Discovery of early-stage biomarkers for diabetic kidney disease using ms-based metabolomics (FinnDiane study)

Diabetic kidney disease (DKD) is a devastating complication that affects an estimated third of patients with type 1 diabetes mellitus (DM). There is no cure once the disease is diagnosed, but early treatment at a sub-clinical stage can prevent or at least halt the progression. DKD is clinically diagnosed as abnormally high urinary albumin excretion rate (AER). We hypothesize that subtle changes in the urine metabolome precede the clinically significant rise in AER. To test this, 52 type 1 diabetic patients were recruited by the FinnDiane study that had normal AER (normoalbuminuric). After an average of 5.5 years of follow-up half of the subjects (26) progressed from normal AER to microalbuminuria or DKD (macroalbuminuria), the other half remained normoalbuminuric. The objective of this study is to discover urinary biomarkers that differentiate the progressive form of albuminuria from non-progressive form of albuminuria in humans. Metabolite profiles of baseline 24 h urine samples were obtained by gas chromatography–mass spectrometry (GC–MS) and liquid chromatography–mass spectrometry (LC–MS) to detect potential early indicators of pathological changes. Multivariate logistic regression modeling of the metabolomics data resulted in a profile of metabolites that separated those patients that progressed from normoalbuminuric AER to microalbuminuric AER from those patients that maintained normoalbuminuric AER with an accuracy of 75% and a precision of 73%. As this data and samples are from an actual patient population and as such, gathered within a less controlled environment it is striking to see that within this profile a number of metabolites (identified as early indicators) have been associated with DKD already in literature, but also that new candidate biomarkers were found. The discriminating metabolites included acyl-carnitines, acyl-glycines and metabolites related to tryptophan metabolism. We found candidate biomarkers that were univariately significant different. This study demonstrates the potential of multivariate data analysis and metabolomics in the field of diabetic complications, and suggests several metabolic pathways relevant for further biological studies

Philosophical racism and ubuntu: In dialogue with Mogobe Ramose

This article discusses two complementary themes that play an important role in contemporary South African political philosophy: (1) the racist tradition in Western philosophy; and (2) the role of ubuntu in regaining an authentic African identity, which was systematically suppressed during the colonial past and apartheid. These are also leading themes in Mogobe Ramose’s African Philosophy Through Ubuntu. The first part concentrates on John Locke. It discusses the thesis that the reprehensible racism of many founders of liberal political philosophy has lethally infected liberal theory

Matrix-Assisted Laser Desorption Ionization-Mass Spectrometry Signal Enhancement of Peptides after Selective Extraction with Polymeric Reverse Micelles

Extraction of peptides by reverse micelle-forming amphiphilic homopolymers and subsequent matrix-assisted laser desorption ionization-mass spectrometry (MALDI-S) detection of these peptides in the presence of these polymers can significantly enhance peptide ion signals. Here, the mechanism of this MALDI signal enhancement is investigated. We find that the signal enhancement is caused by coalescence of polymer-peptide conjugates into "hotspots" on the MALDI target. Hotspot formation is observed only on hydrophilic surfaces and not hydrophobic surfaces. With the use of an Anchorchip MALDI target, which contains very small hydrophilic spots surrounded by a larger hydrophobic area, we find that this hotspot formation can be further exploited for ultrasensitive MALDI-MS analyses of peptides and peptide mixtures. MALDI-MS signals can be enhanced by 3-5 orders of magnitude when peptides are extracted by the amphiphilic homopolymers and detected on the Anchorchip MALDI target. This signal enhancement combined with the extraction selectivity of these reverse micelle-forming homopolymers makes these materials promising tools for sensitive detection of peptides in complex mixtures