完整後設資料紀錄
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dc.contributor.author劉大中zh_TW
dc.contributor.author陳三元zh_TW
dc.contributor.authorLiu, Ta-Chungen_US
dc.contributor.authorChen, San-Yuanen_US
dc.date.accessioned2018-01-24T07:38:59Z-
dc.date.available2018-01-24T07:38:59Z-
dc.date.issued2016en_US
dc.identifier.urihttp://etd.lib.nctu.edu.tw/cdrfb3/record/nctu/#GT079918837en_US
dc.identifier.urihttp://hdl.handle.net/11536/140186-
dc.description.abstract大腦退化性疾病與其他相關疾病已對人類產生莫大影響,近年來,越來越多的大腦相關疾病,大部分常是無法治癒。因此,辨別與精準偵測大腦內生物訊號,並加以處理解析,從中能診斷大腦疾病進程,此儼然已成為治療大腦相關疾病的必要角色。隨著奈米科技的進步,侵入式感測器與非侵入式感測器能夠針對病患給予不同程度之應用性,奈米材料改質感測器之微小電極,乃是絕對趨勢。本論文致力結合材料科學、電化學理論與生物化學已發展不同之神經化學界面,並進一步應用在生醫感測器上面。 在第一部分,將石墨烯化學裂解成小於150nm的片狀結構,再利用單步驟循環伏安電泳沉降技術,將片狀石墨烯沉積於侵入式之神經陣列金電極表面,名為rGO/Au2O3電極。同時此特殊電泳沉降技術除了能將奈米片狀石墨烯均勻沉積在金電極表面,又能同步還原石墨烯成為還原態石墨烯,大大提高導電性與比表面積;而奈米等級之片狀石墨烯,其表面邊緣富含活化點,能催化氧化還原反應。根據調控不同之電泳沉積速率,我們探討了rGO/Au2O3奈米結構電極之電化學界面反應,證明最低之電泳沉積速度(10 mVs-1) 具有最佳感測性質。因此,藉由rGO/Au2O3奈米結構電極,我們以缺血性中風之大鼠動物模型作感測之概念驗證,透過監測中風後過氧化氫(H2O2)之變化,可發現rGO/Au2O3奈米結構電極較未改質金電極有更敏銳的感測效能,也證明了rGO/Au2O3電化學界面能作為感測其他腦內化學分子之潛力。 在第二部分,由於個人精準醫療(POC)為現今感測科技之趨勢,針對早期阿茲海默症的診斷研究,多以感測患者生物流體(Bio-fluids)內之生物標誌分子,像是乙狀澱粉蛋白聚合體,作為診斷依據。因此,我們結合奈米高分子自組裝技術與免疫電化學理論開發出了三維的導電奈米微胞結構界面,輔以神經陣列電極(原為觀察體外培養細胞之電生理訊號),開發出多功能感測平台。此導電奈米微胞乃由雙性蛋白質-蠶絲蛋白與導電型高分子單體(EDOT)構成,並搭載專一性抗體,以電泳方式將導電奈米微胞沉降於電極上,具有以下特點:1)高含量PEDOT與奈米顆粒結構,大大提升電子傳導效率與降低阻抗;2)電泳過程同時發生EDOT電聚合反應,提升薄膜與電極之附著力;3)導電奈米微胞表面接枝的專一性抗體與PEDOT,放大了氧化還原電子轉移之訊號;4)此導電奈米微胞電極達到6.6 pg/ml與少於10分鐘之應答時間,能實際應用於生物流體體外感測。最後,以基因誘導阿茲海默小鼠(3×Tg-AD)之血漿作驗證,輔以腦部組織切片染色與微型正子影像,證實了結合神經陣列元件與改質奈米結構神經界面能建立乙狀澱粉蛋白聚合程度之觀察模型,作為早期阿茲海默症之有效診斷依據。總括我們的研究,以材料科學之功能化設計為基礎,將期望提高各式生醫感測器之效能,同時也提供對於相關疾病的研究價值。zh_TW
dc.description.abstractIn recent years, brain-related diseases have caused huge impacts on human beings, and most of them were unable to cured. Therefore, distinguishing and processing biosignals in brain is quietly essential and helpful for diagnosing brain-related diseases. Through improvements have been brought by nanotechnology, implantable or non-implantable biosensors are able to give applicability for different kinds of diseases, electrodes in biosensors modified with nanomaterials has played an important role on the development of biosensing. In this thesis, we focus on developing neurochemistry interface according to the knowledge and technology of material science, electrochemical theory and biochemistry for further application on biosensing. In first part, we separated graphite into graphene oxide nanosheets (<150 nm) by a chemical cleavage manner, and then used a one-step cyclic voltammetry (CV) electrophoresis to deposit graphene oxide nanosheets on the gold electrodes in implantable microelectrode array, named as rGO/Au2O3 nanocomposite electrode. The enhanced electrons transfers and high surface areas were achieved by the electrophoresis which was not only able to well-dispersive deposit graphene oxide nanosheets onto electrode surface, but simultaneously electro-reduce graphene oxides into reduced graphene oxides (rGO). Furthermore, the enriched edges on nanopieces of rGOs providing active sites could catalyze the redox reactions. By tuning different deposition scan rates, we studied the electrode interfacial properties according electrochemical impedance spectrum (EIS), and lower deposition scan rate of 10 mVs-1 give the optimum sensing performance. Herein, we presented a proof-to-concept validation using a hyperacute stroke rat model to monitor the changes of H2O2 concentration during stroke. As expected, rGO/Au2O3 electrode owns better sensing performances no matter in sensitivity or response time than conventional gold electrode, and this rGO/Au2O3 neurochemical interface offers great promise as other sensing applications. In second part, due to personal medical precision (point of care, POC) for the current trend in the science and technology of biosensing, the diagnosis of early Alzheimer’s disease is more to sense biological fluids of patients within molecular biomarkers, i.e. amyloid-beta peptides. As a result, we combined copolymer self-assembly nanotechnology and immune-electrochemical theory developed a three-dimensional conductive nanospheres structure interface, integrated with microelectrode sensor array (formerly used as observation of electrophysiological signals of cultured cells), to develop a multisensing platform. This conductive nanospheres made by amphiphilic silk fibroin and conductive polymer monomer (EDOT), and equipped with specific antibody were deposited onto electrodes by electrophoresis, with the following merits: 1) high doping PEDOT and nanoparticle structure give great electron transferring efficiency and low impedance; 2) compared to conventional electrophoresis, the silk-based nanospheres with the help of EDOT electro-polymerization give strong adhesions, 3) the specificity and signals amplification are enhanced owing to the high coupling of antibodies within one single nanosphere on surface. 4) The high sensitivity interface with low detection limit of 6.6 pg/ml and short response time of less than 10 minutes is capable of biological fluids in detection of amyloid-beta. For the final part, this multisensing system has been evaluated in 3×Tg-AD (homozygous) mice serum, and proposes proof of concept to construct a model using a microelectrode sensor array to enable tracking amyloid-beta aggregation behaviors for the diagnosis of Alzheimer’s disease.en_US
dc.language.isoen_USen_US
dc.subject循環伏安法zh_TW
dc.subject電泳zh_TW
dc.subject神經電化學界面zh_TW
dc.subject植入式神經電極zh_TW
dc.subject石墨烯zh_TW
dc.subject蠶絲蛋白zh_TW
dc.subject生醫感測zh_TW
dc.subject缺血性中風zh_TW
dc.subject阿茲海默症zh_TW
dc.subjectCyclic Voltammetryen_US
dc.subjectelectrophoresisen_US
dc.subjectneurochemistryen_US
dc.subjectimplantable neural probeen_US
dc.subjectgraphene oxideen_US
dc.subjectsilk fibroinen_US
dc.subjectbiosensingen_US
dc.subjecthyperacute Strokeen_US
dc.subjectAlzheimer’s diseaseen_US
dc.subjectamyloid betaen_US
dc.title設計新穎奈米化之神經電化學界面構築於微電極陣列感測器:應用於大腦疾病診斷zh_TW
dc.titleDesign and Fabrication of Nanostructured Neurochemistry Interface with Microelectrode Sensor Array in Brain Disease Applicationsen_US
dc.typeThesisen_US
dc.contributor.department材料科學與工程學系所zh_TW
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