The increasing use of engineered nanoparticles (NPs) in industrial and household applications will very likely lead to the release of such materials into the environment. As wastewater treatment plants (WWTPs) are usually the last barrier before the ...
A label-free electrochemiluminescence (ECL) cytosensor was developed for dynamically evaluating of epidermal growth factor receptor (EGFR) expression on MCF-7 cancer cells based on the specific recognition of epidermal growth factor (EGF) with its re...
The flood of high-dimensional data resulting from mass cytometry experiments that measure more than 40 features of individual cells has stimulated creation of new single cell computational biology tools. These tools draw on advances in the field of m...
MOTIVATION: Finding one or more cell populations of interest, such as those correlating to a specific disease, is critical when analysing flow cytometry data. However, labelling of cell populations is not well defined, making it difficult to integrat...
Measurable residual disease (MRD) assessment by flow cytometry (FC) plays an essential role in prognosis and therapy escalation of B-cell acute lymphoblastic leukemia (B-ALL). However, the high degree of expertise and manual analysis time required li...
BACKGROUND: Gastric cancer (GC) is a highly heterogeneous disease, and the response of patients to clinical treatment varies substantially. There is no satisfactory strategy for predicting curative effects to date. We aimed to explore a new method fo...
Accurate diagnosis of B-cell chronic lymphoproliferative disorders (B-CLPDs) remains challenging due to overlapping phenotypes across subtypes. Machine learning (ML) offers promising tools to improve marker evaluation and refine flow cytometry analys...
Journal of cellular and molecular medicine
Jun 1, 2024
In patients with nasopharyngeal carcinoma (NPC), the alteration of immune responses in peripheral blood remains unclear. In this study, we established an immune cell profile for patients with NPC and used flow cytometry and machine learning (ML) to i...
Spiking neural networks (SNNs) are bio-inspired neural networks that - to an extent - mimic the workings of our brains. In a similar fashion, event-based vision sensors try to replicate a biological eye as closely as possible. In this work, we integr...
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