Introduction of macarpine as a novel cell‐permeant DNA dye for live cell imaging and flow cytometry sorting

[Background Information] Macarpine (MA) is a quaternary benzophenanthridine plant alkaloid isolated from Macleaya microcarpa or Stylophorum lasiocarpum. Benzophenanthridine alkaloids are interesting natural products that display antiproliferative, antimicrobial, antifungal and anti‐inflammatory activities, and also fluorescence properties. In a previous study, we demonstrated that thanks to its ability to interact with DNA and its spectral properties MA could be used as a supravital DNA probe for fluorescence microscopy and flow cytometry including analyses of the cell cycle. In this study, we evaluated the suitability of MA as a DNA dye for time‐lapse microscopy and flow‐cytometric cell sorting.[Results] Living A‐375 and MEF cells stained with MA were monitored by time‐lapse microscopy for 24 h. Mitoses were observed at MA concentrations up to 0.5 μg/ml during the first 2–3 h. After this period of time, cells treated with MA at concentrations of 0.75 and 0.5 μg/ml underwent apoptosis. Cells cultivated with MA at concentration of 0.25 μg/ml or lower survived throughout the 24 h period. Toxicity of MA was dependent on light wavelength and frequency of image capturing. The intensity of MA fluorescence decreased during the incubation. MA concentration of 0.1 μg/ml was identified as the most suitable for live cell imaging with respect to fluorescence intensity and toxicity. MA at the concentration 10 μg/ml was used for sorting of enhanced green fluorescent protein (EGFP)‐labelled neurons and fibroblasts yielding profiles similar to those obtained with DRAQ5. Contrary to DRAQ5, MA‐stained cells survived in culture, and the sorted cells lost the MA signal suggesting reversible binding of the dye to the DNA.[Conclusion] The results proved that MA may readily be used for chromosomes depicting and mitosis monitoring by time‐lapse microscopy. In addition, MA has shown to be a suitable probe for sorting of EGFP‐labelled cells, including neurons, that survived the labelling process.[Significance] In consideration of the results, we highly anticipate an onward use of MA in a broad range of applications based on live cell sorting and imaging, for example, cell synchronisation and monitoring of proliferation as an important experimental and/or diagnostic utility.This work was supported by Ministry of Education, Youth and Sports of the Czech Republic [KONTAKT II LH12176, MUNI/A/1123/2014 and MUNI/A/1195/2014], Ministerio de Economía y Competitividad [SAF2012‐38316] and Fundación Ramón Areces [CIVP16A1815].Peer reviewe

Regional gray matter changes and age predict individual treatment response in Parkinson's disease

We aimed at testing the potential of biomarkers in predicting individual patient response to dopaminergic therapy for Parkinson's disease. Treatment efficacy was assessed in 30 Parkinson's disease patients as motor symptoms improvement from unmedicated to medicated state as assessed by the Unified Parkinson's Disease Rating Scale score III. Patients were stratified into weak and strong responders according to the individual treatment response. A multiple regression was implemented to test the prediction accuracy of age, disease duration and treatment dose and length. Univariate voxel-based morphometry was applied to investigate differences between the two groups on age-corrected T1-weighted magnetic resonance images. Multivariate support vector machine classification was used to predict individual treatment response based on neuroimaging data. Among clinical data, increasing age predicted a weaker treatment response. Additionally, weak responders presented greater brain atrophy in the left temporoparietal operculum. Support vector machine classification revealed that gray matter density in this brain region, including additionally the supplementary and primary motor areas and the cerebellum, was able to differentiate weak and strong responders with 74% accuracy. Remarkably, age and regional gray matter density of the left temporoparietal operculum predicted both and independently treatment response as shown in a combined regression analysis. In conclusion, both increasing age and reduced gray matter density are valid and independent predictors of dopaminergic therapy response in Parkinson's disease. Keywords: Parkinson's disease, Dopaminergic therapy, Voxel-based morphometry, Support vector machine classification, Predictive model