| Title |
Bionic 3D spheroids biosensor chips for high-throughput and dynamic drug screening
|
|---|---|
| Published in |
Biomedical Microdevices, September 2018
|
| DOI | 10.1007/s10544-018-0329-x |
| Pubmed ID | |
| Authors |
Qian Wu, Xinwei Wei, Yuxiang Pan, Yingchang Zou, Ning Hu, Ping Wang |
| Abstract |
To perform the drug screening, planar cultured cell models are commonly applied to test efficacy and toxicity of drugs. However, planar cultured cells are different from the human 3D organs or tissues in vivo. To simulate the human 3D organs or tissues, 3D spheroids are developed by culturing a small aggregate of cells which reside around the extracellular matrix and interact with other cells in liquid media. Here we apply lung carcinoma cell lines to engineer the 3D lung cancer spheroid-based biosensor using the interdigitated electrodes for drug efficacy evaluation. The results show 3D spheroid had higher drug resistance than the planar cell model. The anticarcinogen inhibition on different 3D lung cancer spheroid models (A549, H1299, H460) can be quantitatively evaluated by electric impedance sensing. Besides, we delivered combination of anticarcinogens treatments to A549 spheroids which is commonly used in clinic treatment, and found the synergistic effect of cisplatin plus etoposide had higher drug response. To simultaneously test the drug efficacy and side effects on multi-organ model with circulatory system, a connected multiwell interdigitated electrode arraywas applied to culture different organoid spheroids. Overall, the organization of 3D cancer spheroids-based biosensor, which has higher predictive value for drug discovery and personalized medicine screening, is expected to be well applied in the area of pharmacy and clinical medicine. |
Mendeley readers
The data shown below were compiled from readership statistics for 56 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 56 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 11 | 20% |
| Student > Master | 7 | 13% |
| Researcher | 6 | 11% |
| Student > Doctoral Student | 4 | 7% |
| Student > Bachelor | 4 | 7% |
| Other | 10 | 18% |
| Unknown | 14 | 25% |
| Readers by discipline | Count | As % |
|---|---|---|
| Engineering | 9 | 16% |
| Biochemistry, Genetics and Molecular Biology | 9 | 16% |
| Medicine and Dentistry | 6 | 11% |
| Agricultural and Biological Sciences | 3 | 5% |
| Chemical Engineering | 2 | 4% |
| Other | 9 | 16% |
| Unknown | 18 | 32% |
Attention Score in Context
This research output has an Altmetric Attention Score of 3. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 17 September 2020.
All research outputs
#7,688,781
of 23,393,513 outputs
Outputs from Biomedical Microdevices
#242
of 770 outputs
Outputs of similar age
#133,875
of 338,795 outputs
Outputs of similar age from Biomedical Microdevices
#2
of 10 outputs
Altmetric has tracked 23,393,513 research outputs across all sources so far. This one is in the 44th percentile – i.e., 44% of other outputs scored the same or lower than it.
So far Altmetric has tracked 770 research outputs from this source. They receive a mean Attention Score of 4.1. This one is in the 32nd percentile – i.e., 32% of its peers scored the same or lower than it.
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We're also able to compare this research output to 10 others from the same source and published within six weeks on either side of this one. This one has scored higher than 8 of them.