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We study the formation of surface relief structures in azo-polymers generated via two-photon induced photoisomerization using a femtosecond near-infrared optical vortex laser beam. These structures exhibit exotic flower-like shapes with petals along the azimuthal direction, and they are formed from spatial mode instability, which is associated with third-order nonlinear effects in the azo-polymer. This process is a unique and exotic interaction between light and matter, which may be applied to the development of advanced optical data storage technologies. Here, an additional degree of freedom is offered by the number of formed petals, which themselves are a function of the topological charge of the optical vortex beam. [ABSTRACT FROM AUTHOR]

In silico prediction for toxicity of chemicals is required to reduce cost, time, and animal testing. However, predicting hepatocellular hypertrophy, which often affects the derivation of the No-Observed-Adverse-Effect Level in repeated dose toxicity studies, is difficult because pathological findings are diverse, mechanisms are largely unknown, and a wide variety of chemical structures exists. Therefore, a method for predicting the hepatocellular hypertrophy of diverse chemicals without complete understanding of their mechanisms is necessary. In this study, we developed predictive classification models of hepatocellular hypertrophy using machine learning--specifically, deep learning, random forest, and support vector machine. We extracted hepatocellular hypertrophy data on rats from 2 toxicological databases, our original database developed from risk assessment reports such as pesticides, and the Hazard Evaluation Support System Integrated Platform. Then, we constructed prediction models based on molecular descriptors and evaluated their performance using independent test chemicals datasets, which differed from the training chemicals datasets. Further, we defined the applicability domain (AD), which generally limits the application for chemicals, as structurally similar to the training chemicals dataset. The best model was found to be the support vector machine model using the Hazard Evaluation Support System Integrated Platform dataset, which was trained with 251 chemicals and predicted 214 test chemicals inside the applicability domain. It afforded a prediction accuracy of 0.76, sensitivity of 0.90, and area under the curve of 0.81. These in silico predictive classification models could be reliable tools for hepatocellular hypertrophy assessments and can facilitate the development of in silico models for toxicity prediction. [ABSTRACT FROM AUTHOR]

Possible effects of interleukin-6 ( IL-6) on reproductive performance, embryonal development, parturition, and postnatal development have been suggested based on protein/m RNAexpression level of IL-6 in related organs, but less is known about functions of IL-6 signals in these areas. Following two different approaches have been employed to investigate the role of IL-6 signals in fertility and pre-/postnatal development: administration of a rat anti-mouse IL-6 receptor antibody, MR16-1, to mice as a neutralizing antibody system, and B6.129S2- Il6tm1Kopf/ J ( IL-6 knockout [ KO]) mice as a KO system. By intravenously dosing 50 mg/kg of MR16-1 every 3 days, animals in male and female fertility studies and dams in a pre-/postnatal development study exhibited plasma MR16-1 concentrations much higher than the effective plasma concentration, indicating that MR16-1 exposure was sufficient to completely block IL-6 signals. The concentration of MR16-1 in the plasma of fetuses exceeded that in the plasma of pregnant animals, and MR16-1 concentration in milk was about one-fourth of that in plasma. Both the transient IL-6 signal blockade by MR16-1, and the constitutive IL-6 signal inhibition using IL-6 KO mice in a combined fertility and pre-/postnatal development study, revealed no biologically important effects on fertility, early embryonic development to implantation, or pre-/postnatal development, including Ig G/ Ig M production by keyhole limpet hemocyanin sensitization. These results indicate that IL-6 signals have no unique, noncompensable roles in reproduction and development in the whole body system, although contributions of IL-6 in the signaling network appear to exist, as suggested by previously published investigations. [ABSTRACT FROM AUTHOR]

The sugar-based gemini surfactant with peptide bonds, N,N'-bisalkyl-N,N'-bis[2-(lactobionylamide)ethyl]hexanediamide (2C(n)peLac, in which n represents hydrocarbon chain lengths of 12 and 16), was synthesized by reacting adipoyl chloride with the corresponding monomeric surfactant N-alkyl-N'-lactobionylethylenediamine (C(n)peLac), which was obtained by reacting ethylenediamine with alkyl bromide and lactobionic acid. The adsorption and micellization properties of C(n)peLac and 2C(n)peLac were characterized by the measurement of their equilibrium and dynamic surface tension, steady-state fluorescence using pyrene as a probe, dynamic light scattering (DLS), and time-resolved fluorescence quenching (TRFQ), and their biodegradability was also investigated. The critical micelle concentration (cmc) decreases with an increase in the hydrocarbon chains from monomeric to gemini surfactants, whereas it increases with an increase in the chain length from 12 to 16 for both systems. The increases in both the hydrocarbon chain and the chain length of sugar-based surfactants reduce surface activities such as the ability to lower the surface tension, the occupied area per molecule, and the adsorption rate at the air/water interface. The sugar-based surfactants C(n)peLac and 2C(n)peLac exhibit unique aggregation behavior in aqueous solution. The DLS results indicate that the apparent hydrodynamic diameter of C(n)peLac micelles decreases sharply with increasing concentration, whereas that of 2C(n)peLac micelles decreases gradually. From the TRFQ measurement, it was observed that, as concentration increases, the aggregation numbers are almost constant for C(n)peLac, whereas they increase for 2C(n)peLac. These results imply that loosely packed micelles formed by sugar-based surfactants become tightly packed micelles as the concentration increases. Furthermore, it was found that 2C(n)peLac shows lower biodegradability than does C(n)peLac because it contains tertiary amines in the molecule.