請用此 Handle URI 來引用此文件：
http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/48961完整後設資料紀錄
| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 潘文涵(Wen-Harn Pan) | |
| dc.contributor.author | Feng-Ju Wu | en |
| dc.contributor.author | 吳豐如 | zh_TW |
| dc.date.accessioned | 2021-06-15T11:12:26Z | - |
| dc.date.available | 2019-08-25 | |
| dc.date.copyright | 2016-08-25 | |
| dc.date.issued | 2016 | |
| dc.date.submitted | 2016-08-22 | |
| dc.identifier.citation | 1. World Health Organization. Dementia: a public health priority (World Health Organization, 2012).
2. Burns, A. and S. Iliffe, Alzheimer’s disease. BMJ, 2009. 338. 3. World Health Organization. Dementia fact sheet no. 362. 2012, Apr. 4. Castellani, R.J., et al., Reexamining Alzheimer's Disease: Evidence for a Protective Role for Amyloid-β Protein Precursor and Amyloid-β. Journal of Alzheimer's disease : JAD, 2009. 18(2): 447-452. 5. Ballard, C., et al., Alzheimer's disease. The Lancet. 377(9770): 1019-1031. 6. Kaddurah-Daouk, R., et al., Alterations in metabolic pathways and networks in Alzheimer’s disease. Translational psychiatry, 2013. 3(4): e244. 7. L Ferreira, I., et al., Multiple defects in energy metabolism in Alzheimer's disease. Current drug targets, 2010. 11(10): 1193-1206. 8. Rojo, L.E., et al., Neuroinflammation: implications for the pathogenesis and molecular diagnosis of Alzheimer's disease. Archives of medical research, 2008. 39(1): 1-16. 9. Ferrer, I., Defining Alzheimer as a common age-related neurodegenerative process not inevitably leading to dementia. Progress in neurobiology, 2012. 97(1): 38-51. 10. Ahtiluoto, S., et al., Diabetes, Alzheimer disease, and vascular dementia A population-based neuropathologic study. Neurology, 2010. 75(13): 1195-1202. 11. Ohara, T., et al., Glucose tolerance status and risk of dementia in the community The Hisayama Study. Neurology, 2011. 77(12): 1126-1134. 12. Peila, R., B.L. Rodriguez, and L.J. Launer, Type 2 Diabetes, APOE Gene, and the Risk for Dementia and Related Pathologies. The Honolulu-Asia Aging Study, 2002. 51(4): 1256-1262. 13. Roriz-Filho, J.S., et al., (Pre) diabetes, brain aging, and cognition. Biochimica et Biophysica Acta (BBA)-Molecular Basis of Disease, 2009. 1792(5): 432-443. 14. Samaras, K. and P.S. Sachdev, Diabetes and the elderly brain: sweet memories? Therapeutic advances in endocrinology and metabolism, 2012. 3(6): 189-196. 15. Cukierman, T., H. Gerstein, and J. Williamson, Cognitive decline and dementia in diabetes—systematic overview of prospective observational studies. Diabetologia, 2005. 48(12): 2460-2469. 16. Janson, J., et al., Increased risk of type 2 diabetes in Alzheimer disease. Diabetes, 2004. 53(2): 474-481. 17. Luchsinger, J.A., et al., Hyperinsulinemia and risk of Alzheimer disease. Neurology, 2004. 63(7): 1187-1192. 18. Sommerfield, A.J., et al., Short-term, delayed, and working memory are impaired during hypoglycemia in individuals with type 1 diabetes. Diabetes care, 2003. 26(2): 390-396. 19. Exalto, L., et al., An update on type 2 diabetes, vascular dementia and Alzheimer's disease. Experimental gerontology, 2012. 47(11): 858-864. 20. Control, D., et al., The effect of intensive treatment of diabetes on the development and progression of long-term complications in insulin-dependent diabetes mellitus. N Engl j Med, 1993. 1993(329): 977-986. 21. Biessels, G.J., et al., Ageing and diabetes: implications for brain function. European journal of pharmacology, 2002. 441(1): 1-14. 22. Gispen, W.H. and G.-J. Biessels, Cognition and synaptic plasticity in diabetes mellitus. Trends in neurosciences, 2000. 23(11): 542-549. 23. Irie, F., et al., Enhanced risk for Alzheimer disease in persons with type 2 diabetes and APOE ε4: The Cardiovascular Health Study Cognition Study. Archives of neurology, 2008. 65(1): 89-93. 24. Zhao, W.-Q. and M. Townsend, Insulin resistance and amyloidogenesis as common molecular foundation for type 2 diabetes and Alzheimer's disease. Biochimica et Biophysica Acta (BBA)-Molecular Basis of Disease, 2009. 1792(5): 482-496. 25. Cole, G.M. and S.A. Frautschy, The role of insulin and neurotrophic factor signaling in brain aging and Alzheimer’s Disease. Experimental gerontology, 2007. 42(1): 10-21. 26. Hoyer, S., The brain insulin signal transduction system and sporadic (type II) Alzheimer disease: an update. Journal of neural transmission, 2002. 109(3): 341-360. 27. Watson, G.S. and S. Craft, Insulin resistance, inflammation, and cognition in Alzheimer's Disease: lessons for multiple sclerosis. Journal of the neurological sciences, 2006. 245(1): 21-33. 28. Umegaki, H., Type 2 diabetes as a risk factor for cognitive impairment: current insights. Clin Interv Aging, 2014. 9(9): 1011-1019. 29. Cole, A.R., et al., Molecular connexions between dementia and diabetes. Neuroscience & Biobehavioral Reviews, 2007. 31(7): 1046-1063. 30. Brownlee, M., Michael, Advanced protein glycosylation in diabetes and aging. Annual review of medicine, 1995. 46(1): 223-234. 31. Qiu, W.Q., et al., Insulin-degrading enzyme regulates extracellular levels of amyloid β-protein by degradation. Journal of Biological Chemistry, 1998. 273(49): 32730-32738. 32. Messier, C., Diabetes, Alzheimer's disease and apolipoprotein genotype. Experimental gerontology, 2003. 38(9): 941-946. 33. Ko, L.-w., et al., An immunochemical study on tau glycation in paired helical filaments. Brain research, 1999. 830(2): 301-313. 34. Kaytor, M.D. and H.T. Orr, The GSK3β signaling cascade and neurodegenerative disease. Current opinion in neurobiology, 2002. 12(3): 275-278. 35. Ravindran, P., K.N. Babu, and K. Sivaraman, Turmeric: the genus Curcuma. 2007: CRC Press. 36. Jurenka, S. and M. Jurenka, Anti-inflammatory properties of curcumin, a major constituent. Alternative medicine review, 2009. 14(2). 37. Aggarwal, B.B., et al., Curcumin‐free turmeric exhibits anti‐inflammatory and anticancer activities: Identification of novel components of turmeric. Molecular nutrition & food research, 2013. 57(9): 1529-1542. 38. Arora, R., et al., Anti-inflammatory studies on Curcuma longa (turmeric). The Indian journal of medical research, 1971. 59(8): 1289-1295. 39. ABE, Y., S. Hashimoto, and T. HORIE, Curcumin inhibition of inflammatory cytokine production by human peripheral blood monocytes and alveolar macrophages. Pharmacological Research, 1999. 39(1): 41-47. 40. Ramirez-Boscá, A., et al., Antioxidant curcuma extracts decrease the blood lipid peroxide levels of human subjects. Age, 1995. 18(4): 167-169. 41. Usharani, P., et al., Effect of NCB-02, atorvastatin and placebo on endothelial function, oxidative stress and inflammatory markers in patients with type 2 diabetes mellitus. Drugs in R & D, 2008. 9(4): 243-250. 42. Kuttan, R., P. Sudheeran, and C. Josph, Turmeric and curcumin as topical agents in cancer therapy. Tumori, 1987. 73(1): 29-31. 43. Aggarwal, B.B., A. Kumar, and A.C. Bharti, Anticancer potential of curcumin: preclinical and clinical studies. Anticancer res, 2003. 23(1A): 363-398. 44. Negi, P., et al., Antibacterial activity of turmeric oil: a byproduct from curcumin manufacture. Journal of Agricultural and Food Chemistry, 1999. 47(10): 4297-4300. 45. Liu, J.-Y., S.-J. Lin, and J.-K. Lin, Inhibitory effects of curcumin on protein kinase C activity induced by 12-O-tetradecanoyl-phorbol-13-acetate in NIH 3T3 cells. Carcinogenesis, 1993. 14(5): 857-861. 46. Zhang, C., et al., Curcumin decreases amyloid-β peptide levels by attenuating the maturation of amyloid-β precursor protein. Journal of Biological Chemistry, 2010. 285(37): 28472-28480. 47. Rainey-Smith, S.R., et al., Curcumin and cognition: a randomised, placebo-controlled, double-blind study of community-dwelling older adults. British Journal of Nutrition, 2016. 115(12): 2106-2113. 48. Wong, C.P., T. Kaneda, and H. Morita, Plant natural products as an anti-lipid droplets accumulation agent. Journal of natural medicines, 2014. 68(2): 253-266. 49. Lee, M.-S., et al., Turmeric improves post-prandial working memory in pre-diabetes independent of insulin. Asia Pacific journal of clinical nutrition, 2014. 23(4): 581. 50. Jordan, K.W., et al., Metabolomic characterization of human rectal adenocarcinoma with intact tissue magnetic resonance spectroscopy. Diseases of the colon and rectum, 2009. 52(3): 520. 51. Nordström, A., et al., Nonlinear data alignment for UPLC-MS and HPLC-MS based metabolomics: quantitative analysis of endogenous and exogenous metabolites in human serum. Analytical chemistry, 2006. 78(10): 3289-3295. 52. Wishart, D.S., Current progress in computational metabolomics. Briefings in Bioinformatics, 2007. 8(5): 279-293. 53. Nicholson, J.K., Global systems biology, personalized medicine and molecular epidemiology. Molecular systems biology, 2006. 2(1): 52. 54. Holmes, E., I.D. Wilson, and J.K. Nicholson, Metabolic phenotyping in health and disease. Cell, 2008. 134(5): 714-717. 55. Nicholson, J.K., et al., Metabonomics: a platform for studying drug toxicity and gene function. Nature reviews Drug discovery, 2002. 1(2): 153-161. 56. Nicholson, J.K., J.C. Lindon, and E. Holmes, 'Metabonomics': understanding the metabolic responses of living systems to pathophysiological stimuli via multivariate statistical analysis of biological NMR spectroscopic data. Xenobiotica, 1999. 29(11): 1181-1189. 57. Dettmer, K., P.A. Aronov, and B.D. Hammock, Mass spectrometry‐based metabolomics. Mass spectrometry reviews, 2007. 26(1): 51-78. 58. Roberts, L.D., et al., Targeted metabolomics. Current protocols in molecular biology, 2012: 30.2. 1-30.2. 24. 59. Johnson, C.H., J. Ivanisevic, and G. Siuzdak, Metabolomics: beyond biomarkers and towards mechanisms. Nature Reviews Molecular Cell Biology, 2016. 60. Dall’Acqua, S., et al., Changes in urinary metabolic profile after oral administration of curcuma extract in rats. Journal of pharmaceutical and biomedical analysis, 2014. 100: 348-356. 61. Ireson, C., et al., Characterization of metabolites of the chemopreventive agent curcumin in human and rat hepatocytes and in the rat in vivo, and evaluation of their ability to inhibit phorbol ester-induced prostaglandin E2 production. Cancer Research, 2001. 61(3): 1058-1064. 62. Nieman, D.C., et al., Influence of red pepper spice and turmeric on inflammation and oxidative stress biomarkers in overweight females: A metabolomics approach. Plant foods for human nutrition, 2012. 67(4): 415-421. 63. Crum, R.M., et al., Population-based norms for the Mini-Mental State Examination by age and educational level. Jama, 1993. 269(18): 2386-2391. 64. Baddeley, A., Working memory. Science, 1992. 255(5044): 556. 65. Diamond, A., Executive Functions. Annual review of psychology, 2013. 64: 135-168. 66. Cowan, N., What are the differences between long-term, short-term, and working memory? Progress in brain research, 2008. 169: 323-338. 67. Vaux, D.L., F. Fidler, and G. Cumming, Replicates and repeats—what is the difference and is it significant? EMBO reports, 2012. 13(4): 291-296. 68. Liang, Y.-J., et al., SMART: Statistical Metabolomics Analysis | |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/48961 | - |
| dc.description.abstract | 研究背景與目的：過去研究團隊發現，攝取薑黃 6 小時內能改善認知功能及增進工作記憶。然而薑黃對於工作記憶的影響並不是透過降血糖途徑或降低阿茲海默症相關生物標記基因表現量而來，因此需要更進一步的研究來了解其影響機制。代謝體學主要的標的物為生物體內的小分子代謝物，藉由測量這些代謝物，能夠幫助我們更加清楚人體代謝受到挑戰時的變化情形。本研究接續之前的相關短期攝食研究，利用代謝體學的方式探討薑黃組與安慰劑組血漿中代謝物的變化型態之不同，進而搜尋可能參與工作記憶的生物指標、代謝路徑和機制。
實驗方法：本研究前一階段招募 23 位受試者，為一隨機分派雙盲的代謝體研究。投予薑黃後，試驗觀察期大約為 6 小時。本研究測量評估試驗前以及試驗後固定時間點 (2,4,6小時後)，個案血中代謝物強度，並與工作記憶分數利用廣義估計方程（GEE）模型比較薑黃組與安慰劑組之平均測量值與變化斜率差異作關聯分析。實驗組 (n=12) 攝入兩片白吐司以及薑黃膠囊 (1g) ，安慰劑組 (n=11) 作為對照組，共進行 4 個時間點的血漿樣本收集。所有樣本使用全方位的分析平台：超高效液相層析四極柱飛行時間質譜儀來分析安慰劑組和攝食薑黃組的血漿樣本。 結果：有顯著差異的代謝物在人體參與的代謝路徑包含碳水化合物代謝、氨基酸代謝、核酸代謝、脂質代謝等。此外，我們發現 S-Adenosyl-L-homocysteine (負向) 和 trans-Cinnamic acid (正向) 這兩個代謝物和受試者工作記憶分數的改善量顯著相關。這些發現提供了一個全面的血漿代謝圖譜，有助於探討攝取薑黃能夠增進工作記憶的潛在機制。 結論：由實驗結果發現，薑黃可能作用機制為提升苯丙氨酸代謝及降低半胱氨酸和腺苷代謝以提升工作記憶。本實驗結果幫助我們更加了解薑黃增進工作記憶的作用機制。 | zh_TW |
| dc.description.abstract | Background and objective: Our previous study showed that the intake of turmeric with white bread could acutely increase working memory in patient with prediabetes. However, the effect was not associated with known AD biomarkers, more research is needed to understand the potential mechanisms. Metabolomics is a systematic platform which appraises all small molecule metabolites in a bio-specimen. Exploring metabolomics changes may help us to find new biomarkers and mechanisms associating with working memory. This study was a double-blind randomized placebo controlled metabolics study. We intended to use analytical metabolomics approach to find specific metabolic changes associated with turmeric intervention.
Method: The study included 2 groups: the experimental group (n=12) provided with 1g of turmeric capsule and with two slices of bread, whereas the control group (n=11) provided with placebo. The observation period lasted for 6 hours collecting the plasma samples at four time points and appraising working memory (WM) before and after the 6 hr period. We applied a comprehensive UPLC-MS platform to carry out untargeted plasma metabolomics. Using generalized estimating equation (GEE) models, we carried out statistical analyses to compare turmeric groups with placebo group through time points on mean intensity difference and on slope of intensity changes. Results: Metabolite markers identified were involved in carbohydrate metabolism, amino acid metabolism, nucleotide metabolism, lipid metabolism, etc. The changes (AUC) of S-adenosyl-L-homocysteine was inversely associated with WM changes; whereas trans-cinnamic acid was found positively associated with WM changes. These findings provide a comprehensive global plasma metabolite profiling and may contribute to understanding the pathogenic mechanism of how turmeric improved WM performance. Conclusion: In conclusion, we identified comprehensive metabolic shifts between turmeric and placebo subjects including altered carbohydrate metabolism, nucleotide metabolism, lipid metabolism, amino acid metabolism, etc. The WM improved by turmeric administration may on account of changes in cysteine and adenosine metabolism as well as phenylalanine metabolism identified in our study. This study helps us approach the potential mechanism of turmeric effect on working memory. | en |
| dc.description.provenance | Made available in DSpace on 2021-06-15T11:12:26Z (GMT). No. of bitstreams: 1 ntu-105-R03b22030-1.pdf: 5254449 bytes, checksum: 554da79ac0495e125760bdf541db1790 (MD5) Previous issue date: 2016 | en |
| dc.description.tableofcontents | 致謝…………………………………………………………………………………….Ⅰ
中文摘要 …………………………………………………………….….………….....Ⅱ Abstract …………………………………………………………………………….......Ⅲ Chapter 1. Introduction …………………………………………………..…….....… 1 1.1. Alzheimer’s disease 1.2. Cognitive impairment and dementia in (pre)diabetes 1.3. Health benefits of turmeric treatment 1.4. Metabolomics 1.5. Metabolomics study of turmeric treatment Chapter 2.Materials and methods ……………………………………………….…. 14 2.1. Study design 2.2. Participants 2.3. Study materials 2.4. Working memory test 2.5. Metabolomics analysis 2.6. Data analysis Chapter 3. Results ………………………………………………………...………..…27 3.1. Baseline characteristics of the participants 3.2. Metabolite data pre-processing 3.3. Identifying metabolites of interest by GEE models 3.4. Pathway analysis 3.5. The association between WM changes and metabolites net AUC Chapter 4. Discussion ………...............................................................................…... 32 Chapter 5. Tables and figures ……………................................................…..….……40 References ………............................................................................……......................61 Appendices ………............................................................................………………….70 | |
| dc.language.iso | en | |
| dc.subject | 工作記憶 | zh_TW |
| dc.subject | 代謝體學 | zh_TW |
| dc.subject | 血漿 | zh_TW |
| dc.subject | 薑黃 | zh_TW |
| dc.subject | plasma | en |
| dc.subject | working memory | en |
| dc.subject | turmeric | en |
| dc.subject | metabolomics | en |
| dc.title | 以代謝體研究法探討薑黃影響糖尿病前期工作記憶之生物標記與潛在機制 | zh_TW |
| dc.title | Application of metabolomics approach to find biomarkers and mechanisms of turmeric effect on working memory in pre-diabetes | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 104-2 | |
| dc.description.degree | 碩士 | |
| dc.contributor.oralexamcommittee | 楊欣洲,郭錦樺,李美璇,馬克華偉士(WAHLQVIST MARK LAWRE) | |
| dc.subject.keyword | 代謝體學,血漿,薑黃,工作記憶, | zh_TW |
| dc.subject.keyword | metabolomics,plasma,turmeric,working memory, | en |
| dc.relation.page | 88 | |
| dc.identifier.doi | 10.6342/NTU201603520 | |
| dc.rights.note | 有償授權 | |
| dc.date.accepted | 2016-08-22 | |
| dc.contributor.author-college | 生命科學院 | zh_TW |
| dc.contributor.author-dept | 生化科技學系 | zh_TW |
| 顯示於系所單位： | 生化科技學系 | |
文件中的檔案：
| 檔案 | 大小 | 格式 | |
|---|---|---|---|
| ntu-105-1.pdf 未授權公開取用 | 5.13 MB | Adobe PDF |
系統中的文件，除了特別指名其著作權條款之外，均受到著作權保護，並且保留所有的權利。