Efficient Expression and Purification of Fc-fragment-binding Domain and Its Application to Immunoglobulin G Purification

The number of therapeutic monoclonal antibodies used in clinical trials has recently increased dramatically, leading to the development of optimized downstream purification processes[1]. Staphylococcal protein A （SPA）, a cell-wall protein of Staphylococcus aureus, has been developed as a universal ligand for immunoglobulin G （IgG） purification because it binds specifically to the Fc portion of the IgG molecule of many mammals[2]. However, certain characteristics of SPA severely restrict the advancement of the antibody industry.

Guest Editorial TTA Special Section on Applications of Terahertz Time Domain Spectroscopy

Terahertz （THz） radiation, whose frequency ranges from 0.1 THz to 10.0 THz, has rich science, but limited technology. It has long been considered the last remaining scientific gap in the electromagnetic spectrum. Far from being fully exploited, it offers great opportunities in science, innovation, new technology, and potential applications. THz science and technology enables fundamental research directly impact our lives, from industrial quality control,

Inhibition of Microbial Growth by Anilines： A QSAR Study

The relative toxicity of 48 anilines using the Tetrahymena pyriformis population growth characteristics IGC50 （concentration causing 50% growth inhibition）, available in the literature, was studied. At first, the entire data set was randomly split into a training set （31 chemicals） used to establish the QSAR model, and a test set （17 chemicals） for statistical external validation. A biparametric model was developed using, as independent variables, 3D theoretical descriptors derived from DRAGON software. The GA-MLR （genetic algorithm variable subset selection） procedure was performed on the trainingset by the software mobydigs using the OLS （ordinary least squares） regression method, and GA（genetic algorithm）-VSS（variable subset selection） by maximising the cross-validated explained variance （Q^2Loo）＇ The obtained model was examined for robustness （Q^2LOOcross-validation, Y-scrambling） and predictive ability through both internal （Q^2LM0, bootstrap） and external validation （Q^2ext） methods. Descriptors included in the QSAR model indicated that log/GC^-150 value was related to molecular size and shape, and interaction of molecule with its surrounding medium or its target. Moreover, the applicability domain of the model was discussed.

Quantitative Structure-Activity Relationship Study of a Benzimidazole-Derived Series Inhibiting Mycobacterium tuberculosis H37Rv

This work was carried out on a series of twenty-two (22) benzimidazole derivatives with inhibitory activities against Mycobacterium tuberculosis H37Rv by applying the Quantitative Structure-Activity Relationship (QSAR) method. The molecules were optimized at the level DFT/B3LYP/6-31 + G (d, p), to obtain the molecular descriptors. We used three statistical learning tools namely, the linear multiple regression (LMR) method, the nonlinear regression (NLMR) and the artificial neural network (ANN) method. These methods allowed us to obtain three (3) quantitative models from the quantum descriptors that are, chemical potential (μ), polarizability (α), bond length l (C = N), and lipophilicity. These models showed good statistical performance. Among these, the ANN has a significantly better predictive ability R2 = 0.9995;RMSE = 0.0149;F = 31879.0548. The external validation tests verify all the criteria of Tropsha et al. and Roy et al. Also, the internal validation tests show that the model has a very satisfactory internal predictive character and can be considered as robust. Moreover, the applicability range of this model determined from the levers shows that a prediction of the pMIC of the new benzimidazole derivatives is acceptable when its lever value is lower than 1.

Application of matched filters in time-scale domain for elastography

Elasticity imaging offers the possibility of detecting changes in elastic properties and assesses the biomechanical properties of soft tissue with increased sensitivity and spatial resolution compared with conventional palpation. However, the range of applied strains is limited by the concomitant increase of echo signal decorrelation, The decorrelation is mainly introduced by diffuse scattering, while the regular scattering is highly correlated. Because the regular scattering and diffuse scattering localize with different patterns in different ranges of time-scale plane, a new method is put forward to detect the regular scattering with matched filters based on wavelet transform using Generalized Likelihood Aatio Test (GLRT). The simulation results illustrate that the change in estimated mean interscatterer spacing introduced by a SNR of -10 dB is 1.1±2.8%. Thus, by tracking the highly correlated regular scattering, the internal strain can be estimated based on the change in interscatterer spacing under the condition of large surface deformation. The experiment studies show that the internal strain can be estimated up to 10% applied deformation in phantom and 5% strain in porcine liver.

Quantitative structure-activity relationship of compounds binding to estrogen receptor β based on heuristic method

Estrogen compounds may pose a serious threat to the health of humans and wildlife. The estrogen receptor （ER） exists as two subtypes, ERα and ERβ. Compounds might have different relative affinities and binding modes for ERα and ERβ. In this study, the heuristic method was performed on 31 compounds binding to ERβ to select 5 variances most related to the activity （LogRBA） from 1524 variances, which were then employed to develop the best model with the significant correlation and the best predictive power （γ^2 = 0.829, q^2LOO = 0.742, γ^2pred = 0.772, q^2ext = 0.724, RMSEE = 0.395） using multiple linear regression （MLR）. The model derived identified critical structural features related to the activity of binding to ERβ. The applicability domain （AD） of the model was assessed by Williams plot.