Screening approach for identifying cocrystal types and resolution opportunities in complex chiral multicomponent systems

Cocrystallization of racemic-compound-forming chiral molecules can result in conglomerate cocrystals or diastereomerically related cocrystals, which enable the application of chiral separation techniques such as preferential crystallization and classic resolution. Here, a systematic method to identify the types and phase diagrams of cocrystals formed by chiral target compounds and candidate coformers in a particular solvent system is presented, which allows the design of suitable chiral resolution processes. The method is based on saturation temperature measurements of specific solution compositions containing both enantiomers of chiral molecules and a coformer. This method is applied to analyze three different systems. For racemic phenylalanine (Phe) in water/ethanol mixtures one of the enantiomers selectively cocrystallizes with the opposite enantiomer of valine (Val), forming the more stable diastereomerically related cocrystal. The racemic compound ibuprofen crystallizes with the nonchiral coformer 1,2-bis(4-pyridyl)ethane (BPN) as racemic compound cocrystals. More interestingly, when it is combined with trans-1-(2-pyridyl)-2-(4-pyridyl)ethylene (BPE), the racemic compound ibuprofen cocrystallizes as a conglomerate, which in principle enables the application of preferential crystallization of this racemic compound. The systematic method shows the benefit of using pseudo-binary phase diagrams. Such pseudo-binary phase diagrams depict the saturation temperature on a very specific route through the quaternary phase diagram, allowing the identification of various cocrystal types as well as the corresponding cocrystallization conditions. The systematic method can be used to identify a suitable solid phase for chiral separation, and the obtained phase diagram information enables the performance of a crystallization-mediated chiral resolution process design. Such a guideline for a chiral resolution process design has never been reported for conglomerate cocrystal systems such as IBU:BPE, presented in this study

Domain Wall Spacetimes: Instability of Cosmological Event and Cauchy Horizons

The stability of cosmological event and Cauchy horizons of spacetimes associated with plane symmetric domain walls are studied. It is found that both horizons are not stable against perturbations of null fluids and massless scalar fields; they are turned into curvature singularities. These singularities are light-like and strong in the sense that both the tidal forces and distortions acting on test particles become unbounded when theses singularities are approached.Comment: Latex, 3 figures not included in the text but available upon reques

Comprehensive molecular characterization of gastric adenocarcinoma

Gastric cancer is a leading cause of cancer deaths, but analysis of its molecular and clinical characteristics has been complicated by histological and aetiological heterogeneity. Here we describe a comprehensive molecular evaluation of 295 primary gastric adenocarcinomas as part of The Cancer Genome Atlas (TCGA) project. We propose a molecular classification dividing gastric cancer into four subtypes: tumours positive for Epstein–Barr virus, which display recurrent PIK3CA mutations, extreme DNA hypermethylation, and amplification of JAK2, CD274 (also known as PD-L1) and PDCD1LG2 (also knownasPD-L2); microsatellite unstable tumours, which show elevated mutation rates, including mutations of genes encoding targetable oncogenic signalling proteins; genomically stable tumours, which are enriched for the diffuse histological variant and mutations of RHOA or fusions involving RHO-family GTPase-activating proteins; and tumours with chromosomal instability, which show marked aneuploidy and focal amplification of receptor tyrosine kinases. Identification of these subtypes provides a roadmap for patient stratification and trials of targeted therapies

Multiplatform Analysis of 12 Cancer Types Reveals Molecular Classification within and across Tissues of Origin

Recent genomic analyses of pathologically-defined tumor types identify “within-a-tissue” disease subtypes. However, the extent to which genomic signatures are shared across tissues is still unclear. We performed an integrative analysis using five genome-wide platforms and one proteomic platform on 3,527 specimens from 12 cancer types, revealing a unified classification into 11 major subtypes. Five subtypes were nearly identical to their tissue-of-origin counterparts, but several distinct cancer types were found to converge into common subtypes. Lung squamous, head & neck, and a subset of bladder cancers coalesced into one subtype typified by TP53 alterations, TP63 amplifications, and high expression of immune and proliferation pathway genes. Of note, bladder cancers split into three pan-cancer subtypes. The multi-platform classification, while correlated with tissue-of-origin, provides independent information for predicting clinical outcomes. All datasets are available for data-mining from a unified resource to support further biological discoveries and insights into novel therapeutic strategies

Evaluating adsorbed-phase activity coefficient models using a 2D-lattice model

<div><p>Despite the wide use of the real adsorbed solution theory to predict multicomponent adsorption equilibrium, the models used for the adsorbed phase activity coefficients are usually borrowed from the gas–liquid phase equilibria. In this work, the accuracy of the Wilson and NRTL models for evaluating adsorbed phase activity coefficients is tested using a 2D-lattice model. An accurate model for adsorbed-phase activity coefficients should have no problem in fitting adsorption data obtained using this simple lattice model. The results, however, show that the commonly used Wilson and NRTL models cannot describe the adsorbed phase activity coefficients for slightly non-ideal to strong non-ideal mixtures. Therefore, until new models for adsorbed phase activity coefficients are developed, we should use existing models for liquids with care. In the second part of this work, the use of Monte Carlo simulations on a segregated 2D-lattice model, for predicting adsorption of mixtures is investigated. The segregated model assumes that the competition for adsorption occurs at isolated adsorption sites, and that the molecules from each adsorption site interact with the bulk phase independently. Two binary mixtures in two adsorbent materials were used as case studies for testing the predictions of the segregated 2D-lattice model: the binary system CO₂–N₂ in the hypothetical pure silica zeolite PCOD8200029, with isolated adsorption sites and normal preference for adsorption, and the binary system CO₂–C₃H₈ in pure silica mordenite (MOR), with isolated adsorption sites and inverse site preference. The segregated 2D-lattice model provides accurate predictions for the system CO₂–N₂ in PCOD8200029 but fails in predicting the adsorption behaviour of CO₂–C₃H₈ in pure silica MOR. The predictions of the segregated ideal adsorbed solution theory model are superior to those of the 2D-lattice model.</p></div

Design and Validation of a Droplet-based Microfluidic System To Study Non-Photochemical Laser-Induced Nucleation of Potassium Chloride Solutions

Non-photochemical laser-induced nucleation (NPLIN) has emerged as a promising primary nucleation control technique offering spatiotemporal control over crystallization with potential for polymorph control. So far, NPLIN was mostly investigated in milliliter vials, through laborious manual counting of the crystallized vials by visual inspection. Microfluidics represents an alternative to acquiring automated and statistically reliable data. Thus we designed a droplet-based microfluidic platform capable of identifying the droplets with crystals emerging upon Nd:YAG laser irradiation using the deep learning method. In our experiments, we used supersaturated solutions of KCl in water, and the effect of laser intensity, wavelength (1064, 532, and 355 nm), solution supersaturation (S), solution filtration, and intentional doping with nanoparticles on the nucleation probability is quantified and compared to control cooling crystallization experiments. Ability of dielectric polarization and the nanoparticle heating mechanisms proposed for NPLIN to explain the acquired results is tested. Solutions with lower supersaturation (S = 1.05) exhibit significantly higher NPLIN probabilities than those in the control experiments for all laser wavelengths above a threshold intensity (50 MW/cm2). At higher supersaturation studied (S = 1.10), irradiation was already effective at lower laser intensities (10 MW/cm2). No significant wavelength effect was observed besides irradiation with 355 nm light at higher laser intensities (≥50 MW/cm2). Solution filtration and intentional doping experiments showed that nanoimpurities might play a significant role in explaining NPLIN phenomena