國立虎尾科技大學 |

SERS-Based Prognosis of Kidney Transplant Outcome.

紀錄類型:	書目-語言資料,手稿 : Monograph/item
正題名/作者:	SERS-Based Prognosis of Kidney Transplant Outcome./
作者:	Chi, Jingmao.
面頁冊數:	1 online resource (199 pages)
附註:	Source: Dissertation Abstracts International, Volume: 78-12(E), Section: B.
標題:	Materials science. -
電子資源:	click for full text (PQDT)
ISBN:	9780355094183

SERS-Based Prognosis of Kidney Transplant Outcome.
Chi, Jingmao.

SERS-Based Prognosis of Kidney Transplant Outcome. - 1 online resource (199 pages)

Source: Dissertation Abstracts International, Volume: 78-12(E), Section: B.

Thesis (Ph.D.)--Stevens Institute of Technology, 2017.

Includes bibliographical references

Kidney transplant is the predominant procedure of all organ transplants around the world. The number of patients on the waiting list for a kidney is growing rapidly, yet the number of donations does not keep up with the fast-growing need. This thesis focuses on the surface-enhanced Raman scattering (SERS) analysis of urine samples for prognosis of kidney transplant outcome, which can potentially let patients have a more timely treatment as well as expand the organ pool for transplant. We have observed unique SERS spectral features from urine samples of kidney transplant recipients that have strong associations with the kidney acute rejection (AR) based on the analysis of urine one day after the transplant. Our ability to provide an early prognosis of transplant outcome is a significant advance over the current gold standard of clinical diagnosis, which occurs weeks or months after the surgical procedure. The SERS analysis has also been applied to urine samples from deceased kidney donors. Excellent classification ability was achieved when the enhanced PCA-LDA analysis was used to classify and identify urine samples from different cases. The sensitivity of the acute tubular necrosis (ATN) class is more than 90%, which can indicate the usable kidneys in the high failure risk category. This analysis can help clinicians identify usable kidneys which would be discarded using conventional clinic methods as high failure risk. To investigate the biomarkers that cause the unique SERS features, an HPLC-SERS-MS approach was established. The high-performance liquid chromatography (HPLC) was used to separate the urinary components to reduce the sample complexity. The mass spectrometry (MS) was used to determine the formulas and the structures of the biomarkers. The presence of 1-methyl-2-pyrrolidone (NMP) and adenine in urine samples were confirmed by both MS and SERS analysis. Succinylmonocholine, a metabolite of suxamethonium, has a potential to be the biomarker that causes the unique SERS spectral features that indicate kidney AR. By integrating SERS analysis with statistical and chemical analysis and with the promising outcomes, this research has made a significant contribution in exploring the frontier of SERS analysis in biomedical sensing and diagnosis.

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2018

Mode of access: World Wide Web

ISBN: 9780355094183Subjects--Topical Terms:

557839
Materials science.
Index Terms--Genre/Form:

554714
Electronic books.

SERS-Based Prognosis of Kidney Transplant Outcome.
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520 $a Kidney transplant is the predominant procedure of all organ transplants around the world. The number of patients on the waiting list for a kidney is growing rapidly, yet the number of donations does not keep up with the fast-growing need. This thesis focuses on the surface-enhanced Raman scattering (SERS) analysis of urine samples for prognosis of kidney transplant outcome, which can potentially let patients have a more timely treatment as well as expand the organ pool for transplant. We have observed unique SERS spectral features from urine samples of kidney transplant recipients that have strong associations with the kidney acute rejection (AR) based on the analysis of urine one day after the transplant. Our ability to provide an early prognosis of transplant outcome is a significant advance over the current gold standard of clinical diagnosis, which occurs weeks or months after the surgical procedure. The SERS analysis has also been applied to urine samples from deceased kidney donors. Excellent classification ability was achieved when the enhanced PCA-LDA analysis was used to classify and identify urine samples from different cases. The sensitivity of the acute tubular necrosis (ATN) class is more than 90%, which can indicate the usable kidneys in the high failure risk category. This analysis can help clinicians identify usable kidneys which would be discarded using conventional clinic methods as high failure risk. To investigate the biomarkers that cause the unique SERS features, an HPLC-SERS-MS approach was established. The high-performance liquid chromatography (HPLC) was used to separate the urinary components to reduce the sample complexity. The mass spectrometry (MS) was used to determine the formulas and the structures of the biomarkers. The presence of 1-methyl-2-pyrrolidone (NMP) and adenine in urine samples were confirmed by both MS and SERS analysis. Succinylmonocholine, a metabolite of suxamethonium, has a potential to be the biomarker that causes the unique SERS spectral features that indicate kidney AR. By integrating SERS analysis with statistical and chemical analysis and with the promising outcomes, this research has made a significant contribution in exploring the frontier of SERS analysis in biomedical sensing and diagnosis.
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