Drug-dendrimer supramolecular complexation studied from molecular dynamics simulations and NMR spectroscopy

Fully atomistic molecular dynamics (MD) simulations and NMR spectroscopy were employed to get insights about the molecular details of drug-dendrimer supramolecular association phenomena, using piroxicam (PRX) and the third generation poly(amido amine) (PAMAM-G3) dendrimer as model systems. Theoretical results concerning the complex stoichiometry suggest that PRX forms drug-dendrimer complexes of the type 24:1 at pH 7.0. This result was validated with the experimental quantities obtained from aqueous solubility profiles, which led to an empiric stoichiometry of 23:1 for the PRX:PAMAM-G3 system. The predicted binding mode between PRX and PAMAM-G3 accounts for the preferred encapsulation of the drug inside dendrimer cavities, which is mainly driven by van der Waals and hydrogen bonding interactions, and to a lesser extent, for the external association of the guest through electrostatic contacts with the positively charged amino groups of PAMAM periphery. The binding mode obtained from MD simulations was confirmed with 2D-NOESY experiments, which evidence the preferred internal complexation of PRX with PAMAM-G3. The predominance of internal encapsulation over external contacts in the PRX:PAMAM-G3 system differs from the general behaviour expected for acidic anionic guests, for which external electrostatic interactions with the positively charged PAMAM surface have been postulated as the most relevant factor for drug association.     

Programmable Polymer‐Based Supramolecular Temperature Sensor with a Memory Function

A new class of polymeric thermometers with a memory function is reported that is based on the supramolecular host–guest interactions of poly(N‐isopropylacrylamide) (PNIPAM) with side‐chain naphthalene guest moieties and the tetracationic macrocycle cyclobis(paraquat‐p‐phenylene) (CBPQT⁴⁺) as the host. This supramolecular thermometer exhibits a memory function for the thermal history of the solution, which arises from the large hysteresis of the thermoresponsive LCST phase transition (LCST=lower critical solution temperature). This hysteresis is based on the formation of a metastable soluble state that consists of the PNIPAM–CBPQT⁴⁺ host–guest complex. When heated above the transition temperature, the polymer collapses, and the host–guest interactions are disrupted, making the polymer more hydrophobic and less soluble in water. Aside from providing fundamental insights into the kinetic control of supramolecular assemblies, the developed thermometer with a memory function might find use in applications spanning the physical and biological sciences.     

Theoretic quantum information entropies for the generalized hyperbolic potential

The Shannon entropy (S) and the Fisher Information (I) entropies are investigated for a generalized hyperbolic potential in position and momentum spaces. First, the Schrodinger equation is solved exactly using the Nikiforov-Uvarov-Functional Analysis method to obtain the energy spectra and the corresponding wave function. By Fourier transforming the position space wave function, the corresponding momentum wave function was obtained for the low-lying states corresponding to the ground and first excited states. The positions and momentum of Shannon entropy and Fisher Information entropies were calculated numerically. Finally, the Bialynicki-Birula and Mycielski and the Stam-Cramer-Rao inequalities for the Shannon entropy and Fisher Information entropies, respectively, were tested and were found to be satisfied for all cases considered.     

Disentangling Reaction Processes of Zeolites within Single‐Oriented Channels

Establishing structure–reactivity relationships for specific channel orientations of zeolites is vital to developing new, superior materials for various applications, including oil and gas conversion processes. Herein, a well‐defined model system was developed to build structure–reactivity relationships for specific zeolite‐channel orientations during various catalytic reaction processes, for example, the methanol‐ and ethanol‐to‐hydrocarbons (MTH and ETH) process as well as oligomerization reactions. The entrapped and effluent hydrocarbons from single‐oriented zeolite ZSM‐5 channels during the MTH process were monitored by using operando UV/Vis diffuse reflectance spectroscopy (DRS) and on‐line mass spectrometry (MS), respectively. The results reveal that the straight channels favor the formation of internal coke, promoting the aromatic cycle. Furthermore, the sinusoidal channels produce aromatics, (e.g., toluene) that further grow into larger polyaromatics (e.g., graphitic coke) leading to deactivation of the zeolites. This underscores the importance of careful engineering of materials to suppress coke formation and tune product distribution by rational control of the location of zeolite acid sites and crystallographic orientations.     

An Edge Server Placement Method Based on Reinforcement Learning

In mobile edge computing systems, the edge server placement problem is mainly tackled as a multi-objective optimization problem and solved with mixed integer programming, heuristic or meta-heuristic algorithms, etc. These methods, however, have profound defect implications such as poor scalability, local optimal solutions, and parameter tuning difficulties. To overcome these defects, we propose a novel edge server placement algorithm based on deep q-network and reinforcement learning, dubbed DQN-ESPA, which can achieve optimal placements without relying on previous placement experience. In DQN-ESPA, the edge server placement problem is modeled as a Markov decision process, which is formalized with the state space, action space and reward function, and it is subsequently solved using a reinforcement learning algorithm. Experimental results using real datasets from Shanghai Telecom show that DQN-ESPA outperforms state-of-the-art algorithms such as simulated annealing placement algorithm (SAPA), Top-K placement algorithm (TKPA), K-Means placement algorithm (KMPA), and random placement algorithm (RPA). In particular, with a comprehensive consideration of access delay and workload balance, DQN-ESPA achieves up to 13.40% and 15.54% better placement performance for 100 and 300 edge servers respectively.     

NMR imaging of solid polymers: Strategies for chemical-shift selectivity

One reason that the solid-state imaging field is exciting is because of its potential to provide spatially resolved chemical information from deep inside a solid sample. To achieve this goal, methods are needed which exploit the many NMR parameters to generate image contrast. We describe two strategies for employing the chemical-shift anisotropy as a contrast mechanism in images of abundant nuclei in solid polymers. We illustrate these approaches with images which map spatial variations of molecular orientation in samples of polytetrafluoroethylene.     

Effect of molecular architecture on DBS-induced block copolymer gels: A rheological study

Dibenzylidene sorbitol (DBS) is capable of gelling a variety of organic solvents and polymeric materials by forming a rigid, 3-D hydrogen-bonded network. In this work, two poly(siloxane)/poly(propylene oxide) segmented copolymers of equal composition and molecular weight, but different architectures (endblocked vs. pendant), as well as a pure poly(propylene oxide), have been gelled with DBS. We have investigated the dynamic rheological properties of these gels to ascertain the effect of copolymer architecture, PDMS comonomer and DBS concentration on network formation.     

Design and experimental validation of a nonlinear controller for underactuated surface vessels

Nonlinear Dynamics - This paper addresses the problem of trajectory tracking control of an underactuated surface vessel moving in a two-dimensional space in the presence of unknown disturbances. In...