On Modeling Missing Data in Structural Investigations Based on Tetrachoric Correlations With Free and Fixed Factor Loadings

In modeling missing data, the missing data latent variable of the confirmatory factor model accounts for systematic variation associated with missing data so that replacement of what is missing is not required. This study aimed at extending the modeling missing data approach to tetrachoric correlations as input and at exploring the consequences of switching between models with free and fixed factor loadings. In a simulation study, confirmatory factor analysis (CFA) models with and without a missing data latent variable were used for investigating the structure of data with and without missing data. In addition, the numbers of columns of data sets with missing data and the amount of missing data were varied. The root mean square error of approximation (RMSEA) results revealed that an additional missing data latent variable recovered the degree-of-model fit characterizing complete data when tetrachoric correlations served as input while comparative fit index (CFI) results showed overestimation of this degree-of-model fit. Whereas the results for fixed factor loadings were in line with the assumptions of modeling missing data, the other results showed only partial agreement. Therefore, modeling missing data with fixed factor loadings is recommended.

Glucuronidation Pathways of 5- and 7-Hydroxypropranolol: Determination of Glucuronide Structures and Enzyme Selectivity

Propranolol, a non-selective beta-blocker medication, has been utilized in the treatment of cardiovascular diseases for several decades. Its hydroxynaphthyl metabolites have been recognized to possess varying degrees of beta-blocker activity due to the unaltered side-chain. This study achieved the successful separation and identification of diastereomeric glucuronic metabolites derived from 4-, 5-, and 7-hydroxypropranolol (4-OHP, 5-OHP, and 7-OHP) in human urine. Subsequently, reaction phenotyping of 5- and 7-hydroxypropranolol by different uridine 5'-diphospho-glucuronosyltransferases (UGTs) was carried out, with a comparison to the glucuronidation of 4-hydroxypropranolol (4-OHP). Among the 19 UGT enzymes examined, UGT1A1, UGT1A3, UGT1A7, UGT1A8, UGT1A9, UGT1A10, UGT2A1, and UGT2A2 were found to be involved in the glucuronidation of 5-OHP. Furthermore, UGT1A6 exhibited glucuronidation activity towards 7-OHP, along with the aforementioned eight UGTs. Results obtained by glucuronidation of corresponding methoxypropranolols and MS/MS analysis of 1,2-dimethylimidazole-4-sulfonyl (DMIS) derivatives of hydroxypropranolol glucuronides suggest that both the aromatic and aliphatic hydroxy groups of the hydroxypropranolols may be glucuronidated in vitro. However, the analysis of human urine samples collected after the administration of propranolol leads us to conclude that aromatic-linked glucuronidation is the preferred pathway under physiological conditions.

Effects of Nd2O3 Nanoparticles on the Structural Characteristics and Dielectric Properties of PVA Polymeric Films

Polyvinyl alcohol (PVA) and Neodymium (III) oxide (Nd2O3) were combined to synthesized flexible innovative PVA/Nd2O3 polymer composite samples utilizing a solution casting approach for use in dielectric devices. The XRD, FTIR, and SEM methods are all investigated to characterize the composite films. In a frequency of 50 Hz to 5 MHz, the effects of additive Nd2O3 on the dielectric behavior of PVA were recorded. The PVA/Nd2O3 composite films were successfully fabricated, as shown by XRD and infrared spectroscopy. The scanning microscopy pictures showed that the Nd2O3 was loaded and distributed uniformly throughout the PVA. After the incorporation of Nd2O3, the composite PVA/Nd2O3 has a conductivity of 6.82 × 10-9 S·cm-1, while the PVA has a conductivity of 0.82 × 10-9 S·cm-1. Another improvement is the decrease in the relaxation time from 14.2 × 10-5 s for PVA to 6.35 × 10-5 s for PVA/Nd2O3, and an increase in the dielectric constant of 0.237 for PVA to 0.484 at a frequency of 100 Hz. The results showed that the composite samples have considerable changes as flexible films in different applications, including batteries and electronic circuits.

Synthesis and Characterization of Antibacterial Chitosan Films with Ciprofloxacin in Acidic Conditions

This work presents the results of research on obtaining chitosan (CS) films containing on their surface ciprofloxacin (CIP). A unique structure was obtained that not only gives new properties to the films, but also changes the way of coverage and structure of the surface. The spectroscopic test showed that in the process of application of CIP on the surface of CS film, CIP was converted from its crystalline form to an amorphic one, hence improving its bioavailability. This improved its scope of microbiological effect. The research was carried out on the reduction of CIP concentration during the process of CIP adhesion to the surface of chitosan films. The antibacterial activity of the CS films with and without the drug was evaluated in relation to Escherichia coli and Staphylococcus aureus, as well as Candida albicans and Penicillium expansum. Changes in the morphology and roughness of membrane surfaces after the antibacterial molecule adhesion process were tested with atomic force microscopy (AFM) and scanning electron microscopy (SEM). Structural analysis of CS and its modifications were confirmed with Fourier-transform spectroscopy in the infrared by an attenuated total reflectance of IR radiation (FTIR-ATR) and solid-state nuclear magnetic resonance (NMR).

On Modeling Missing Data of an Incomplete Design in the CFA Framework

The paper reports an investigation on whether valid results can be achieved in analyzing the structure of datasets although a large percentage of data is missing without replacement. Two types of confirmatory factor analysis (CFA) models were employed for this purpose: the missing data CFA model with an additional latent variable for representing the missing data and the semi-hierarchical CFA model that also includes the additional latent variable and reflects the hierarchical structure assumed to underlie the data. Whereas, the missing data CFA model assumes that the model is equally valid for all participants, the semi-hierarchical CFA model is implicitly specified differently for subgroups of participants with and without omissions. The comparison of these models with the regular one-factor model in investigating simulated binary data revealed that the modeling of missing data prevented negative effects of missing data on model fit. The investigation of the accuracy in estimating the factor loadings yielded the best results for the semi-hierarchical CFA model. The average estimated factor loadings for items with and without omissions showed the expected equal sizes. But even this model tended to underestimate the expected values.

The Diverse World of Foldamers: Endless Possibilities of Self-Assembly

Different classes of foldamers, which are synthetic oligomers that adopt well-defined conformations in solution, have been the subject of extensive studies devoted to the elucidation of the forces driving their secondary structures and their potential as bioactive molecules. Regardless of the backbone type (peptidic or abiotic), the most important features of foldamers are the high stability, easy predictability and tunability of their folding, as well as the possibility to endow them with enhanced biological functions, with respect to their natural counterparts, by the correct choice of monomers. Foldamers have also recently started playing a starring role in the self-assembly of higher-order structures. In this review, selected articles will be analyzed to show the striking number of self-assemblies obtained for foldamers with different backbones, which will be analyzed in order of increasing complexity. Starting from the simplest self-associations in solution (e.g., dimers of β-strands or helices, bundles, interpenetrating double and multiple helices), the formation of monolayers, vesicles, fibers, and eventually nanostructured solid tridimensional morphologies will be subsequently described. The experimental techniques used in the structural investigation, and in the determination of the driving forces and mechanisms underlying the self-assemblies, will be systematically reported. Where applicable, examples of biomimetic self-assembled foldamers and their interactions with biological components will be described.