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When you need better resolution than what can be achieved using a traditional microscope, it can be very intimidating to figure out which machines will work best for your experiment. Super-resolution imaging methods require software reconstruction after image acquisition. This is because multiple images are required, and they need to be combined. Additionally, the points of light need to be reassigned to their true location. Today, we're going to discuss 5 different super resolution methods their pros and cons. Although Rayleigh Criterion is not broken, these techniques each feature creative ways to get around it.

Reproducibility is key to the scientific method. After the results of a study are published, the community validates the findings and extends them. If the findings are not reproducible, the second step is impossible. With performable experiments increasing in complexity, and the concurrent increase in the cost of equipment and reagents to perform these experiments, it is important to find the best way to maximize the money spent on advancing research. In flow cytometry, there are many places where improvements can be made to increase the consistency and reproducibility of an experiment. The most obvious place is in the instrument, but today’s focus is on the reagents we use to identify cells of interest: Antibodies and fluorochromes.

All flow cytometer instruments have a certain 3 components, and the way they are put together will dictate the performance of the system. As a user, you’ll be interacting heavily with these components, so you need to know both what they are and how they work. There are fluidics, optics, and electronics. The fluidics allow you to interact at the right flow rate so that your data keep a tight CV. Then you can run the same flow rate for all your samples, and you won't have different CVs for different samples. There are also different optics you can use, like PMTs, APDs, and PDs. It's important to remember the bandpass filters because they indicate the detector on which your signal will be measured. And with a newer generation of instruments, you can actually change out bandpass filters and design the flow cytometer to your specifications - just make sure you cite the specific bandpass filter that you use. Finally, there are electronics, which process the photon into an electronic signal that is ultimately digitized and stored in a file known as the “FCS file.” An analysis can be performed on this file at a later time.

Did you know that tissues can be measured by flow cytometry? Flow cytometry is the measurement of cellular processes at the whole-cell level. This definition is useful because it includes not only flow cytometry, but any technique that measures at the level of the whole cell. Microscopy, for instance, is a great example of cytometry. But, what can be measured by flow cytometry? For one, tissues with lots of cells. When flow cytometry is practiced, the cells are broken up. Therefore, any cellular interactions within the sample are also broken up. This includes tissues, cell-to-cell contacts in tissues, and virtually any information about the microenvironment. As we continue to discover, the microenvironment can play a dramatic role in cell development, influencing how cells grow and change. This article will discuss how to analyze tissues and microenvironments by flow cytometry.

I am still convinced that my first cell sorter was possessed. The number of issues that I had with the system remains hard for me to believe, even after all these years. It had been purchased, in part, from one vendor because the sales rep for a competitor was nowhere to be found. At that time, I admit I wasn’t overly diligent in my research process. Since then, I’ve pinpointed some critical questions that need to be answered before purchasing a new instrument. At the end of the process, a shiny new instrument will arrive at your facility. Make sure you find time to do a shakedown and validate the system. This is the time to get to know it better, identify quirks and potential issues, and develop training and QC programs. Once your shakedown is complete, you can start adding users and encouraging feedback on the system.

When you're performing imaging, always make sure that any phenotype isn't just an artifact of unhealthy cells. If you're doing drug discovery, you want to ensure that the treatment isn't highly toxic to non-target cells. Therefore, it's important to understand the health of the cells.

It has been said that “a picture is worth a thousand words.” We are visual creatures, and we seek to capture and describe the world around us. Some of the earliest evidence for this comes from very old cave paintings found around the world, like this painting of a horse found in the caves in Lascaux, France. With the development of reliable microscopes, such as those developed by the dutch draper Antonie van Leeuwenhoek, we were able to see what was previously invisible, probing the unseen and learning in great detail how organisms worked. Over time, the field of cytometry (the analysis of biological processes at the whole-cell level) has expanded in many different directions. Flow cytometry can be thought of as a microscope with very poor resolution. The power of flow cytometry lies in its ability to analyze thousands of cells through many dimensions, providing an amazingly detailed understanding of the cell. However, due to the resolution, it is not possible to tell where these signals are located.

Quality control is the hallmark of improving reproducibility. QC programs are designed to help determine when the process in question goes off the expected path. Depending on the deviation from the established acceptance criteria will dictate the level of intervention that needs to occur. This can be as easy as cleaning the instrument and rerunning the QC, or as extreme as removing the data from the final analysis. Since there is documentation as to the deviations, this provides the rationale for excluding data.

FlowJo is a powerful tool for performing and analyzing flow cytometry experiments, if you know how to use it to the fullest. This includes understanding embedding and using keywords, the FlowJo compensation wizard, spillover spreading matrix, FlowJo and R, and creating tables in FlowJo. Extending your use of FJ using these hacks will help organize your data, improve analysis and make your exported data easier to understand and explain to others. Take a few moments and explore all you can do with FJ beyond just gating populations.

Live cell imaging is advantageous for research were you may be worried about artifacts of fixation or when you want to measure a phenomenon over time. Live cell imaging is more difficult to achieve than fixed samples because we need to keep the cells live AND happy along with obtaining the images we need. We can reduce artifacts by keeping the cells in a favorable environment and minimizing external stressors. Here are 5 points to keep in mind when setting up your live cell imaging experiment.

To get the best flow cytometry data you need to be thinking about all the steps in your experiment to ensure that you have high-quality data to analyze. To improve the quality of your analysis make sure you're adding keywords at the beginning of your experimental setup, develop a quality control program, trust but verify any software wizards, use proper controls, and make sure you extract the correct data.

Reproducibility is a state of mind. It's not one simple thing that you do that will make all your data more reproducible, it a shift in the way one thinks about and perform experiments. With the emphasis on rigor and reproducibility in science, it's very important that researchers start putting into place everything they can do to help improve the quality and reproducibility of there data. Learn 3 action steps that can be taken to enhance experimental reproducibility.