Recognition of cancer cells is essential for many important areas such as targeted cancer therapy. Multimonosaccharide-based recognition could be a useful strategy to improve the recognition specificity, but such a possibility has not been explored yet. Herein we report pattern recognition of cells via multiplexed imaging with monosaccharide-imprinted quantum dots (QDs). Imprinted with sialic acid, fucose, and mannose as the template, respectively, the QDs exhibited good specificity toward the template monosaccharides. Multiplexed imaging of cells simultaneously stained with these monosaccharide-imprinted QDs revealed the relative expression levels of the monosaccharides on the cells. Pattern recognition constructed using the intensities of multiplexed imaging unveiled the similarities and differences of different cell lines, allowing for the recognition of not only cancer cells from normal cells but also cancer cells of different cell lines. Thus, this study paved a solid ground for the design and preparation of novel cancer-cell targeting reagents and nanoprobes.
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http://dx.doi.org/10.1021/acs.analchem.7b00965 | DOI Listing |
ACS Sens
January 2025
Materials Interfaces Center, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, P. R. China.
Over recent years, the LUMinescent AntiBody Sensor (LUMABS) system, utilizing bioluminescence resonance energy transfer (BRET), has emerged as a highly effective method for antibody detection. This system incorporates NanoLuc (Nluc) as the donor and fluorescent protein (FP) as the acceptor. However, the limited Stokes shift of FP poses a challenge, as it leads to significant spectral cross-talk between the excitation and emission spectra.
View Article and Find Full Text PDFLab Chip
January 2025
Department of Biomedical Engineering, City University of Hong Kong, 83 Tat Chee Avenue, Kowloon Tong, Hong Kong, China.
Revealing how individual cells alter their secretions over time is crucial for understanding their responses to environmental changes. Key questions include: When do cells modify their functions and states? What transitions occur? Insights into the kinetic secretion trajectories of various cell types are essential for unraveling complex biological systems. This review highlights seven microfluidic technologies for time-resolved single-cell secretion analysis: 1.
View Article and Find Full Text PDFGut
January 2025
Nuffield Department of Surgical Sciences, University of Oxford, Oxford, UK
Background: The immune suppression mechanisms in pancreatic ductal adenocarcinoma (PDAC) remain unknown, but preclinical studies have implicated macrophage-mediated immune tolerance. Hence, pathways that regulate macrophage phenotype are of strategic interest, with reprogramming strategies focusing on inhibitors of phosphoinositide 3-kinase-gamma (PI3Kγ) due to restricted immune cell expression. Inhibition of PI3Kγ alone is ineffective in PDAC, despite increased infiltration of CD8+ T cells.
View Article and Find Full Text PDFEur J Epidemiol
January 2025
Department of Dermatology, Erasmus MC Cancer Institute, Rotterdam, The Netherlands.
Early-stage cutaneous melanoma patients generally have a favorable prognosis, yet a significant proportion of metastatic melanoma cases arise from this group, highlighting the need for improved risk stratification using novel prognostic biomarkers. The Dutch Early-Stage Melanoma (D-ESMEL) study introduces a robust, population-based methodology to develop an absolute risk prediction model for stage I/II melanoma, incorporating clinical, imaging, and multi-omics data to identify patients at increased risk for distant metastases. Utilizing the Netherlands Cancer Registry and Dutch Nationwide Pathology Databank, we collected primary tumor samples from early-stage melanoma patients, with and without distant metastases during follow-up.
View Article and Find Full Text PDFMol Biol Cell
January 2025
Cell Biology, Neurobiology and Biophysics, Department of Biology, Faculty of Science, Utrecht University, Utrecht, the Netherlands.
The cellular interior is a spatially complex environment shaped by non-trivial stochastic and biophysical processes. Within this complexity, spatial organizational principles-also called spatial phenotypes-often emerge with functional implications. However, identifying and quantifying these phenotypes in the stochastic intracellular environment is challenging.
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