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With the increased development of fluorescently conjugated monoclonal antibodies came more applications with potential clinical impact. In bone marrow transplantation, studies using hematopoietic cytokines made it feasible to gather stem cells from peripheral blood. It was also shown that reconstitution of bone marrow was accelerated when using cell from peripheral blood rather than bone marrow. Many more clinical flow cytoemtry applications have been developed. All of which should follow these 6 keys of running clinical flow cytometry experiments.

Flow cytometry data analysis is getting more complex. Gone is the rule of 2-3 color experiments. Even beginners are starting with 5+ color assays, and the adoption of mass cytometry has the potential to increase our headaches even more. Current data analysis methods are good for single tubes or small cohort studies.  What do you do when you have a large dataset, with multiple sampling conditions, and multiple outcome measurements? With data complexity of this nature, one can export the numerical data to a third party analysis package, but even then the analysis can be difficult to perform. To overcome this…

Measuring purity is not the best way to measure flow cytometry cell sorter performance. Recovery is much more sensitive to the correct calculation of a cell sorter's drop delay than the purity. Here's how to calculate cell sorter recovery, yield, and purity, and why you should use recovery over purity to measure cell sorter performance.

What happens if one combines the power and speed of traditional flow cytometers with the resolution of a microscope? Cytometry is the study of biological processes at the whole cell level and includes techniques like light microscopy and electron microscopy. But microscopy by itself is a bit different. From the earliest days of microscopy, including the use of the first true microscopes by van Leeuwenhoek and others, scientists have been able to start seeing the finest details of a cell. With the development of the flow cytometer, researchers have been able to explore cellular processes in great deal.  For example, modern…

Sudoku puzzles seem to be all the rage. I see it in coffeehouses, at the airport, even in doctors offices. Everyone is trying to work out how to fit the numbers into the grids so that everything adds up properly. Designing polychromatic flow cytometry panels is much like the Sudoku puzzle. In this case, the grid is composed of the antigens on one side, and the cytometer detectors on the other. The goal is to fill in the grid correctly.   Instead of adding up to 45, like in Sudoku, the flow cytometrist is trying to optimize the ability to…

Manual compensation is the process of adjusting the compensation based on how the data visually looks. If you have manually compensated data in your lab notebook--strike it out now. Manual compensation results in overcompensated data, yielding incorrect conclusions. If you have issues, explore what those problems are and work to resolve them rather than making up fiction by manual compensation. Here are three keys to automatically compensating your data.

We all know that flow cytometry makes individual measurements on large populations of cells, it allows for statistical analysis of the data, lending strength to a researcher’s conclusions. Likewise, the isolation of very complex populations by flow cytometry cell sorting can help lead to a richer understanding of the intricate biology at the genomic, proteomic and functional level. As a reviewer of papers and grants, I am always especially interested in the details of HOW the experiments were performed because that is the critical foundation for what the data is able to tell us–and what it can NOT tell us.…

Pairing highly expressed antigens (like CD3) with dimmer fluorochromes, and the antigens of interest with the brightest fluorochromes, is a key part of panel design with few tools to help. With early generation instruments, this was relatively easy to determine, since fluorochrome choice was limited. With the advent of instruments capable of measuring more than 4 fluorochromes, there is a need to characterize the relative brightness of different fluorochromes under actual experimental conditions, rather than as free fluors. Bigos et al (2004) first reported this in an abstract and it was later simplified in Maecker et al (2004). This equation (Figure…

Here at ExCyte–we are excited for all of the new flow cytometry instruments, reagents, and software you will have access to in 2015. There are so many new and innovative products that we have been testing and looking into for you. These are just a few highlights of the great things coming your way in 2015. I. Instrumentation The field of flow cytometry is seeing various trends in instrumentation–on one end are smaller, more compact and more powerful instruments for the high end needs of researchers, and on the other end are easier to use instruments that make flow cytometry…

BD Biosciences brand of digital flow cytometers, including the FACSCanto, the LSR-II, FACSAria and Fortessa, utilize a software acquisition program known as FACSDiva. Diva is aptly named as it can be a difficult program to master. However, Diva has come along way over the past 10 years and many improvements have been made to help end-user. Taking time to learn these changes will improve the reproducibility of your data, the chances of your data getting published, and your overall experience on the cytometer. These changes will also save you time. Here are 8 time-saving FACSDiva tips to use the during…

Flow cytometry data are numbers rich. Data from experiments can be population measurements (percent of CD4+ cells, for example), or it can be expression level (median fluorescent expression of CD69 on activated T cells). Many times, researchers are content to show histograms to illustrate their point after a flow experiment. This approach misses the opportunity to take that content rich data and extend the analysis into a statistical analysis. To properly perform statistical analysis, the first step is to understand the hypothesis. The hypothesis will guide the statistical analysis, identifying the correct test to be performed. There are several things…

Cell death is a fact of biological life.  How, when, where and most importantly, why cells die, can have huge biological consequences on the path an organism may take. Apoptosis, or programed cell death, can result in a selective advantage for an organism. Fingers, for example, are the result of apoptosis of cells during development. Next to immunophenotyping, measuring apoptosis using flow cytometry is one of the most common assays. It may be because of the many different ways to measure the process, many of which can be easily performed in a high-throughput manner, or combined with other assays to determine if…