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Baczynska, E.

Publications and source records attributed to Baczynska, E..

2 recordsLinked to original sources

The molecular fingerprint of stress resilience

Stress resilience is the ability of neuronal networks to maintain their function despite the stress exposure. Using a mouse model we here investigate stress resilience phenomenon. To assess the resilient and anhedonic behavioral phenotypes developed after the induction of chronic unpredictable stress, we quantitatively characterized the structural and functional plasticity of excitatory synapses in the hippocampus using a combination of proteomic, electrophysiological, and imaging methods. Our results indicate that stress resilience is an active and multifactorial process manifested by structural, functional, and molecular changes in synapses. We reveal that chronic stress influences palmitoylation of synaptic proteins, whose profiles differ between resilient and anhedonic animals. The changes in palmitoylation are predominantly related with the glutamate receptor signaling thus affects synaptic transmission and associated structures of dendritic spines. We show that stress resilience is associated with structural compensatory plasticity of the postsynaptic parts of synapses in CA1 subfield of the hippocampus. One Sentence SummaryCompensatory remodeling of dendritic spines at the structural and molecular levels underlies stress resilience.

neuroscience↗

3dSpAn: an interactive software for 3D segmentation and analysis of dendritic spines

Three dimensional segmentation and analysis of dendritic spines involve two major challenges: 1) how to segment individual spines from the dendrites and 2) how to quantitatively assess the morphology of individual spines. We developed a software named 3dSpAn to address these two issues by implementing our previously published 3D multiscale opening algorithm in shared intensity space and using effective morphological features for individual dendritic spine plasticity analysis. 3dSpAn consists of four modules: Preprocessing and ROI selection, Intensity thresholding and seed selection, Multiscale segmentation and Quantitative morphological feature extraction. We show the results of segmentation and morphological analysis for different observation methods, including in vitro and ex vivo imaging with confocal microscopy, and in vivo samples, using high-resolution two-photon microscopy. The software is freely available, the source code, windows installer, the software manual and video tutorial can be obtained from: https://sites.google.com/view/3dSpAn/.

neuroscience↗