NKG2C+ NK Cells for Immunotherapy of Glioblastoma Multiforme

In glioblastoma, non-classical human leucocyte antigen E (HLA-E) and HLA-G are frequently overexpressed. HLA-E loaded with peptides derived from HLA class I and from HLA-G contributes to inhibition of natural killer (NK) cells with expression of the inhibitory receptor CD94/NKG2A. We investigated whether NK cells expressing the activating CD94/NKG2C receptor counterpart were able to exert anti-glioma effects. NKG2C+ subsets were preferentially expanded by a feeder cell line engineered to express an artificial disulfide-stabilized trimeric HLA-E ligand (HLA-E*spG). NK cells expanded by a feeder cell line, which facilitates outgrowth of conventional NKG2A+, and fresh NK cells, were included for comparison. Expansion via the HLA-E*spG feeder cells selectively increased the fraction of NKG2C+ NK cells, which displayed a higher frequency of KIR2DL2/L3/S2 and CD16 when compared to expanded NKG2A+ NK cells. NKG2C+ NK cells exhibited increased cytotoxicity against K562 and KIR:HLA-matched and -mismatched primary glioblastoma multiforme (GBM) cells when compared to NKG2A+ NK cells and corresponding fresh NK cells. Cytotoxic responses of NKG2C+ NK cells were even more pronounced when utilizing target cells engineered with HLA-E*spG. These findings support the notion that NKG2C+ NK cells have potential therapeutic value for treating gliomas.     

Sonochemical Activation of Al/Ni Hydrogenation Catalyst

This paper proposes a sonochemical approach to the nanostructuring of Al/Ni catalyst with high content of accessible Ni centers and a high reusability. The surface and bulk composition as well as pore size distribution of this catalyst are controlled synergistically by adjusting the ultrasound intensity in aqueous solution. Sonochemical activation of Al/Ni alloy leads to formation of mesoporous Al/Ni metallic based frameworks with surface area up to 125 m² g^?1, and regular distribution of nickel active center in the porous matrix. One of the opportunities of porous Al/Ni catalyst is that due to a time‐resolved controllable formation of protective oxide layer it can be stored and handled under air in comparison to traditional Raney catalysts which need inert conditions. The Al/Ni catalyst is characterized by scanning electron microscopy (SEM), electron diffraction spectroscopy (EDS), X‐ray photoelectron spectroscopy (XPS), confocal scanning fluorescence microscopy (CSFM), solid‐state NMR experiments, and powder X‐ray diffraction analysis (PXRD). The catalytic activity was investigated for the hydrogenation of acetophenone.     

Accuracy analysis of a covariance matching approach for identifying errors-in-variables systems

A system identification method for errors-in-variables problems based on covariance matching was recently proposed. In the first step, a small amount of covariances of noisy input–output data are computed, and then a parametric model is fitted to these covariances. In this paper, the method is further analyzed and the asymptotic accuracy of the parameter estimates is derived. An explicit algorithm for computing the asymptotic covariance matrix of the parameter estimates is given, and the identification method is shown to be asymptotically statistically efficient assuming that the given information is the computed covariances. As an important byproduct, an efficient algorithm is presented for computing the covariance matrix of the computed input–output covariances.     

Seminar zum systematischen Erfinden

SciencenewsTriz*-Check up

Seminar zum systematischen Erfinden     

Image similarity and tissue overlaps as surrogates for image registration accuracy: widely used but unreliable

The accuracy of nonrigid image registrations is commonly approximated using surrogate measures such as tissue label overlap scores, image similarity, image difference, or transformation inverse consistency error. This paper provides experimental evidence that these measures, even when used in combination, cannot distinguish accurate from inaccurate registrations. To this end, we introduce a "registration" algorithm that generates highly inaccurate image transformations, yet performs extremely well in terms of the surrogate measures. Of the tested criteria, only overlap scores of localized anatomical regions reliably distinguish reasonable from inaccurate registrations, whereas image similarity and tissue overlap do not. We conclude that tissue overlap and image similarity, whether used alone or together, do not provide valid evidence for accurate registrations and should thus not be reported or accepted as such.     

Comparison and validation of tissue modelization and statistical classification methods in T1-weighted MR brain images

This paper presents a validation study on statistical nonsupervised brain tissue classification techniques in magnetic resonance (MR) images. Several image models assuming different hypotheses regarding the intensity distribution model, the spatial model and the number of classes are assessed. The methods are tested on simulated data for which the classification ground truth is known. Different noise and intensity nonuniformities are added to simulate real imaging conditions. No enhancement of the image quality is considered either before or during the classification process. This way, the accuracy of the methods and their robustness against image artifacts are tested. Classification is also performed on real data where a quantitative validation compares the methods' results with an estimated ground truth from manual segmentations by experts. Validity of the various classification methods in the labeling of the image as well as in the tissue volume is estimated with different local and global measures. Results demonstrate that methods relying on both intensity and spatial information are more robust to noise and field inhomogeneities. We also demonstrate that partial volume is not perfectly modeled, even though methods that account for mixture classes outperform methods that only consider pure Gaussian classes. Finally, we show that simulated data results can also be extended to real data.     

Fabrication of CdSe‐Nanofibers with Potential for Biomedical Applications

The design and synthesis of nanostructured functional hybrid biomaterials are essential for the next generation of advanced diagnostics and the treatment of disease. A simple route to fabricate semiconductor nanofibers by self‐assembled, elastin‐like polymer (ELP)‐templated semiconductor nanoparticles is reported. Core–shell nanostructures of CdSe nanoparticles with a shell of ELPs are used as building blocks to fabricate functional one‐dimensional (1D) nanostructures. The CdSe particles are generated in situ within the ELP matrix at room temperature. The ELP controls the size and the size‐distribution of the CdSe nanoparticles in an aqueous medium and simultaneously directs the self‐assembly of core–shell building blocks into fibril architectures. It was found that the self‐assembly of core–shell building blocks into nanofibers is strongly dependent on the pH value of the medium. Results of cytotoxicity and antiproliferation of the CdSe‐ELP nanofibers demonstrate that the CdSe‐ELP does not exhibit any toxicity towards B14 cells. Moreover, these are found to be markedly capable of crossing the cell membrane of B14. In contrast, unmodified CdSe nanoparticles with ELPs cause a strong toxic response and reduction in the cell proliferation. This concept is valid for the fabrication of a variety of metallic and semiconductor 1D‐architectures. Therefore, it is believed that these could be used not only for biomedical purposes but for application in a wide range of advanced miniaturized devices.