Composite cryogel with immobilized concanavalin A for affinity chromatography of glycoproteins

Composite cryogels containing porous adsorbent particles were prepared under cryogelation conditions. The composites with immobilized concanavalin A (Con A) were used for capturing glycoproteins. Adsorbent particles were introduced into the structure in order to improve the capacity and to facilitate the handling of the particles. The monolithic composite cryogels were produced from suspensions of polyvinyl alcohol particles and porous adsorbent particles and cross‐linked under acidic conditions at sub‐zero temperature. The cryogels were epoxy activated and Con A was immobilized as an affinity ligand. Binding and elution of horseradish peroxidase (HRP) was studied in batch experiment and in a chromatographic setup. Increasing adsorbent concentration in composite cryogels will increase ligand density, which therefore enhances the amount of bound HRP from 0.98 till 2.9 (milligram enzyme per milliliter of gel) in the chromatographic system. The material was evaluated in 10 cycles for binding and elution of HRP.     

Towards a miniaturized non-radioactive electron emitter with proximity focusing

Most state of the art gas sensor systems based on atmospheric pressure ionization, such ion mobility spectrometers use radioactive beta-sources (e.g. ³H or ⁶³Ni) to provide free electrons with high kinetic energy to initiate a chemical gas phase ionization of the analytes to be detected. Here, we introduce a non-radioactive electron emitter which generates free electrons at atmospheric pressure. Therefore, electrons are generated in a vacuum by field emission and accelerated towards a 300 nm thin 1 mm² silicon nitride membrane separating the vacuum from atmospheric pressure. Electron currents of about a few hundred microamps can be reached. High energetic electrons of about 10 keV can easily penetrate the membrane without significant loss of kinetic energy. The concept of proximity focusing avoids complex electron lenses to focus the electron beam onto the membrane. The used field emitter tips are made of multi-walled carbon nanotubes. Another benefit of our system is that no insulated power supply operating at high voltage is needed, as necessary for thermo emitters. Here, we show a first prototype of a proximity focused electron gun with field emitting carbon nanotubes. The system is coupled to our drift tube ion mobility spectrometer for validation. Ion mobility spectra similar to those of a ³H ionization source were achieved.     

The electronic structure of Ge9[Si(SiMe3)3]3-: a superantiatom complex

We report on the electronic structure of Ge(9)[Si(SiMe(3))(3)](3)(-). Systematic density functional theory analysis of the electronic shell structure of the cluster and its derivatives reveals that the Ge(9)[Si(SiMe(3))(3)](3)(-) and its neutral counterpart have electronic shells that can be explained using the superatom model. The ligand-core interaction of these complexes is distinctly different from previously identified gold, gallium, and aluminium superatom complexes, indicating an electron-donating rather than electron-withdrawing ligand. We modify the electron-counting rule for this case and introduce a simple picture for superatom and superantiatom complexes. Discussions comparing shell models, Zintl clusters, the superhalogen Al(13) and superatom complexes to Ge(9)[Si(SiMe(3))(3)](3)(-) are presented.     

Morphological and tissue characterization of the medicinal fungus Hericium coralloides by a structural and molecular imaging platform

In this study the potential of new imaging techniques such as Magnetic Resonance Imaging (MRI), Matrix-Assisted Laser Desorption/Ionization (MALDI) profiling mass spectrometry ("MALDI Profiling") and Fourier Transform Infrared (FTIR) spectroscopic imaging was evaluated to study morphological and molecular patterns of the potential medicinal fungus Hericium coralloides. For interpretation, the MALDI profiling, FTIR imaging and MRI results were correlated with histological information gained from Scanning Electron Microscopy (SEM) and Light Microscopy (LM). Additionally we tested several evaluation processes and optimized the methodology for use of complex FTIR images to monitor molecular patterns. It is demonstrated that the combination of these spectroscopic methods enables to gain a more distinct picture concerning morphology and distribution of active ingredients. We were able to obtain high quality FTIR imaging and MALDI-profiling results and to distinguish different tissue types with their chemical ingredients. Beside this, we have created a 3-D reconstruction of a mature Hericium basidioma, based on the MRI dataset: analyses allowed, for the first time, a realistic approximation of the "evolutionary effectiveness" of this bizarrely formed basidioma type, concerning the investment of sterile tissue and its reproductive output (production of basidiospores).     

QSAR classification of metabolic activation of chemicals into covalently reactive species

Metabolic activation of chemicals into covalently reactive species might lead to toxicological consequences such as tissue necrosis, carcinogenicity, teratogenicity, or immune-mediated toxicities. Early prediction of this undesirable outcome can help in selecting candidates with increased chance of success, thus, reducing attrition at all stages of drug development. The ensemble modelling of mixed features was used for the development of a model to classify the metabolic activation of chemicals into covalently reactive species. The effects of the quality of base classifiers and performance measure for sorting were examined. An ensemble model of 13 naive Bayes classifiers was built from a diverse set of 1,479 compounds. The ensemble model was validated internally with five-fold cross validation and it has achieved sensitivity of 67.4% and specificity of 93.4% when tested on the training set. The final ensemble model was made available for public use.     

Characterization of Zn‐Containing Metal–Organic Frameworks by Solid‐State 67Zn NMR Spectroscopy and Computational Modeling

Metal–organic frameworks (MOFs) are an extremely important class of porous materials with many applications. The metal centers in many important MOFs are zinc cations. However, their Zn environments have not been characterized directly by ⁶⁷Zn solid‐state NMR (SSNMR) spectroscopy. This is because ⁶⁷Zn (I=5/2) is unreceptive with many unfavorable NMR characteristics, leading to very low sensitivity. In this work, we report, for the first time, a ⁶⁷Zn natural abundance SSNMR spectroscopic study of several representative zeolitic imidazolate frameworks (ZIFs) and MOFs at an ultrahigh magnetic field of 21.1 T. Our work demonstrates that ⁶⁷Zn magic‐angle spinning (MAS) NMR spectra are highly sensitive to the local Zn environment and can differentiate non‐equivalent Zn sites. The ⁶⁷Zn NMR parameters can be predicted by theoretical calculations. Through the study of MOF‐5 desolvation, we show that with the aid of computational modeling, ⁶⁷Zn NMR spectroscopy can provide valuable structural information on the MOF systems with structures that are not well described. Using ZIF‐8 as an example, we further demonstrate that ⁶⁷Zn NMR spectroscopy is highly sensitive to the guest molecules present inside the cavities. Our work also shows that a combination of ⁶⁷Zn NMR data and molecular dynamics simulation can reveal detailed information on the distribution and the dynamics of the guest species. The present work establishes ⁶⁷Zn SSNMR spectroscopy as a new tool complementary to X‐ray diffraction for solving outstanding structural problems and for determining the structures of many new MOFs yet to come.     

Energy Fluctuations Shape Free Energy of Nonspecific Biomolecular Interactions

Understanding design principles of biomolecular recognition is a key question of molecular biology. Yet the enormous complexity and diversity of biological molecules hamper the efforts to gain a predictive ability for the free energy of protein-protein, protein-DNA, and protein-RNA binding. Here, using a variant of the Derrida model, we predict that for a large class of biomolecular interactions, it is possible to accurately estimate the relative free energy of binding based on the fluctuation properties of their energy spectra, even if a finite number of the energy levels is known. We show that the free energy of the system possessing a wider binding energy spectrum is almost surely lower compared with the system possessing a narrower energy spectrum. Our predictions imply that low-affinity binding scores, usually wasted in protein-protein and protein-DNA docking algorithms, can be efficiently utilized to compute the free energy. Using the results of Rosetta docking simulations of protein-protein interactions from Andre et al. (Proc. Natl. Acad. Sci. USA 105:16148, 2008), we demonstrate the power of our predictions.     

A performance study of radio-opaque personal protective fabrics for the reduction of transmittance of gamma-rays and neutrons

Commercial radio-opaque combat (CRC) fabrics, for incorporation into personal protective equipment used by first responders and armed forces, are marketed as having the ability to provide a level of protection against specific types of radiation. For a CRC material, a standard combat uniform and a multi-layered chemical, biological, radiological, nuclear (CBRN) protective material, the present work examines chemical composition and radiation protection against gamma-rays and neutron fluxes. Significant reduction in gamma-ray transmittance occurs only for the CRC fabric (46–514 keV) with gamma-ray attenuation coefficients of 3.10 to <0.10 cm² g⁻¹. Reduction in neutron transmittance, for all three fabrics, could not be assessed with certainty as the measured transmittance was obscured by large statistical uncertainties.     

Dynamic pressure based prediction of spray cooling heat transfer coefficients

An important goal of spray cooling research is the ability to predict local heat transfer from the spray hydrodynamics. It is postulated that the local normal pressure exerted by the spray onto the heated surface can be used to obtain the local heat transfer coefficient. This hypothesis was tested using data obtained from hollow cone, full cone, and linear sprays at four nozzle pressures and three stand-off distances. A correlation between the pressure and heat transfer coefficient was determined from the data, then used to “predict” the heat transfer coefficient to verify the accuracy of the correlation. The area averaged heat transfer coefficient could be predicted within 25%, indicating that pressure can be used to predict the local heat transfer coefficient in the single-phase regime.