Reversible Aggregation of Chlorophyll Derivative Induced by Phase Transition of Lipid.

Controlling the supramolecular organization of pigment molecules will provide innovative materials that exhibit variable optical properties. In nature, photosynthetic systems employ chlorophyllous supramolecules in which each pigment molecule is suitably organized in proteins, and their properties are adequately optimized by changing the structures of the surrounding amino acid residues. Here, we report a strategy for varying the aggregation behavior of a chlorophyll derivative by using a phase-transition phenomenon of lipid bilayers. Methyl pyropheophorbide a (MPP) was employed as a chlorophyllous pigment in our artificial system, and synthetic phosphatidylcholines with saturated acyl chain(s) were also used. The MPP molecules successfully accumulated within the lipid bilayer of liposomes without changing the vesicular structure. When the lipid bilayer was in a gel form (under the phase-transition temperature, Tm), the embedded MPP aggregated to yield a dimeric form showing red-shifted absorption bands and circular dichroism signals. When the solutions of MPP-containing liposomes were heated to higher temperatures than their Tm, MPP disaggregated to monomeric form as the absorption spectrum changed into its original fashion in dichloromethane. The reversible thermochromic (dis)aggregation of the MPP molecules had good cyclability. Additional careful examination of the phase transition in the MPP-lipid co-assemblies clarified that the critical temperatures of the MPP (dis)aggregation were in good agreement with the phase-transition temperatures of the pigment-containing bilayers. The reversible MPP aggregation in the lipid bilayers occurred in a wide range of temperatures (around 10-55 °C) by changing the length of the diacyl side chains of phospholipids. The reversible thermochromism of the chlorophyllous system was established by varying the nature of the surrounding lipid bilayer. This study can provide a useful strategy for making variable tetrapyrrolic aggregate systems induced by mild extrinsic stimuli.

[Survey of Radioactive Cesium and Potassium Intake from Food Using Duplicate Diet (Fiscal Years 2011-2014)].

Dietary intake of radioactive substances ((134)Cs, (137)Cs, (40)K) from food in fiscal 2011--2014 was surveyed using the duplicate diet method. 1,612 diet samples were collected from general households of 18 prefectures. (134)Cs and (137)Cs were detected in samples from Fukushima Prefecture, Miyagi Prefecture and Tokyo Prefecture. (134)Cs and (137)Cs were detected in 11 samples in fiscal 2011, 12 samples in fiscal 2012, and 7 samples in fiscal 2013, but none was detected in fiscal 2014. The largest radioactivity in a sample was 12 Bq/kg in Fukushima Prefecture in fiscal 2011. The detected levels gradually decreased and were less than 1.0 Bq/kg in fiscal 2014. The maximum estimated dose of radioactive cecium was 0.14 mSv/year in fiscal 2011. Radioactive potassium was detected in every meal, and showed little change through the four years (median around 30 Bq/kg).

An analysis of thyroid function diagnosis using Bayesian-type and SOM-type neural networks.

Thyroid function diagnosis is an important classification problem, and we made reanalysis of the human thyroid data, which had been analyzed by the multivariate analysis, by the two notable neural networks. One is the self-organizing map approach which clusters the patients and displays visually a characteristic of the distribution according to laboratory tests. We found that self-organizing map (SOM) consists of three well separated clusters corresponding to hyperthyroid, hypothyroid and normal, and more detailed information for patients is obtained from the position in the map. Besides, the missing value SOM which we had introduced to investigate QSAR problem turned out to be also useful in treating such classification problem. We estimated the classification rates of thyroid disease using Bayesian regularized neural network (BRNN) and found that its prediction accuracy is better than multivariate analysis. Automatic relevance determination (ARD) method of BRNN was surely verified to be effective by the direct calculation of classification rates using BRNN without ARD for all possible combinations of laboratory tests.