EasySep? Direct Human CTC Enrichment Kit
Immunomagnetic negative selection of untouched human circulating tumor cells (CTCs) directly from whole blood
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Find supporting information and directions for use in the Product Information Sheet or explore additional protocols below.
Resources and Publications
Educational Materials (12)
Frequently Asked Questions
Publications (2)
Facile, rapid and efficient isolation of circulating tumor cells using aptamer-targeted magnetic nanoparticles integrated with a microfluidic device.
RSC advances 2022 nov
Abstract
Facile and sensitive detection and isolation of circulating tumor cells (CTCs) was achieved using the aptamer-targeted magnetic nanoparticles (Apt-MNPs) in conjugation with a microfluidic device. Apt-MNPs were developed by the covalent attachment of anti-MUC1 aptamer to the silica-coated magnetic nanoparticles via the glutaraldehyde linkers. Apt-MNPs displayed high stability and functionality after 6 months of storage at 4 °C. The specific microfluidic device consisting of mixing, sorting and separation modules was fabricated through conventional photo- and soft-lithography by using polydimethylsiloxane. The capture efficiency of Apt-MNPs was first studied in vitro on MCF-7 and MDA-MB-231 cancer cell lines in the bulk and microfluidic platforms. The cell capture yields of more than 91% were obtained at the optimum condition after 60 minutes of exposure to 50 $\mu$g mL-1 Apt-MNPs with 10 to 106 cancer cells in different media. CTCs were also isolated efficiently from the blood samples of breast cancer patients and successfully propagated in vitro. The isolated CTCs were further characterized using immunofluorescence staining. The overall results indicated the high potential of the present method for the detection and capture of CTCs.
Label-free detection of rare circulating tumor cells by image analysis and machine learning.
Scientific reports 2020
Abstract
Detection and characterization of rare circulating tumor cells (CTCs) in patients' blood is important for the diagnosis and monitoring of cancer. The traditional way of counting CTCs via fluorescent images requires a series of tedious experimental procedures and often impacts the viability of cells. Here we present a method for label-free detection of CTCs from patient blood samples, by taking advantage of data analysis of bright field microscopy images. The approach uses the convolutional neural network, a powerful image classification and machine learning algorithm to perform label-free classification of cells detected in microscopic images of patient blood samples containing white blood cells and CTCs. It requires minimal data pre-processing and has an easy experimental setup. Through our experiments, we show that our method can achieve high accuracy on the identification of rare CTCs without the need for advanced devices or expert users, thus providing a faster and simpler way for counting and identifying CTCs. With more data becoming available in the future, the machine learning model can be further improved and can serve as an accurate and easy-to-use tool for CTC analysis.
New look, same high quality and support! You may notice that your instrument or reagent packaging looks slightly different from images displayed on the website, or from previous orders. We are updating our look but rest assured, the products themselves and how you should use them have not changed. Learn more
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PRODUCTS ARE FOR RESEARCH USE ONLY AND NOT INTENDED FOR HUMAN OR ANIMAL DIAGNOSTIC OR THERAPEUTIC USES UNLESS OTHERWISE STATED. FOR ADDITIONAL INFORMATION ON QUALITY AT 海角破解版, REFER TO WWW.海角破解版.COM/COMPLIANCE.
PRODUCTS ARE FOR RESEARCH USE ONLY AND NOT INTENDED FOR HUMAN OR ANIMAL DIAGNOSTIC OR THERAPEUTIC USES UNLESS OTHERWISE STATED. FOR ADDITIONAL INFORMATION ON QUALITY AT 海角破解版, REFER TO WWW.海角破解版.COM/COMPLIANCE.
