TUM-ParticleTyper: A detection and quantification tool for automated analysis of (Microplastic) particles and fibers.

TUM-ParticleTyper is a novel program for the automated detection, quantification and morphological characterization of fragments, including particles and fibers, in images from optical, fluorescence and electron microscopy (SEM). It can be used to automatically select targets for subsequent chemical analysis, e.g.

High-resolution mapping of injury-site dependent functional recovery in a single axon in zebrafish.

In non-mammalian vertebrates, some neurons can regenerate after spinal cord injury. One of these, the giant Mauthner (M-) neuron shows a uniquely direct link to a robust survival-critical escape behavior but appears to regenerate poorly. Here we use two-photon microscopy in parallel with behavioral assays in zebrafish to show that the M-axon can regenerate very rapidly and that the recovery of functionality lags by just days.

Oligosaccharide Chromatographic Techniques for Quantitation of Structural Process-Related Impurities in Heparin Resulting From 2-O Desulfation.

Heparin is a widely-used intravenous anticoagulant comprising a complex mixture of highly-sulfated linear polysaccharides of repeating sequences of uronic acids (either iduronic or glucuronic) 1->4 linked to D-glucosamine with specific sulfation patterns. Preparation of crude heparin from mammalian mucosa involves protease digestion with alcalase under basic conditions (pH ≥ 9) and high temperature (>50°C) and also oxidation. Under such conditions, side reactions including the ubiquitous 2-O desulfation occur on the heparin backbone yielding non-endogenous disaccharides within polysaccharide chains.

Raman microspectroscopic identification of microplastic particles in freshwater bivalves (Unio pictorum) exposed to sewage treatment plant effluents under different exposure scenarios.

We investigated the uptake of microplastic (MP, <5 mm) particles by using freshwater bivalves (Unio pictorum) as biological samplers in the environment. They were exposed either directly to the biologically purified sewage of a North Bavarian sewage treatment plant (STP) or placed in a small river up- and downstream of the wastewater discharge for 28 days and 6 months, respectively. A control group was maintained in a pond.

Topological cell clustering in the ATLAS calorimeters and its performance in LHC Run 1.

The reconstruction of the signal from hadrons and jets emerging from the proton-proton collisions at the Large Hadron Collider (LHC) and entering the ATLAS calorimeters is based on a three-dimensional topological clustering of individual calorimeter cell signals. The cluster formation follows cell signal-significance patterns generated by electromagnetic and hadronic showers. In this, the clustering algorithm implicitly performs a topological noise suppression by removing cells with insignificant signals which are not in close proximity to cells with significant signals.