thermodynamics, and theoretical calculations (DFT) and studies the interaction of uranyl ions with a phosphopeptide, thus mimicking a possible osteopontin (OPN) hydroxyapatite growth‐inhibition site. Although thermodynamical aspects were investigated by using time‐resolved laser fluorescence spectroscopy (TRLFS) and isothermal titration calorimetry (ITC), structural characterization was performed by extended X‐ray absorption fine structure (EXAFS) at the U L_III‐edge combined with attenuated total reflection Fourier transform infrared (ATR‐FTIR) spectroscopy. From the vibrational and fluorescence spectra, several structural models of a UO₂²⁺/peptide complex were developed and subsequently refined by using theoretical calculations to fit the experimental EXAFS obtained. The structural effect of the pH value was also considered under acidic to moderately acidic conditions (pH 1.5–5.5). Most importantly, the uranyl/peptide coordination environment was similar to that of the native protein.     

A stabilized formulation of IBX (SIBX) for safe oxidation reactions including a new oxidative demethylation of phenolic methyl aryl ethers

[reaction: see text] SIBX is a nonexplosive formulation of IBX that can be used as a suspension in a variety of standard organic solvents such as refluxing EtOAc and THF to oxidize safely alcohols into aldehydes and ketones. The use of hot THF is limited to the oxidation of allylic and benzylic alcohols. Most yields are comparable to those obtained with IBX or DMP. SIBX can also be used to perform oxygenative demethylation of 2-methoxyarenols into orthoquinones and catechols.     

Online large volume sample staking preconcentration and separation of enantiomeric GHRH analogs by capillary electrophoresis

A capillary electrophoresis method is proposed to analyze the four most well-known growth hormone–releasing hormone (GHRH) analogs that are misused by athletes. Dimethyl-β-cyclodextrin used as a chiral selector allowed, for the first time, the separation of those basic peptide analogs, including enantiopeptides (sermorelin and CJC-1293) that differ by the chirality of only one amino acid. To increase the method sensitivity, electrokinetic preconcentration methods have been investigated. The large volume sample stacking with polarity switching (PS-LVSS) method with an injected sample volume corresponding to 80% of the capillary one was found superior to the sweeping in terms of signal enhancement factor (SEF). Acid and organic solvent addition to the sample (0.1 mM phosphoric acid with 30% methanol) led to a twofold signal improvement, when compared to water as a matrix. We increased capillary dimensions to provide a signal enhancement through the injection of a larger sample volume. Finally, using a combination of the optimized PS-LVSS preconcentration with the chiral capillary zone electrophoresis (CZE), the GHRH analogs were separated and limits of detection between 75 and 200 ng/mL were reached. This method was successfully applied to urine after a desalting step. An optimized C18 SPE was used for that purpose in order to provide low sample conductivity (<130 µS/cm) and preserve the efficiency of LVSS preconcentration. SEF of 640 was obtained with desalted urine spiked with sermorelin by comparison to the CZE (without preconcentration) method.     

Host-guest Assembly Based on γ-Cyclodextrin-functionalized Multiwalled Carbon Nanotubes for Rutin Electrochemical Sensing

Here, we report multiwalled carbon nanotubes (MWCNTs) functionalized with γ-cyclodextrins (γCD) as a novel electrochemical strategy for Rutin determination, showing superior performance than β-cyclodextrins (βCD) modified MWCNTs, suggesting an adequate environment for host-guest interactions. Under optimized conditions, the sensor showed a linear range of 39–975 nmol L⁻¹ and a limit of detection of 7 nmol L⁻¹. When tested with quercetin, catechin, and caffeine, the platform presented high selectivity with an interference response <10 %. The method was employed to quantify Rutin in spiked pharmaceutical and herbal extracts, providing recovery of 93–98.4 %. Also, HPLC-PDA confirmed the method‘s accuracy.     

Vinyl nosylates as partner in copper and silver co-catalyzed Sonogashira cross-coupling reactions

Vinyl nosylates, readily obtained from β-dicarbonyl derivatives, could be efficiently engaged in Sonogashira cross-coupling reactions, either cocatalyzed by copper or silver salts. The para-nitrobenzenesulfonate (nosylate) group allows this coupling to be performed under very mild conditions (room temperature). These new leaving group and mild conditions could be applied to the synthesis of acetylenic coumarinyl derivatives and to the total synthesis of an acetylenic monoterpene natural product, named cleviolide.     

A priori estimates for rough PDEs with application to rough conservation laws

We introduce a general weak formulation for PDEs driven by rough paths, as well as a new strategy to prove well-posedness. Our procedure is based on a combination of fundamental a priori estimates with (rough) Gronwall-type arguments. In particular this approach does not rely on any sort of transformation formula (flow transformation, Feynman–Kac representation formula etc.) and is therefore rather flexible. As an application, we study conservation laws driven by rough paths establishing well–posedness for the corresponding kinetic formulation.     

A study of accelerated Newton methods for multiple polynomial roots

We analyze and compare several accelerated Newton methods with built in multiplicity estimates. We also introduce the concept of indicator functions and discuss the Crouse-Putt method. It is shown that many of the accelerated Newton methods not only derive from Schröder’s classic approach but are equivalent. The related computational experiments show that the built in multiplicity estimates can significantly decrease the number of Newton iterations, while the error of these estimates may significantly increase.     

New product launch decisions with robust optimization

We consider a problem where a company must decide the order in which to launch new products within a given time horizon and budget constraints, and where the parameters of the adoption rate of these new products are subject to uncertainty. This uncertainty can bring significant change to the optimal launch sequence. We present a robust optimization approach that incorporates such uncertainty on the Bass diffusion model for new products as well as on the price response function of partners that collaborate with the company in order to bring its products to market. The decision-maker optimizes his worst-case profit over an uncertainty set where nature chooses the time periods in which (integer) units of the budgets of uncertainty are used for worst impact. This leads to uncertainty sets with binary variables. We show that a conservative approximation of the robust problem can nonetheless be reformulated as a mixed integer linear programming problem, is therefore of the same structure as the deterministic problem and can be solved in a tractable manner. Finally, we illustrate our approach on numerical experiments. Our model also incorporates contracts with potential commercialization partners. The key output of our work is a sequence of product launch times that protects the decision-maker against parameter uncertainty for the adoption rates of the new products and the response of potential partners to partnership offers.     

Protecting the data-driven newsvendor against rare events: a correction-term approach

We propose an approach to the data-driven newsvendor problem that incorporates a correction factor to account for rare events, when the decision-maker has few historical data points at his disposal but knows the range of the demand. This mitigates a weakness of pure data-driven methodologies, specifically, the fact that they under-protect the system against tail events, which are in general under-observed in the empirical demand distribution. We test the approach in extensive computational experiments and provide a summary table of the numerical experiments to help the decision maker gain further insights.