Comparison of the toxicity of smoke from conventional and harm reduction cigarettes using human embryonic stem cells.

This study evaluated the hypothesis that smoke from harm reduction cigarettes impedes attachment and proliferation of H9 human embryonic stem cells (hESCs). Smoke from three harm reduction brands was compared with smoke from a conventional brand. Doses of smoke were measured in puff equivalents (PE) (1 PE = the amount of smoke in one puff that dissolves in 1 ml of medium). Cytotoxic doses were determined using morphological criteria and trypan blue staining, and apoptosis was confirmed using Magic Red staining. Attachment and proliferation of hESC were followed at a noncytotoxic dose in time-lapse videos collected using BioStation technology. Data were mined from videos either manually or using video bioinformatics subroutines developed with CL-Quant software. Mainstream (MS) and sidestream (SS) smoke from conventional and harm reduction cigarettes induced apoptosis in hESC colonies at 1 PE. At 0.1 PE (noncytotoxic), SS smoke from all brands inhibited attachment of hESC colonies to Matrigel with the strongest inhibition occurring in harm reduction brands. At 0.1 PE, SS smoke, but not MS smoke, from all brands inhibited hESC growth, and two harm reduction brands were more potent than the conventional brand. In general, hESC appeared more sensitive to smoke than their mouse ESC counterparts. Although harm reduction cigarettes are often marketed as safer than conventional brands, our assays show that SS smoke from harm reduction cigarettes was at least as potent or in some cases more potent than smoke from a conventional brand and that SS smoke was more inhibitory than MS smoke in all assays.

Video bioinformatics analysis of human embryonic stem cell colony growth.

Because video data are complex and are comprised of many images, mining information from video material is difficult to do without the aid of computer software. Video bioinformatics is a powerful quantitative approach for extracting spatio-temporal data from video images using computer software to perform dating mining and analysis. In this article, we introduce a video bioinformatics method for quantifying the growth of human embryonic stem cells (hESC) by analyzing time-lapse videos collected in a Nikon BioStation CT incubator equipped with a camera for video imaging. In our experiments, hESC colonies that were attached to Matrigel were filmed for 48 hours in the BioStation CT. To determine the rate of growth of these colonies, recipes were developed using CL-Quant software which enables users to extract various types of data from video images. To accurately evaluate colony growth, three recipes were created. The first segmented the image into the colony and background, the second enhanced the image to define colonies throughout the video sequence accurately, and the third measured the number of pixels in the colony over time. The three recipes were run in sequence on video data collected in a BioStation CT to analyze the rate of growth of individual hESC colonies over 48 hours. To verify the truthfulness of the CL-Quant recipes, the same data were analyzed manually using Adobe Photoshop software. When the data obtained using the CL-Quant recipes and Photoshop were compared, results were virtually identical, indicating the CL-Quant recipes were truthful. The method described here could be applied to any video data to measure growth rates of hESC or other cells that grow in colonies. In addition, other video bioinformatics recipes can be developed in the future for other cell processes such as migration, apoptosis, and cell adhesion.