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Organisationseinheit der BAM
Sialic acid (SA) is a monosaccharide usually linked to the terminus of glycan chains on the cell surface. It plays a crucial role in many biological processes, and hypersialylation is a common feature in cancer. Lectins are widely used to analyze the cell surface expression of SA.
However, these protein molecules are usually expensive and easily denatured, which calls for the development of alternative glycan-specific receptors and cell imaging technologies. In this study, SA-imprinted fluorescent core-shell molecularly imprinted polymer particles (SA-MIPs) were employed to recognize SA on the cell surface of cancer cell lines. The SA-MIPs improved suspensibility and scattering properties compared with previously used core-shell SA-MIPs. Although SA-imprinting was performed using SA without preference for the alpha-2,3- and alpha-2,6-SA forms, we screened the cancer cell lines analyzed using the lectins Maackia Amurensis Lectin I (MAL I, alpha-2,3-SA) and Sambucus Nigra Lectin (SNA, alpha-2,6-SA). Our results show that the selected cancer cell lines in this study presented a varied binding behavior with the SA-MIPs. The binding pattern of the lectins was also demonstrated. Moreover, two different pentavalent SA conjugates were used to inhibit the binding of the SA-MIPs to breast, skin, and lung cancer cell lines, demonstrating the specificity of the SA-MIPs in both flow cytometry and confocal fluorescence microscopy. We concluded that the synthesized SA-MIPs might be a powerful future tool in the diagnostic analysis of various cancer cells.
A thin-layer reference material for surface and near-surface analytical methods was produced and certified. The surface density of the implanted Sb layer was determined by Rutherford backscattering spectrometry (RBS), instrumental neutron activation analysis (INAA), and inductively coupled plasma isotope dilution mass spectrometry (ICP-IDMS) equipped with a multi-collector. The isotopic abundances of Sb (121Sb and 123Sb) were determined by multi-collector ICP-MS and INAA. ICP-IDMS measurements are discussed in detail in this paper. All methods produced values traceable to the SI and are accompanied by a complete uncertainty budget. The homogeneity of the material was measured with RBS. From these measurements the standard uncertainty due to possible inhomogeneities was estimated to be less than 0.78% for fractions of the area increments down to 0.75 mm2 in size. Excellent agreement between the results of the three different methods was found. For the surface density of implanted Sb atoms the unweighted mean value of the means of four data sets is 4.8121016 cm-2 with an expanded uncertainty (coverage factor k=2) of 0.0921016 cm-2. For the isotope amount ratio R (121Sb/123Sb) the unweighted mean value of the means of two data sets is 1.435 with an expanded uncertainty (coverage factor k=2) of 0.006.
A layer of Sb atoms, implanted with an energy of 400 keV and a nominal dose of 5×1016 atoms/cm2 into a high purity silicon wafer, was certified for its areal density (atoms/cm2) using Rutherford backscattering spectrometry (RBS), instrumental neutron activation analysis (INAA) and inductively coupled plasma isotope dilution mass spectrometry (ICP-IDMS) and for its isotope ratio using INAA and ICP-IDMS. Excellent agreement between the results of the different independent methods was found. In the present work, the measurements of the homogeneity of the areal density of Sb, previously determined with RBS in spots having 1 mm diameter, are improved with synchrotron X-ray fluorescence analysis: Higher precision in even smaller sample spots allows to estimate a reduced inhomogeneity of the whole batch of samples of the order of only 0.4%. Thus the uncertainty of the certified value can further be reduced. Down to fractions of a chip with 0.3×0.4 mm2 area, the areal density is now certified as (4.81±0.06)×1016 Sb atoms/cm2, where the expanded uncertainty 0.06 (coverage factor k=2) corresponds to only 1.2%. The relative merits of the different analytical methods are discussed.
The adsorption of porphyrin derivatives on a Au(111) surface was studied by scanning tunneling microscopy and spectroscopy at low temperatures in combination with density functional theory calculations. Different molecular appearances were found and could be assigned to the presence of single gold adatoms bonded by a coordination bond underneath the molecular monolayer, causing a characteristic change of the electronic structure of the molecules. Moreover, this interpretation could be confirmed by manipulation experiments of individual molecules on and off a single gold atom. This study provides a detailed understanding of the role of metal adatoms in surface–molecule bonding and anchoring and of the appearance of single molecules, and it should prove relevant for the imaging of related molecule–metal systems.
This Report describes the certification of the reference material antimony implanted in Si/SiO2 intended to be used for calibration of surface and near surface analytical methods. It describes the preparation, homogeneity measurements and the analytical work performed for the certification of both Areal density of antimony Atoms (retained dose) and the isotope amount Ratio as well as giving considerations on the stability of the material.
Sialyl-Tn (STn or sialyl-Thomsen-nouveau) is a carbohydrate antigen expressed by more than 80% of human carcinomas. We here report a strategy for ratiometric STn detection and dual-color cancer cell labeling, particularly, by molecularly imprinted polymers (MIPs). Imprinting was based on spectroscopic studies of a urea-containing green-fluorescent monomer 1 and STn-Thr-Na (sodium salt of Neu5Acα2-6GalNAcα-O-Thr). A few-nanometer-thin green-fluorescent polymer shell, in which STn-Thr-Na was imprinted with 1, other comonomers, and a cross-linker, was synthesized from the surface of red-emissive carbon nanodot (R-CND)-doped silica nanoparticles, resulting in dual fluorescent STn-MIPs. Dual-color labeling of cancer cells was achieved since both red and green emissions were detected in two separate channels of the microscope and an improved accuracy was obtained in comparison with single-signal MIPs. The flow cytometric cell analysis showed that the binding of STn-MIPs was significantly higher (p < 0.001) than that of non-imprinted polymer (NIP) control particles within the same cell line, allowing to distinguish populations. Based on the modularity of the luminescent core–fluorescent MIP shell architecture, the concept can be transferred in a straightforward manner to other target analytes.
We present Jobflow, a domain-agnostic Python package for writing computational workflows tailored for high-throughput computing applications. With its simple decorator-based approach, functions and class methods can be transformed into compute jobs that can be stitched together into complex workflows. Jobflow fully supports dynamic workflows where the full acyclic graph of compute jobs is not known until runtime, such as compute jobs that launch
other jobs based on the results of previous steps in the workflow. The results of all Jobflow compute jobs can be easily stored in a variety of filesystem- and cloud-based databases without the data storage process being part of the underlying workflow logic itself. Jobflow has been intentionally designed to be fully independent of the choice of workflow manager used to dispatch the calculations on remote computing resources. At the time of writing, Jobflow
workflows can be executed either locally or across distributed compute environments via an adapter to the FireWorks package, and Jobflow fully supports the integration of additional workflow execution adapters in the future.
Jobflow is a free, open-source library for writing and executing workflows. Complex workflows can be defined using simple python functions and executed locally or on arbitrary computing resources using the FireWorks workflow manager.
Some features that distinguish jobflow are dynamic workflows, easy compositing and connecting of workflows, and the ability to store workflow outputs across multiple databases.