Friday , April 16 2021

Shooting Single Cells traveling with the speed of Usain Bolt



The accuracy and accuracy with which single cells can be analyzed and manipulated has been greatly improved in recent years with the development of flow cytometry based on microfluids.

Despite its sensitivity, microfluid flow cytometry is limited by low throughput and weak spatial resolution. Recent research has attempted to revolutionize methods for microfluidic flow cytometric techniques to address these constraints. This resulted in the development of new platforms that combine the high bandwidth offered by conventional flow cytometry with spatial resolution of optical microscopy.

Now, a review by scientists at the Institute of Chemical and Bioengineering has summed up recent research into the development of ultra-high-pass single-stage analysis and multi-parameter imaging tools.

The authors summarize several microfluidic means of focusing cells and describe the most advanced detection methodologies; namely shooting techniques based on the camera and the camera. The review is published by Stavrekis and his colleagues Analytical biotechnology special edition of the magazine Current opinion in biotechnology.

The analysis of a single ultra-high flow ultrasound analysis revolutionizes the field of biomedicine.Promotional | Shutterstock

Cameras that can overcome fogging

Simultaneous processing of individual cells or biomolecules depends on the ability to focus cells in the flow of a single cell. This allows cells to be isolated and photographed individually. Several techniques for manipulating the flow of the sheath, a liquid-injected liquid wall, improve the positioning of the flow of the internal flow. This test stream covers the cells that are examined and allows them to be set optimally for shooting.

Movement of high cell velocity in the shell is problematic because it creates "optical blurring", blur over the image of the object. Attempts to eliminate optical blur have previously implemented imaging techniques. These techniques have attempted to merge microscopy, which offers good image resolution with flow cytometry, which suffers from weak spatial resolution.

However, image flows suffer from low moderate throughputs and the need for large amounts of fluid. Current research, instead, focuses on flow cytometry flows with microfluidics, offers the advantages of high-pass and low volume.

Schonbrun et al., for example, incorporated the use of the microframed platform with diffractive lenses to generate an increase and submicron resolution. The latest developments in the microfluid processing of the image have managed to achieve even greater capacity, calling the ultra-high highway.

Rhine et al. demonstrated a means of achieving high-velocity images at high speeds with an analytical productivity of 85,000 cells / s. In addition, they could take more parametric measurements (multi-color fluorescence, light field and dark field images), which allows cells to be characterized with much greater accuracy.

Photo detectors – a superior image acquisition tool?

Camera-based methods are limited by the compromise between sensitivity and recording speed. Platforms based on photodetector, however, offer an alternative way of capturing fast events. The latest methods are focused on capturing images with time that dramatically improves the sensitivity of the image. Time stretching techniques use broadband light pulses from femto-to-pico-seconds to display each biomolecule or cell in the sample.

The shooting-lifting technology, which was developed in California, was recently refined in Hong Kong by Cia et al, whose efforts resulted in a second generation technique called asymmetric optical microscopy detection (or ATOM). Duration includes optical encoding frames for images in ultrafast laser impulses.

The frame rate is determined by the rate of repetition of the ultrafast pulse laser, so that ATOM allows the recording speed to be recorded in millions of frames per second. Furthermore, the encoded image may be amplified. The combined effect of high speed and sensitivity eliminates the scale shown by camera-based methods.

Researchers in Hong Kong captured obscure images of cells that did not require labeling, a typical pre-screening technique used to obtain high contrast images. The speed of 105cells / and far exceed the founder of conventional traditional sensors, which provide one hundred of that.

Fluorescent cell capture is one parameter measure for cells that are harder to obtain. Electromagnetic radiation pulses are needed outside of the spectrum of visible light, hence the time spanning from ATOM is inadequate.

Usually, fine fluorescence impulses are read slowly by camera-based methods that produce individual pixels; this limits the speed of fluorescence images. DiBold et al. recently talked about the issue of high-speed fluorescence images. Inspired by the telecommunications field, they developed a way to generate faster reading rates of images.

The technique, called a fluorescence image using radio frequency labeled emission (FIRE), causes fluorescence from each pixel to be encoded to a different radio frequency. This happens in a manner similar to the way many TV channels are delivered to the TV via a signal wire or how many computers are connected to the signal router. This allows the camera to detect a row of up to 200 pixels at a time. When applied to flow cytometry, FIRE allows each cell to take high-resolution, blur-free and multi-colored images, allowing for more information on the image to be collected.

The review authors are exposing their hopes for applying high-pass, multi-parametric images, stating:

WWe expect that image flow cytometers will begin to incorporate machine learning algorithms in order to enable high content analysis in applications such as profiling cell phenotype, personalized medicine and drug development. "

Sources:

Stavrevis, S., et. al. (2019). High-pass microfluidic image flow cytometry. Current opinion in biotechnology. https://doi.org/10.1016/j.copbio.2018.08.002

Di Carlo, D. (2009). Inert microfluidic. Laboratory of chip. https://doi.org/10.1039/b912547g

Schonbrun, E., et. al. (2012). Microfibrication multifunction cytometry for image flow. Laboratory of chip. https://doi.org/ 10.1039 / C1LC20843H

Rane, A. S., et. al. (2017). High-passive multi-parameter flow cytometry. Chem. https://doi.org/10.1016/j.chempr.2017.08.005

Chiya, K. K., et. al. (2016). High-passage cytometry for image flow for multi-class classification of phytoplankton. Optics Express. https://doi.org/10.1364/OE.24.028170

DiBold, D.D., et. al. (2013). Digitally synthesized throw multiplexing for sub-millisecond fluorescence microscopy. Natural photonics. https://doi.org/10.1038/nphoton.2013.245


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