Sepsis is a dysregulated systemic response to infection and is one of the leading causes of in-hospital mortality in Canada. Accurate distinction between survivors and non-survivors of sepsis has recently been demonstrated through quantification of cell-free DNA (cfDNA) concentration in blood. In an analysis of 80 septic patients, non-survivors of sepsis had significantly higher cfDNA concentration levels than that of survivors or healthy patients. Real time separation of cfDNA from contaminants in blood has also been done using a cross channel microfluidic device. Current methods for DNA quantification utilize time consuming and complicated laboratory equipment and therefore are not suitable for bedside real-time testing. Thus a handheld cfDNA fluorescence device coined the Sepsis Check was designed that can perform DNA characterization in a reservoir device and DNA detection in a microfluidic cross channel device. The goal is to use this system along with the cross channel devices to set apart survivors or healthy donors from non-survivors in patients with sepsis.
The design consists of a 470𝑛𝑚 light emitting diode (LED) with 170𝑚𝑊 of optical power (LED470L – ThorLabs), an aspherical uncoated lens with a focal length of 15𝑚𝑚 (LA1540-ML – ThorLabs), a 488𝑛𝑚 bandpass filter with a 3𝑛𝑚 full width at half maximum (FWHM) (FL05488-3 – ThorLabs), an aspherical uncoated lens with a focal length of 25𝑚𝑚 (LA1560-ML – ThorLabs), an aspherical uncoated lens with a focal length of 35𝑚𝑚 (LA1027-ML – ThorLabs), a 525𝑛𝑚 longpass filter with an optical density >4.0 (F84744 – Edmund Optics), and a Raspberry Pi Camera V2 (Raspberry Pi Foundation). The Sepsis Check is made to excite the dsDNA specific PicoGreen fluorophore which has a peak absorbance at 502𝑛𝑚 and a peak emission at 523𝑛𝑚. In summary, the Sepsis Check in this thesis is capable of calibrating dsDNA concentration from 1𝜇𝑔/𝑚𝐿 to 10𝜇𝑔/𝑚𝐿 and detect DNA accumulation of 5𝜇𝑔/𝑚𝐿 and 10𝜇𝑔/𝑚𝐿 in the cross channel device. This tool can be a valuable addition to the ICU to rapidly assess the severity of sepsis for informed decision making. / Thesis / Master of Applied Science (MASc)
| Identifer | oai:union.ndltd.org:mcmaster.ca/oai:macsphere.mcmaster.ca:11375/23998 |
| Date | 30 November 2018 |
| Creators | Bondi, Parker |
| Contributors | Selvaganapathy, Ravi, Biomedical Engineering |
| Source Sets | McMaster University |
| Language | English |
| Detected Language | English |
| Type | Thesis |
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