Aqueous One-pot Synthesis of Glycopolymers by Glycosidase-catalyzed Glycomonomer Synthesis Using 4,6-Dimetoxy Triazinyl Glycoside Followed by Radical Polymerization

Glycopolymers have attracted increased attention as functional polymeric materials, and simple methods for synthesizing glycopolymers remain needed. This paper reports the aqueous one-pot and chemoenzymatic synthesis of four types of glycopolymers via two reactions: the β-galactosidase-catalyzed glycomonomer synthesis using 4,6-dimetoxy triazinyl β-D-galactopyranoside and hydroxy group-containing (meth)acrylamide and (meth)acrylate derivatives as the activated glycosyl donor substrate and as the glycomonomer precursors, respectively, followed by radical copolymerization of the resulting glycomonomer and excess glycomonomer precursor without isolating the glycomonomers. The resulting glycopolymers bearing galactose moieties exhibited specific and strong interactions with the lectin peanut agglutinin as glycoclusters.     

Dynamic Stabilization of DNA Assembly by Using Pyrrole-Imidazole Polyamide

We used N-methylpyrrole (Py)-N-methylimidazole-(Im) polyamide as an exogenous agent to modulate the formation of DNA assemblies at specific double-stranded sequences. The concept was demonstrated on the hybridization chain reaction that forms linear DNA. Through a series of melting curve analyses, we demonstrated that the binding of Py−Im polyamide positively influenced both the HCR initiation and elongation steps. In particular, Py−Im polyamide was found to drastically stabilize the DNA duplex such that its thermal stability approached that of an equivalent hairpin structure. Also, the polyamide served as an anchor between hairpin pairs in the HCR assembly, thus improving the originally weak interstrand stability. We hope that these proof-of-concept results can inspire future use of Py−Im polyamide as a molecular tool to modulate the formation of DNA assemblies.     

Principled analytic classifier for positive-unlabeled learning via weighted integral probability metric

Machine Learning - We consider the problem of learning a binary classifier from only positive and unlabeled observations (called PU learning). Recent studies in PU learning have shown superior...     

Systematic packaging design tools integrating functional and environmental consequences on product life cycle: Case studies on laundry detergent and milk

This study presents systematic packaging design tools integrating functional and environmental consequences on product life cycle. To design packaging for sustainability, the trade-offs between functional and environmental aspects of packaging throughout the product life cycle should be considered. However, it is difficult for packaging designers to understand the overall trade-offs because the extent of the design consequences on the entire life cycle of packaging and its contents is unclear. We developed two tools for packaging design: the Life Cycle Association Matrix (LCAM) and the Function Network Diagram (FND). The following three steps, based on literature reviews and interviews with industrial experts, were applied. Firstly, we listed the product functions and design variables related to the functions as the attributes allocated to the product life cycle. Secondly, the attributes were connected appropriately based on causal relationships. Lastly, we identified the factors to support decision making in the packaging design procedure. As a result, the LCAM depicts the design consequences on the life cycle, and the FND determines the stakeholders affected by the design consequences. Two case studies were demonstrated to analyze the trade-offs by using our tools. In the case studies, a liquid laundry detergent bottle and a milk carton were redesigned. The tools identified the design consequences and stakeholders affected by the redesign of the usability and protective function for the detergent and milk cases, respectively. The results showed the significance of understanding the design consequences on the product life cycle by integrating the functional and environmental aspects.     

Short communication: Temporal changes in the skin morphology of dairy cows during the periparturient period

Management of dairy cow productivity requires monitoring of their nutritional status by visual observation. It has been suggested that changes in hair coat appearance are among the indicators of nutritional state in dairy cows. Temporal changes in the skin morphology in cows, however, have not been reported. In this study, we examined the changes in the skin of dairy cows that occur during the peripartum period. Seven pluriparous cows were used. Skin samples were collected at 28 d before the due date and 28 d and 56 d after calving for morphological examination. Hair follicle width was 108.8 ± 5.9 µm (±SD) in the dry period, 95.5 ± 5.5 µm at 28 d after calving, and 104.2 ± 5.3 µm at 56 d postpartum. The percentages of anagen hair follicles during these 3 periods were 41.4 ± 3.4, 18.5 ± 3.4, and 32.3 ± 3.3%, respectively. The corresponding sebaceous gland sizes were 8,362.0 ± 707.6, 7,800.0 ± 831.4, and 9,186.8 ± 962.6 µm², respectively. Hair follicle width was positively correlated with percentage of anagen hair follicles. The thickness of epidermal and proliferation rate of epidermal cell were also correlated. However, the hair follicle width, sebaceous gland size and cell proliferation rate, and thickness and proliferation rate of epidermal cells did not show any marked changes.     

Quantitative Elemental Analysis of a Single Cell by Using Inductively Coupled Plasma-Mass Spectrometry in Fast Time-Resolved Analysis Mode

The elemental composition of a single yeast, green alga, or red blood cell (RBC) was precisely determined by using inductively coupled plasma-mass spectrometry (ICP-MS) operating in fast time-resolved analysis (TRA) mode. The technique is known as single-cell (SC)-ICP-MS. Phosphorus, sulfur, magnesium, zinc, and iron were detected in the three types of cell. The elemental composition of yeast and green alga obtained by SC-ICP-MS was consistent with results obtained from conventional ICP-MS measurements following acid digestion of the cells. Slight differences were found in the measured values between SC-ICP-MS and the conventional ICP-MS results for RBC. However, the SC-ICP-MS results for S and Fe in RBC were closer to the estimated values for these elements that were calculated from the level of hemoglobin in RBCs. The data suggest that SC-ICP-MS is suitable for the analysis of various cell types, namely, fungus, plant, and animal cells.     

On-off switching properties of one-dimensional photonic crystals consisting of azo-functionalized polymer liquid crystals having different methylene spacers and polyvinyl alcohol

In this paper, photoresponsive behavior of multi-bilayered films having precisely controlled layer thickness prepared by stacking an azo-functionalized polymer liquid crystal, PMAzXAc, and polyvinyl alcohol alternatively, PVA, is described. The multi-bilayered films were found to reflect a light of specific wavelength depending on the layer thickness and refractive index, and showed the reversible change in the reflection intensity by irradiation with visible and UV lights. The change in the reflection intensity was brought about by change in the molecular orientation of PMAzXAc between an out-of-plane orientation and a photo-induced isotropic state, and was strongly dependent on the number of methylene spacer of PMAzXAc linking the azobenzene side group with the acrylate polymer main chain. PMAz6Ac with hexa-methylene spacer showed the largest change in the reflection intensity, while smaller change in the reflection intensity was observed for PMAzXAc having shorter or longer methylene spacer than 6. The effect of the methylene spacers on the photochemical change in the molecular orientation of azobenzene chromophores in the multi-bilayered films will be discussed.     

Evaluation of the Anti-Proliferative Activity of Rare Aldohexoses against MOLT-4F and DU-145 Human Cancer Cell Line and Structure-Activity Relationship of D-Idose

D-Allose (D-All), a C-3 epimer of D-glucose (D-Glc), is a naturally rare monosaccharide, which shows anti-proliferative activity against several human cancer cell lines. Unlike conventional anticancer drugs, D-All targets glucose metabolism and is non-toxic to normal cells. Therefore, it has attracted attention as a unique “seed” compound for anticancer agents. However, the anti-proliferative activities of the other rare aldohexoses have not been examined yet. In this study, we evaluated the anti-proliferative activity of rare aldohexoses against human leukemia MOLT-4F and human prostate cancer DU-145 cell lines. We found that D-All and D-idose (D-Ido) at 5 mM inhibited cell proliferation of MOLT-4F cells by 46 % and 60 %, respectively. On the other hand, the rare aldohexoses at 5 mM did not show specific anti-proliferative activity against DU-145 cells. To explore the structure–activity relationship of D-Ido, we evaluated the anti-proliferative activity of D-sorbose (D-Sor), 6-deoxy-D-Ido, and L-xylose (L-Xyl) against MOLT-4F cells and found that D-Sor, 6-deoxy-D-Ido, and L-Xyl showed no inhibitory activity at 5 mM, suggesting that the aldose structure and the C-6 hydroxy group of D-Ido are important for its activity. Cellular glucose uptake assay and western blotting analysis of thioredoxin-interacting protein (TXNIP) expression suggested that the anti-proliferative activity of D-Ido is induced by inhibition of glucose uptake via TXNIP-independent pathway.     

Robot motion design using bunraku emotional expressions – focusing on Jo-Ha-Kyū in sounds and movements*

One of the UNESCO intangible cultural heritages Bunraku puppets can play one of the most beautiful puppet motions in the world. The Bunraku puppet motions can express emotions without the so-called ‘Uncanny Valley.’ We try to convert these emotional motions into robot affective motions so that robots can interact with human beings more comfortable. In so doing, in the present paper, we present a robot motion design framework using Bunraku affective motions that are based on the so-called ‘Jo-Ha-Kyū,’ and convert a few simple Bunraku motions into a robot motions using one of deep learning methods. Our primitive experiments show that Jo-Ha-Kyū can be incorporated into robot motion design smoothly, and some simple affective robot motions can be designed using our proposed framework.