Diketonylpyridinium cations as a support of new ionic liquid crystals and ion-conductive materials: analysis of counter-ion effects

Ionic liquid crystals (ILCs) allow the combination of the high ionic conductivity of ionic liquids (ILs) with the supramolecular organization of liquid crystals (LCs). ILCs salts were obtained by the assembly of long-chained diketonylpyridinium cations of the type [HOO^(R(n)pyH)] + and BF_(4)^(-) , ReO_(4)^(-), NO_(3)^(-), CF_(3)SO_(3)^(-), CuCl_(4)^(2-) counter-ions. We have studied the thermal behavior of five series of compounds by differential scanning calorimetry (DSC) and hot stage polarized light optical microscopy (POM). All materials show thermotropic mesomorphism as well as crystalline polymorphism. X-ray diffraction of the [HOO^(R(12)pyH)][ReO_(4)] crystal reveals a layered structure with alternating polar and apolar sublayers. The mesophases also exhibit a lamellar arrangement detected by variable temperature powder X-ray diffraction. The CuCl_(4)^(2-) salts exhibit the best LC properties followed by the ReO_(4)^(-) ones due to low melting temperature and wide range of existence. The conductivity was probed for the mesophases in one species each from the ReO_(4)^(-) , and CuCl_(4)^(2-) families, and for the solid phase in one of the non-mesomorphic Cl^(-) salts. The highest ionic conductivity was found for the smectic mesophase of the ReO_(4)^(-) containing salt, whereas the solid phases of all salts were dominated by electronic contributions. The ionic conductivity may be favored by the mesophase lamellar structure.

A Diagnostic Calculator for Detecting Glaucoma on the Basis of Retinal Nerve Fiber Layer, Optic Disc, and Retinal Ganglion Cell Analysis by Optical Coherence Tomography

Purpose: The purpose of this study was to develop and validate a multivariate predictive model to detect glaucoma by using a combination of retinal nerve fiber layer (RNFL), retinal ganglion cell-inner plexiform (GCIPL), and optic disc parameters measured using spectral-domain optical coherence tomography (OCT). Methods: Five hundred eyes from 500 participants and 187 eyes of another 187 participants were included in the study and validation groups, respectively. Patients with glaucoma were classified in five groups based on visual field damage. Sensitivity and specificity of all glaucoma OCT parameters were analyzed. Receiver operating characteristic curves (ROC) and areas under the ROC (AUC) were compared. Three predictive multivariate models (quantitative, qualitative, and combined) that used a combination of the best OCT parameters were constructed. A diagnostic calculator was created using the combined multivariate model. Results: The best AUC parameters were: inferior RNFL, average RNFL, vertical cup/disc ratio, minimal GCIPL, and inferior-temporal GCIPL. Comparisons among the parameters did not show that the GCIPL parameters were better than those of the RNFL in early and advanced glaucoma. The highest AUC was in the combined predictive model (0.937; 95% confidence interval, 0.911–0.957) and was significantly (P = 0.0001) higher than the other isolated parameters considered in early and advanced glaucoma. The validation group displayed similar results to those of the study group. Conclusions: Best GCIPL, RNFL, and optic disc parameters showed a similar ability to detect glaucoma. The combined predictive formula improved the glaucoma detection compared to the best isolated parameters evaluated. The diagnostic calculator obtained good classification from participants in both the study and validation groups.