Texture Analysis of the Retinal Nerve Fiber Layer in Fundus Images via Markov Random Fields

Abstract-This paper describes method for analysis of the texture created by retinal nerve fibers (RNF) via Markov Random Fields. The Causal Autoregressive Random (CAR) model is used to create a feature vector describing the changes in texture due to losses in RNF layer. It is shown that features based on CAR model can be used for discrimination between healthy and glaucomatous tissue using simple linear classifier. The classification error is slightly below 4% for the tested dataset

Magainin 2 and PGLa in bacterial membrane mimics III : membrane fusion and disruption

We previously speculated that the synergistically enhanced antimicrobial activity of Magainin 2 and PGLa is related to membrane adhesion, fusion, and further membrane remodelling. Here, we combined computer simulations with time-resolved in vitro fluorescence microscopy, cryogenic electron microscopy (cryo-EM), and small-angle X-ray scattering (SAXS) to interrogate such morphological and topological changes of vesicles at nanoscopic and microscopic length scales in real time. Coarse-grained simulations revealed the formation of an elongated and bent fusion zone between vesicles in the presence of equimolar peptide mixtures. Vesicle adhesion and fusion was observed to occur within few seconds by cryo-EM and corroborated by SAXS measurements. The latter experiments further indicated continued and time-extended structural remodelling also for individual peptides or chemically-linked peptide heterodimers, but with different kinetics. Fluorescence microscopy further captured peptide-dependent adhesion, fusion, and occasional bursting of giant unilamellar vesicles already few seconds after peptide addition. The synergistic interactions between the peptides shorten the time response of vesicles and enhance membrane fusogenic and disrupting properties of the equimolar mixture compared to the individual peptides

Spin-locking in low-frequency reaction yield detected magnetic resonance

The purported effects of weak magnetic fields on various biological systems from animal magnetoreception to human health have generated widespread interest and sparked much controversy in the past decade. To date the only well established mechanism by which the rates and yields of chemical reactions are known to be influenced by magnetic fields is the radical pair mechanism, based on the spin-dependent reactivity of radical pairs. A diagnostic test for the operation of the radical pair mechanism was proposed by Henbest et al. [J. Am. Chem. Soc., 2004, 126, 8102] based on the combined effects of weak static magnetic fields and radiofrequency oscillating fields in a reaction yield detected magnetic resonance experiment. Here we investigate the effects on radical pair reactions of applying relatively strong oscillating fields, both parallel and perpendicular to the static field. We demonstrate the importance of understanding the effect of the strength of the radiofrequency oscillating field; our experiments demonstrate that there is an optimal oscillating field strength above which the observed signal decreases in intensity and eventually inverts. We establish the correlation between the onset of this effect and the hyperfine structure of the radicals involved, and identify the existence of ‘overtone’ type features appearing at multiples of the expected resonance field positio