A label-free DC impedance-based microcytometer for circulating rare cancer cell counting

Lab on a Chip ◽  
2013 ◽  
Vol 13 (5) ◽  
pp. 970 ◽  
Author(s):  
Hyoungseon Choi ◽  
Kwang Bok Kim ◽  
Chang Su Jeon ◽  
Inseong Hwang ◽  
Saram Lee ◽  
...  
Keyword(s):  
Cancer Cell ◽  
Cell Counting ◽  
Rare Cancer ◽  
Label Free

Rare cancer cell analyzer for whole blood applications: Microcytometer cell counting and sorting subcircuits

Methods ◽  
2005 ◽  
Vol 37 (1) ◽  
pp. 120-127 ◽  
Author(s):  
C. Lancaster ◽  
M. Kokoris ◽  
M. Nabavi ◽  
J. Clemmens ◽  
P. Maloney ◽  
...  
Keyword(s):  
Cancer Cell ◽  
Whole Blood ◽  
Cell Counting ◽  
Rare Cancer ◽  
Cell Analyzer

Abstract 188: Deep learning enables label-free profiling of the tumor microenvironment and enrichment of rare cancer cells

2021 ◽  
Author(s):  
Mahyar Salek ◽  
Hou-pu Chou ◽  
Prashast Khandelwal ◽  
Krishna P. Pant ◽  
Thomas J. Musci ◽  
...  
Keyword(s):  
Deep Learning ◽  
Tumor Microenvironment ◽  
Cancer Cells ◽  
Rare Cancer ◽  
Label Free

Label-free quantification of asymmetric cancer-cell filopodium activities in a multi-gradient chip

Lab on a Chip ◽  
2009 ◽  
Vol 9 (7) ◽  
pp. 884 ◽  
Author(s):  
Tsi-Hsuan Hsu ◽  
Meng-Hua Yen ◽  
Wei-Yu Liao ◽  
Ji-Yen Cheng ◽  
Chau-Hwang Lee
Keyword(s):  
Cancer Cell ◽  
Label Free ◽  
Label Free Quantification ◽  
Free Quantification

Methylseleninic Acid Suppresses Breast Cancer Growth via the JAK2/STAT3 Pathway

2018 ◽  
Vol 26 (6) ◽  
pp. 829-838 ◽  
Author(s):  
Changwei Qiu ◽  
Tao Zhang ◽  
Xinying Zhu ◽  
Jinxia Qiu ◽  
Kangfeng Jiang ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Tumor Growth ◽  
Western Blot ◽  
Cancer Cell ◽  
Anticancer Drug ◽  
Cancer Cell Line ◽  
Janus Kinase ◽  
Cell Counting ◽  
Stat3 Pathway ◽  
Methylseleninic Acid

Previous studies show that methylseleninic acid (MSA), which is the most common selenium derivative used as a drug in humans, exerts specific cytotoxic effects in several cancer cell types. However, the complex mechanism of these effects has not been fully elucidated. Here, we demonstrate by Cell Counting Kit-8 in mouse breast cancer cell line 4T1 that MSA inhibits cell viability in a concentration-dependent (5, 10, 20 μmol/L) and time-dependent (6, 12, 24 hours) manner. Flow cytometry, Western blot, and Reverse Transcription-Polymerase Chain Reaction (RT-PCR) analyses indicated that MSA inhibits cancer cell invasion and induces apoptosis by the activation of caspase-3, poly ADP ribose polymerase 1 (PARP1), and BCL2-associated X. Furthermore, MSA demonstrated anticancer activity by inhibiting the Janus kinase 2/signal transducers and activators of transcription 3 (JAK2/STAT3) pathway. The MSA treatment for 24 hours decreased the phosphorylation of JAK2 and STAT3 in 4T1 cells by Western blot. We also confirmed this with the use of a JAK2 chemical inhibitor, AG490, as a positive control. In a 4T1 orthotopic allograft model, morphological and TdT-mediated dUTP nick-end labeling analyses showed that MSA treatment (1.5 mg/kg/weight) for 28 days inhibits tumor growth consistent with the clinical anticancer drug cyclophosphamide. Our observations demonstrate that MSA is a potent anticancer drug in breast cancer and uncovered a key role of the JAK2/STAT3 pathway in modulating tumor growth.

Highly accurate and label-free discrimination of single cancer cell using a plasmonic oxide-based nanoprobe

2021 ◽  
pp. 113814
Author(s):  
Bao Yue Zhang ◽  
Pengju Yin ◽  
Yihong Hu ◽  
Crispin Szydzik ◽  
Muhammad Waqas Khan ◽  
...  
Keyword(s):  
Cancer Cell ◽  
Label Free ◽  
Single Cancer

Label Free, Nontoxic Cu-GSH NCs as a Nanoplatform for Cancer Cell Imaging and Subcellular pH Monitoring Modulated by a Specific Inhibitor: Bafilomycin A1

2020 ◽  
Vol 3 (2) ◽  
pp. 1245-1257 ◽  
Author(s):  
Neeli Chandran ◽  
Prajit Janardhanan ◽  
Manikanta Bayal ◽  
Unnikrishnan Unniyampurath ◽  
Rajendra Pilankatta ◽  
...  
Keyword(s):  
Cancer Cell ◽  
Cell Imaging ◽  
Ph Monitoring ◽  
Specific Inhibitor ◽  
Label Free ◽  
Bafilomycin A1 ◽  
Cancer Cell Imaging

CD4+ versus CD8+ T-lymphocyte identification in an integrated microfluidic chip using light scattering and machine learning

Lab on a Chip ◽  
2019 ◽  
Vol 19 (22) ◽  
pp. 3888-3898 ◽  
Author(s):  
Domenico Rossi ◽  
David Dannhauser ◽  
Mariarosaria Telesco ◽  
Paolo A. Netti ◽  
Filippo Causa
Keyword(s):  
Machine Learning ◽  
Microfluidic Chip ◽  
Cell Counting ◽  
Learning Approach ◽  
Label Free ◽  
Biophysical Properties ◽  
Cd8 Cells ◽  
Cd8 T Lymphocyte ◽  
Machine Learning Approach ◽  
Compact Dimension

Human CD4+ and CD8+ cells are label-free investigated in a compact-dimension microfluidic chip for detailing biophysical properties. A machine learning approach on obtained results allows an accuracy of cell counting and classification up to 88%.

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