Guidance on improving the quality of cell counting results to increase confidence amongst the inherent challenges when working with live cells.
Image cytometry and how it compares to other methods. Improve the quality of cell counting results to increase confidence in processes and workflows.
Exploration of candidate genes responsible for esophageal squamous cell carcinoma (ESCC) pathogenesis may provide insight into the underlying signaling pathways to uncover novel therapeutic targets.
The ATR-CHK1 pathway plays a critical role as a replication checkpoint and is a promising target for emerging therapies.
With new variants and waning immunity occurring, especially in elderly and immunocompromised individuals, it is important to understand how to utilize the tools we have to prevent severe disease and death.
The Celigo Image Cytometer has been previously used for a wide range of immuno-oncology and immunotherapy studies, demonstrating the great utility of this instrument to assess the activity of cytotoxic immune cells against malignant cells of interest.
Sangivamycin is an unsuccessful anti-cancer drug candidate that has proven to be a potent inhibitor of multiple viruses. The authors of this study hypothesized that this compound would also be active against SARS-CoV-2.
PerkinElmer Unveils Industry-first Cell Analysis Solution to Streamline Cell and Gene Therapy Research and Manufacturing
PR Teaser: WALTHAM, Mass.--(BUSINESS WIRE)-- PerkinElmer, Inc., (NYSE: PKI), a global leader committed to innovating for a healthier world, today launched the Cellaca® PLX Image Cytometry System, a first-of-its-kind benchtop platform that enables researchers to assess multiple Critical Quality Attributes (CQAs) of cell samples in a single automated workflow, including cell identity, quality and quantity. Read the full press release »
“Biological variation” is an easy explanation to reach for when repeated measurements don’t match up very well. It is vague enough to excuse inconsistency in nearly any biological experiment, and in many cases, it is difficult to disprove.
Starting with a bioinformatics approach using publicly available databases, the authors were able to confirm that tissues from patients with lung adenocarcinoma had increased expression of BCCIP and that high expression levels of BCCIP were correlated with poor patient prognosis.