Fast Epitope Mapping for the Anti‐MUC1 Monoclonal Antibody by Combining a One‐Bead‐One‐Glycopeptide Library and a Microarray Platform

Anti‐MUC1 monoclonal antibodies (mAbs) are powerful tools that can be used to recognize cancer‐related MUC1 molecules, the O‐glycosylation status of which is believed to affect binding affinity. We demonstrate the feasibility of using a rapid screening methodology to elucidate those effects. The approach involves i) “one‐bead‐one‐compound”‐based preparation of bilayer resins carrying glycopeptides on the shell and mass‐tag tripeptides coding O‐glycan patterns in the core, ii) on‐resin screening with an anti‐MUC1 mAb, iii) separating positive resins by utilizing secondary antibody conjugation with magnetic beads, and (iv) decoding the mass‐tag that is detached from the positive resins pool by using mass spectrometric analysis. We tested a small library consisting of 27 MUC1 glycopeptides with different O‐glycosylations against anti‐MUC1 mAb clone VU‐3C6. Qualitative mass‐tag analysis showed that increasing the number of glycans leads to an increase in the binding affinity. Six glycopeptides selected from the library were validated by using a microarray‐based assay. Our screening provides valuable information on O‐glycosylations of epitopes leading to high affinity with mAb.     

Estimation of diffusion and permeability coefficients of CO2 in polymeric membranes by FTIR method

Infrared spectra of CO₂ sorbed in rubbery and glassy polymeric membranes were measured to examine the relationships between the spectroscopic data and the physical properties of the membranes. The two peaks observed in the spectra of CO₂ were attributed to the R branch and P branch of CO₂ sorbed in the membranes based on the consideration that both peaks were observed at a temperature above the glass transition temperature of the membranes. Apparent diffusion coefficients of CO₂ in the membranes were measured from the desorption kinetics of CO₂ detected by FTIR spectroscopy. The solubility coefficients of CO₂ were also estimated from absorbance spectra of CO₂ sorbed in the membranes using Lambert-Beer's rule. The permeability, solubility, and diffusion coefficients estimated by the FTIR method were found to correlate well with the coefficients obtained by conventional methods such as vacuum-pressure or sorption isotherm methods. © 1996 John Wiley & Sons, Inc.     

Novel gas chromatography-mass spectrometry database for automatic identification and quantification of micropollutants

A novel gas chromatography-mass spectroscopy (GC-MS) database for identification and quantification of micropollutants in environmental and food samples is reported. GC retention times, calibration curves, and mass spectra of nearly 700 chemicals were registered in the database, and the GC retention times of registered chemicals in actual samples were predicted from the retention times of n-alkanes measured before sample analysis. Differences between predicted and actual retention times were less than 3 s, an accuracy that is nearly identical to that obtained by analysis of standard substances. After the retention times were predicted, a calibration file for the GC-MS instrument was created from the predicted retention times, calibration curves, and mass spectra of the registered chemicals. With the resulting calibration file, automated identification of all the chemicals in actual samples was possible without the use of standards, and the identification method was as reliable as conventional methods. When the GC inlet, column, and tuning conditions were adjusted using GC-MS performance check standards, relative standard deviations of 20% or less for determination values could be obtained. More than 90% of the chemicals in the database could be detected at a sensitivity sufficient for all practical purposes (100 pg or less). Because each chemical in the database, to which new substances can easily be added, can be determined in 1 h, micropollutants in samples can be analyzed efficiently and inexpensively.     

Simple separation of isomeric sialylated N-glycopeptides by a zwitterionic type of hydrophilic interaction chromatography

Asparagine-linked oligosaccharides (N-glycans) usually show structural heterogeneity, especially in proteins with sialylated N-glycans and, therefore, their structural analysis is still very difficult. A zwitterionic type of hydrophilic interaction chromatography column with sulfobetaine functional groups (called a ZIC-HILIC column) was applied to the separation of tryptic peptides of alpha-1-acid glycoprotein. It was demonstrated that the ZIC-HILIC separation column has a selectivity for sialylated N-glycopeptides and a high capability for separation based on the structural recognition of sialylated N-glycan isomers as well as for the previously reported neutral N-glycans and N-glycopeptides. The retention characteristics of neutral and sialylated N-glycans derivatized with 2-aminopyridine (PA N-glycans) demonstrate that the retentions of the N-glycans are based primarily on hydrophilic interaction with the water-rich liquid layer generated on the surface of the ZIC-HILIC column. In addition, the electrostatic repulsion interaction shielded with counter ions effectively tunes the separation and recognition of sialylated N-glycan isomers.     

三甲基硅烷基丙炔与五甲基二硅烷基丙炔共聚物膜及其气体透过性

研究了三甲基硅烷基丙块与五甲基二硅烷基丙块共聚物〔poly(TMSP-co-PMDSP)〕的成膜特点。poly(TMSP-co-PMDSP)膜的气体透过系数分别为:P_(O2):4×10~3～12×10~3,P_(N2):3×10~3～8×10~3和P_(CO2):2×10~4～4×10~4barrer,气体透过稳定性低,透过行为偏离第二Fick定律,过系数下降,其中溶解系数降低的比例远大于扩散系数的增加比例,在含有凝聚性气体的环境里,膜的气体透过出现表面吸附控制的特征。     

Two-dimensional hydrophilic interaction chromatography coupling anion-exchange and hydrophilic interaction columns for separation of 2-pyridylamino derivatives of neutral and sialylated N-glycans

A novel chromatographic approach coupling anion-exchange (diethylaminoethylene) and hydrophilic-interaction (amide or zwitterionic type) columns was developed for the separating of 2-pyridylamino derivatives of N-glycans (PA-N-glycans). This is a kind of on-line, two-dimensional (2D) separation approach in hydrophilic-interaction chromatography (called the 2D-HILIC method), analogous to that of coupling cation- (or anion-, or mixed ion-) exchange and reversed-phase columns in hydrophobic interaction (reversed-phase) chromatography. The efficiency of the 2D-HILIC method was tested with biantennary neutral and sialylated PA-N-glycan standards by properly combining linear gradient elutions of water-acetonitrile and spiked-salt (ammonium acetate) elutions. The retention time RSDs of all the peaks in three sequential runs of a 100 min cycle are less than 0.52%, which indicates a reasonably good repeatability of the 2D-HILIC method. Then, the method was applied to a complex mixture of PA-N-glycans from human serum proteins. It was demonstrated that the neutral PA-N-glycans and mono-, di-, tri-, and tetrasialylated PA-N-glycans are able to be eluted in turn according to the number of sialic acids in an automated (programmed) single run.     

Fe K‐Edge X‐ray Absorption Fine Structure Determination of γ‐Al2O3‐Supported Iron‐Oxide Species

The structure of FeO_x species supported on γ‐Al₂O₃ was investigated by using Fe K‐edge X‐ray absorption fine structure (XAFS) and X‐ray diffraction (XRD) measurements. The samples were prepared through the impregnation of iron nitrate on Al₂O₃ and co‐gelation of aluminum and iron sulfates. The dependence of the XRD patterns on Fe loading revealed the formation of α‐Fe₂O₃ particles at an Fe loading of above 10 wt %, whereas the formation of iron‐oxide crystals was not observed at Fe loadings of less than 9.0 wt %. The Fe K‐edge XAFS was characterized by a clear pre‐edge peak, which indicated that the Fe?O coordination structure deviates from central symmetry and that the degree of Fe?O?Fe bond formation is significantly lower than that in bulk samples at low Fe loading (<9.0 wt %). Fe K‐edge extended XAFS oscillations of the samples with low Fe loadings were explained by assuming an isolated iron‐oxide monomer on the γ‐Al₂O₃ surface.     

Raman and infrared spectra of the all-trans, 7-cis, 9-cis, 13-cis and 15-cis isomers of β-carotene: Key bands distinguishing stretched or terminal-bent configurations form central-bent configurations

Raman and infrared spectra in the region of 1800-150 cm⁻¹ were recorded for a set of cis-trans isomers of d̃-carotene, i.e. the all-trans, 7-cis, 9-cis, 13-cis and 15-cis isomers. Spectral comparison revealed Raman and infrared key bands which (1) distinguish stretched or terminal-bent configurations (all-trans, 7-cis and 9-cis) from central-bent configurations (13-cis and 15-cis), and (2) distinguish unmethylated 7-cis and 15-cis configuratios. Keybands (1) include Raman bands at 1160 and 1140 cm⁻¹ and infrared bands at 825 and 775 cm⁻¹ (the intensity varies with the position of the cis-bend) Key bands (2) include Raman bands at 1274 and 962 cm⁻¹ and an infrared band at 741 cm⁻¹ (characteristic of the 7-cis configuration), and also a Raman band at 1247 cm⁻¹ and an infrared band at 775 cm⁻¹ (characteristic of the 15-cis configuration). The normal modes for the key bands were determined by a set of normal coordinate calculations for the isomeric configurations of a simplified model of d̃-carotene. The key bands were mainly related to the C H in-plane bendings, coupled with the CC or C C stretching, or to the C H out-of-plane wagging vibrations, some of which coupled with the CC torsion.     

On the Nature of Functional Differentiation: The Role of Self-Organization with Constraints

The focus of this article is the self-organization of neural systems under constraints. In 2016, we proposed a theory for self-organization with constraints to clarify the neural mechanism of functional differentiation. As a typical application of the theory, we developed evolutionary reservoir computers that exhibit functional differentiation of neurons. Regarding the self-organized structure of neural systems, Warren McCulloch described the neural networks of the brain as being “heterarchical”, rather than hierarchical, in structure. Unlike the fixed boundary conditions in conventional self-organization theory, where stationary phenomena are the target for study, the neural networks of the brain change their functional structure via synaptic learning and neural differentiation to exhibit specific functions, thereby adapting to nonstationary environmental changes. Thus, the neural network structure is altered dynamically among possible network structures. We refer to such changes as a dynamic heterarchy. Through the dynamic changes of the network structure under constraints, such as physical, chemical, and informational factors, which act on the whole system, neural systems realize functional differentiation or functional parcellation. Based on the computation results of our model for functional differentiation, we propose hypotheses on the neuronal mechanism of functional differentiation. Finally, using the Kolmogorov–Arnold–Sprecher superposition theorem, which can be realized by a layered deep neural network, we propose a possible scenario of functional (including cell) differentiation.