Abstract
Background: Developing ultrasensitive and selective biological sensors has increased in interest for applications in disease detection, drug discovery, and biomedical diagnostics. This paper reports a CMOS-compatible technique for fabricating a silicon nanowire field-effect transistor. The nanowire sensor was applied to detect a fragment of the cancer-related interleukin-1β (IL-1β) gene, which is characterized as an indicator of breast, colon, lung, oral, head, and neck cancers. Methods: We used the advanced integrated circuit (IC) technique to fabricate a back-gated nanowire field-effect transistor sensor. The dimensions of the nanowire were 60 nm in width and 20 μm in length. To enhance the sensitivity of the nanowire sensor, a plasma modification treatment with various parameters was employed on the surface of the device. Results: The sensitivity of the silicon nanowire field-effect transistor could be improved after a 1-minute N2O plasma treatment, because the morphology of the detection region is rougher after the N2O plasma treatment. Hence, a more functional linker could be bound to the surface, thereby increasing the probability of DNA immobilization and hybridization. We used a specific sequence of the IL-1β gene to verify the sensitivity enhancement of the nanowire sensor by using plasma treatment. Conclusion: The sensitivity and detection limit of the plasma-treated sensor can be extrapolated to 0.12/decade and 2.5fM, respectively. The detection results demonstrate that real-time monitoring of the expression of IL-1β using nanowire sensors could be useful for evaluating cancer treatment.
| Original language | English |
|---|---|
| Pages (from-to) | 12-16 |
| Number of pages | 5 |
| Journal | Journal of Experimental and Clinical Medicine(Taiwan) |
| Volume | 5 |
| Issue number | 1 |
| DOIs | |
| Publication status | Published - 2013 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
All Science Journal Classification (ASJC) codes
- General Medicine
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