Multiplex suspension array for human anti-carbohydrate antibody profiling

Glycan-binding antibodies form a significant subpopulation of both natural and acquired antibodies and play an important role in various immune processes. They are for example involved in innate immune responses, cancer, autoimmune diseases, and neurological disorders. In the present study, a microsphere-based flow-cytometric immunoassay (suspension array) was applied for multiplexed detection of glycan-binding antibodies in human serum. Several approaches for immobilization of glycoconjugates onto commercially available fluorescent microspheres were compared, and as the result, the design based on coupling of end-biotinylated glycopolymers has been selected. This method requires only minute amounts of glycans, similar to a printed glycan microarray. The resulting glyco-microspheres were used for detection of IgM and IgG antibodies directed against ABO blood group antigens. The possibility of multiplexing this assay was demonstrated with mixtures of microspheres modified with six different ABO related glycans. Multiplexed detection of anti-glycan IgM and IgG correlated well with singleplex assays (Pearson's correlation coefficient r = 0.95-0.99 for sera of different blood groups). The suspension array in singleplex format for A/B trisaccharide, H(di) and Le(x) microspheres corresponded well to the standard ELISA (r > 0.94). Therefore, the described method is promising for rapid, sensitive, and reproducible detection of anti-glycan antibodies in a multiplexed format.

Serum amino acid profiles and their alterations in colorectal cancer

Mass spectrometry-based serum metabolic profiling is a promising tool to analyse complex cancer associated metabolic alterations, which may broaden our pathophysiological understanding of the disease and may function as a source of new cancer-associated biomarkers. Highly standardized serum samples of patients suffering from colon cancer (n = 59) and controls (n = 58) were collected at the University Hospital Leipzig. We based our investigations on amino acid screening profiles using electrospray tandem-mass spectrometry. Metabolic profiles were evaluated using the Analyst 1.4.2 software. General, comparative and equivalence statistics were performed by R 2.12.2. 11 out of 26 serum amino acid concentrations were significantly different between colorectal cancer patients and healthy controls. We found a model including CEA, glycine, and tyrosine as best discriminating and superior to CEA alone with an AUROC of 0.878 (95% CI 0.815-0.941). Our serum metabolic profiling in colon cancer revealed multiple significant disease-associated alterations in the amino acid profile with promising diagnostic power. Further large-scale studies are necessary to elucidate the potential of our model also to discriminate between cancer and potential differential diagnoses. In conclusion, serum glycine and tyrosine in combination with CEA are superior to CEA for the discrimination between colorectal cancer patients and controls.

A framework for benchmarking of homogenisation algorithm performance on the global scale

The International Surface Temperature Initiative (ISTI) is striving towards substantively improving our ability to robustly understand historical land surface air temperature change at all scales. A key recently completed first step has been collating all available records into a comprehensive open access, traceable and version-controlled databank. The crucial next step is to maximise the value of the collated data through a robust international framework of benchmarking and assessment for product intercomparison and uncertainty estimation. We focus on uncertainties arising from the presence of inhomogeneities in monthly mean land surface temperature data and the varied methodological choices made by various groups in building homogeneous temperature products. The central facet of the benchmarking process is the creation of global-scale synthetic analogues to the real-world database where both the "true" series and inhomogeneities are known (a luxury the real-world data do not afford us). Hence, algorithmic strengths and weaknesses can be meaningfully quantified and conditional inferences made about the real-world climate system. Here we discuss the necessary framework for developing an international homogenisation benchmarking system on the global scale for monthly mean temperatures. The value of this framework is critically dependent upon the number of groups taking part and so we strongly advocate involvement in the benchmarking exercise from as many data analyst groups as possible to make the best use of this substantial effort.

Separation of small metabolites and lipids in spectra from biopsies by diffusion-weighted HR-MAS NMR: a feasibility study.

High Resolution Magic Angle Spinning (HR-MAS) NMR allows metabolic characterization of biopsies. HR-MAS spectra from tissues of most organs show strong lipid contributions that are overlapping metabolite regions, which hamper metabolite estimation. Metabolite quantification and analysis would benefit from a separation of lipids and small metabolites. Generally, a relaxation filter is used to reduce lipid contributions. However, the strong relaxation filter required to eliminate most of the lipids also reduces the signals for small metabolites. The aim of our study was therefore to investigate different diffusion editing techniques in order to employ diffusion differences for separating lipid and small metabolite contributions in the spectra from different organs for unbiased metabonomic analysis. Thus, 1D and 2D diffusion measurements were performed, and pure lipid spectra that were obtained at strong diffusion weighting (DW) were subtracted from those obtained at low DW, which include both small metabolites and lipids. This subtraction yielded almost lipid free small metabolite spectra from muscle tissue. Further improved separation was obtained by combining a 1D diffusion sequence with a T2-filter, with the subtraction method eliminating residual lipids from the spectra. Similar results obtained for biopsies of different organs suggest that this method is applicable in various tissue types. The elimination of lipids from HR-MAS spectra and the resulting less biased assessment of small metabolites have potential to remove ambiguities in the interpretation of metabonomic results. This is demonstrated in a reproducibility study on biopsies from human muscle.

Methods for preparing and counting biochemical varves

Four different preparation and counting methods for biochemical varves were compared in order to assess counting errors and to standardize these techniques. The properties of two embedding methods, namely the shock-freeze, freeze-dry and the water-acetone-epoxy-exchange method, are discussed. Varve counts were carried out on fresh sediment and on sediment thin-sections, on the latter by manual and by automated counting using image-analysis software. Counting on fresh sediment and using image-analysis generally underestimated the number of varves, especially in sections with inconspicuous varves. A comparison between multiple varve counts carried out by a single analyst and different analysts showed no significant differences in the mean varve counts.