Wound healing assay performed with automated microscopy is widely used in drug testing, cancer cell analysis, and similar approaches. It is easy to perform, and the results are reproducible. However, it is usually used as a semi-quantitative approach because of inefficient image segmentation in transmitted light microscopy. Recently, several algorithms for wound healing quantification were suggested, but none of them was tested on a large dataset. In the current study, we develop a pipeline allowing to achieve correct segmentation of the wound edges in >95% of pictures and extended statistical data processing to eliminate errors of cell culture artifacts. Using this tool, we collected data on wound healing dynamics of 10 cell lines with 10 min time resolution. We determine that the overall kinetics of wound healing is non-linear; however, all cell lines demonstrate linear wound closure dynamics in a 6-h window between the fifth and 12th hours after scratching. We next analyzed microtubule-inhibiting drugs’, nocodazole, vinorelbine, and Taxol, action on the kinetics of wound healing in the drug concentration-dependent way. Within this time window, the measurements of velocity of the cell edge allow the detection of statistically significant data when changes did not exceed 10–15%. All cell lines show decrease in the wound healing velocity at millimolar concentrations of microtubule inhibitors. However, dose-dependent response was cell line specific and drug specific. Cell motility was completely inhibited (edge velocity decreased 100%), while in others, it decreased only slightly (not more than 50%). Nanomolar doses (10–100 nM) of microtubule inhibitors in some cases even elevated cell motility. We speculate that anti-microtubule drugs might have specific effects on cell motility not related to the inhibition of the dynamic instability of microtubules.

Macroporous scaffolds composed of chitosan (CHI), hydroxyapatite (HA), heparin (Hep), and polyvinyl alcohol (PVA) were prepared with a glutaraldehyde (GA) cross-linker by cryogelation. Addition of PVA to the reaction mixture slowed down the formation of a polyelectrolyte complex (PEC) between CHI and Hep, which allowed more thorough mixing, and resulted in the development of the homogeneous matrix structure. Freezing of the CHI-HA-GA and PVA-Hep-GA mixture led to the formation of a non-stoichiometric PEC between oppositely charged groups of CHI and Hep, which caused further efficient immobilization of bone morphogenic protein 2 (BMP-2) possible due to electrostatic interactions. It was shown that the obtained cryogel matrix released BMP-2 and supported the differentiation of rat bone marrow mesenchymal stem cells (rat BMSCs) into the osteogenic lineage. Rat BMSCs attached to cryogel loaded with BMP-2 and expressed osteocalcin in vitro. Obtained composite cryogel with PEC may have high potential for bone regeneration and tissue engineering applications.

The automated segmentation of cells in microscopic images is an open research problem that has important implications for studies of the developmental and cancer processes based on in vitro models. In this paper, we present the approach for segmentation of the DIC images of cultured cells using G-neighbor smoothing followed by Kauwahara filtering and local standard deviation approach for boundary detection. NIH FIJI/ImageJ tools are used to create the ground truth dataset. The results of this work indicate that detection of cell boundaries using segmentation approach even in the case of realistic measurement conditions is a challenging problem.