Drying-induced surface roughening of polymeric coating under periodic air blowing

We carried out numerical simulations of drying-induced surface roughening of a moving liquid layer under periodic air blowing conditions. Using spatially non-uniform Biot number profiles along the coating surface, the solutions of coupled diffusion/heat transfer equations reveal a periodic growth and relaxation in concentration gradients in the vicinity of the liquid–gas interface. The resultant interfacial stress variations promote particular asymmetric surface topographies that grow and level in a sequential manner. The unique surface roughness is identified by considering time scales required for the web motion, the stress-induced surface evolution, and the pressure-driven leveling. Predicted drying maps represent the surface roughening behavior as regions in parameter space. © 2009 American Institute of Chemical Engineers AIChE J, 200

Optimized reaction pair of the CysHis tag and Ni(II)-NTA probe for highly selective chemical labeling of membrane proteins

Chemical labeling of proteins with synthetic molecular probes offers the possibility to probe the functions of proteins of interest in living cells. However, the methods for covalently labeling targeted proteins using complementary peptide tag-probe pairs are still limited, irrespective of the versatility of such pairs in biological research. Herein, we report the new CysHis tag-Ni(II) probe pair for the specific covalent labeling of proteins. A broad-range evaluation of the reactivity profiles of the probe and the CysHis peptide tag afforded a tag-probe pair with an optimized and high labeling selectivity and reactivity. In particular, the labeling specificity of this pair was notably improved compared to the previously reported one. This pair was successfully utilized for the fluorescence imaging of membrane proteins on the surfaces of living cells, demonstrating its potential utility in biological research

Electron microscopic detection of single membrane proteins by a specific chemical labeling

Electron microscopy (EM) is a technology that enables visualization of single proteins at a nanometer resolution. However, current protein analysis by EM mainly relies on immunolabeling with gold-particle-conjugated antibodies, which is compromised by large size of antibody, precluding precise detection of protein location in biological samples. Here, we develop a specific chemical labeling method for EM detection of proteins at single-molecular level. Rational design of α-helical peptide tag and probe structure provided a complementary reaction pair that enabled specific cysteine conjugation of the tag. The developed chemical labeling with gold-nanoparticle-conjugated probe showed significantly higher labeling efficiency and detectability of high-density clusters of tag-fused G protein-coupled receptors in freeze-fracture replicas compared with immunogold labeling. Furthermore, in ultrathin sections, the spatial resolution of the chemical labeling was significantly higher than that of antibody-mediated labeling. These results demonstrate substantial advantages of the chemical labeling approach for single protein visualization by EM

His タグ/Ni(II)-NTA ペア間相互作用を利用した生細胞での標的タンパク室の共有結合ラベルとその機能解析

京都大学0048新制・課程博士博士(工学)甲第18303号工博第3895号新制||工||1598(附属図書館)31161京都大学大学院工学研究科合成・生物化学専攻(主査)教授 濵地 格, 教授 森 泰生, 教授 跡見 晴幸学位規則第4条第1項該当Doctor of Philosophy (Engineering)Kyoto UniversityDGA

A mathematical model for cancer risk and accumulation of mutations caused by replication errors and external factors.

Replication errors influence mutations, and thus, lifetime cancer risk can be explained by the number of stem-cell divisions. Additionally, mutagens also affect cancer risk, for instance, high-dose radiation exposure increases lifetime cancer risk. However, the influence of low-dose radiation exposure is still unclear because this influence, if any, is very slight. We can assess the minimal influence of the mutagen by virtually comparing the states with and without mutagen using a mathematical model. Here, we constructed a mathematical model to assess the influence of replication errors and mutagens on cancer risk. In our model, replication errors occur with a certain probability during cell division. Mutagens cause mutations at a constant rate. Cell division is arrested when the number of cells reaches the capacity of the cell pool. When the number of cells decreases because of cell death or other reasons, cells resume division. It was assumed that the mutations of cancer driver genes occur stochastically with each mutation and that cancer occurs when the number of cancer driver gene mutations exceeds a certain threshold. We approximated the number of mutations caused by errors and mutagens. Then, we examined whether cancer registry data on cancer risk can be explained only through replication errors. Although the risk of leukemia was not fitted to the model, the risks of esophageal, liver, thyroid, pancreatic, colon, breast, and prostate cancers were explained only by replication errors. Even if the risk was explained by replication errors, the estimated parameters did not always agree with previously reported values. For example, the estimated number of cancer driver genes in lung cancer was larger than the previously reported values. This discrepancy can be partly resolved by assuming the influence of mutagen. First, the influence of mutagens was analyzed using various parameters. The model predicted that the influence of mutagens will appear earlier, when the turnover rate of the tissue is higher and fewer mutations of cancer driver genes were necessary for carcinogenesis. Next, the parameters of lung cancer were re-estimated assuming the influence of mutagens. The estimated parameters were closer to the previously reported values. than when considering only replication errors. Although it may be useful to explain cancer risk by replication errors, it would be biologically more plausible to consider mutagens in cancers in which the effects of mutagens are apparent

Trimethyl-Substituted Carbamate as a Versatile Self-Immolative Linker for Fluorescence Detection of Enzyme Reactions

Self-immolative linker is a useful building block of molecular probes, with broad applications in the fields of enzyme activity analysis, stimuli-responsive material science, and drug delivery. This manuscript presents N-methyl dimethyl methyl (i.e., trimethyl) carbamate as a new class of self-immolative linker for the fluorescence detection of enzyme reactions. The trimethyl carbamate was shown to spontaneously undergo intramolecular cyclization upon formation of a carboxylate group, to liberate a fluorophore with the second time rapid reaction kinetics. Interestingly, the auto-cleavage reaction of trimethyl carbamate was also induced by the formation of hydroxyl and amino groups. Fluorescent probes with a trimethyl carbamate could be applicable for fluorescence monitoring of the enzyme reactions catalyzed by esterase, ketoreductase, and aminotransferase, and for fluorescence imaging of intracellular esterase activity in living cells, hence demonstrating the utility of this new class of self-immolative linker

Host-Guest System Based on Collagen-Like Triple-Helix Hybridization

International audienceA strategy inspired by tweezer receptors has been employed to develop a new host-guest system. The Hybridization into a collagen-like triple helix is the driving force for the recognition that occurs with high affinity and selectivity. Several systems have been screened to find the best host-guest pair and this strategy may be implemented for tag fused protein recongnition