For a list of peer-reviewed articles our products have been cited in, check out the publications page.
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In this Application Note, we show you how it may be possible to optimize the signal of poorly behaving antibodies with the Signal Enhancement Reagent on Milo.
In this application note, we’ll show you how Wes™ and Milo™ partner to get you critical answers to 1) what type of immune cell populations are present in a sample and then 2) what percentage of cells in that sample make up a specific immune cell subtype.
In this application note, we validate Milo for the analysis of hiPSC-CM cultures. Further, we demonstrate how Single-Cell Western analysis can track phenotypic marker heterogeneity over time and monitor the relative proportion of cell subsets during culture differentiation
In this application note, we demonstrate how Milo can be used to identify and quantify neural subtypes in a heterogeneous neural sample, and monitor the differentiation of induced pluripotent stem cells (iPSCs) into neurons, astrocytes, and oligodendrocytes using R&D Systems research-grade or GMP differentiation reagents.
In this application note, we describe and characterize
a protocol to successfully dissociate mouse neural tissue microsurgically dissected from combined cortex, ventricular
zone, and hippocampus regions of E18 mice into single cells.
In this application note, we describe how you can generate great Single-Cell Western data with an Innoscan 710 scanner, which has the best combination of sensitivity, scan time and resolution needed to scan scWest chips.
Single-cell gene expression studies are revolutionizing our understanding of heterogeneity in disease. Single-cell RNA sequencing tools are powerful for discovering mRNA transcript heterogeneity. However, mRNA levels do not always correlate with functional protein levels. In this application note, learn how Milo was used in parallel with a single-cell RNA-Seq workflow at the Stanford Functional Genomics Facility to validate single-cell RNA expression studies with single-cell protein expression data and ensure accurate and complete conclusions about cellular function. Because it uses the large Western catalog of antibodies & can easily measure intracellular proteins, Milo is the only platform with the versatility to detect diverse targets that are discovered in a sequencing run.
In this application note, we demonstrate several measurements that are difficult or impossible to make with conventional westerns or flow cytometry. We uncover three distinct cell subpopulations that differ based on single- or co-expression of two different protein targets and that could not be distinguished using conventional westerns or flow cytometry. We also demonstrate Milo’s ability to detect discrete cell signaling states by measuring multiple phospho-proteins in individual cells within a population. Finally, we demonstrate how Milo can simultaneously quantify phospho- and total protein expression in each individual cell and quantify how the extent of phosphorylation varies across stimulated and unstimulated cell populations.
The Single-Cell Western™ protocol is highly versatile and can easily be adapted for different biological applications and protein targets. Researchers studying signaling proteins or other targets that require treatment of cells prior to analysis can add a drug, cytokine, or other form of pre-treatment directly to scWest chips after cells have been captured and before running the chip on Milo. Cells can also be treated just prior to settling them onto scWest chips. As a result, the flexible Single-Cell Western workflow allows time-dependent experimental manipulations to be easily performed before lysis and electrophoresis.
Here we describe a two-step, on-chip pre-treatment protocol to measure heterogeneity of modified histones — a class of proteins that is challenging to measure but critical in regulating gene expression. This new measurement capability could be key to unlocking new discoveries in the field of epigenetics.
Every cell is unique, making cell-to-cell heterogeneity important in many areas of biomedicine including cancer pathogenesis, immuno-oncology and regenerative medicine. More and more high-profile publications are using single-cell analysis techniques to reveal variability in cellular response to a drug or stimulus. They're also uncovering variation in drug target expression within a tissue and identifying important subpopulations of cells within complex samples that play key roles in disease progression. Single-cell protein expression information is critical when you need to understand the fundamental composition and behavior of complex biological samples.
Milo, the first and only Single-Cell Western platform out there, lets you do Western blotting at the single-cell level. Now you can run Westerns on thousands of individual cells in parallel and get robust, Western-based information on protein expression heterogeneity in your cells. He also multiplexes so you can measure multiple proteins in each single cell. That means you can get a better understanding of correlations between target expression and characterize cell signaling in specific target-positive subpopulations of cells. Where your target is located in a cell doesn't matter to Milo — his fast, simple workflow lets you measure proteins both on and in each individual cell with the same workflow. It's easy to detect surface proteins and you don't have to worry about fixing and permeabilizing your sample to measure intracellular proteins. As an added bonus, Milo uses conventional Western antibodies which means you can measure diverse protein targets — even ones that don't have good flow cytometry antibodies. The best part? Scout™ Software automates your data analysis and gives you quantitative protein expression measurements in each single cell.
Milo enables scientists to perform single-cell resolution Westerns (scWesterns) for over 1,000 individual cells simultaneously, and in a fraction of the time of conventional Westerns. Researchers can now gain selective protein expression information for up to four protein targets in each cell, offering views into cell-to-cell variation within a complex sample.