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  5. 透過機器學習探討桑葉清肺熱及利關節之化學參考物質
 
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透過機器學習探討桑葉清肺熱及利關節之化學參考物質

Other Title
Evaluation of Chemical Reference Substances in Mulberry Leaves Associated with Pulmonary Heat-Eliminating and Joint-Protective Effects Using Machine Learning
Type
thesis
Date Issued
2026-01-14
Author(s)
林哲羣
Advisor
王靜瓊
Subjects
系所名稱:中草藥臨床藥物研發博士學位學程
Publisher
中草藥臨床藥物研發博士學位學程
Description
學位別:博士
語文別:中文
口試委員:王靜瓊; 李佳蓉; 王三源; 林麗純; 張永勳
Abstract
桑葉為養蠶產業中的重要經濟作物,在亞洲廣泛栽種。近年研究指出,桑葉具有調節血糖和抗氧化等多項健康效益。臺灣具備適宜的氣候與地理環境,極適合桑葉栽種,顯示其具備高度的發展潛能。在中醫藥中,桑葉屬常用藥材,功能包括疏風清熱、潤肺止咳、滋陰潤燥與通利關節。良好的藥用品質則需建立在完善的品質管控之上。現行《臺灣中藥典》第四版將芸香苷 (Rutin) 列為桑葉的化學參考物質。然而,單一成分往往並不足以反映複雜天然藥材的整體藥效。因此,本研究採用化學指紋圖譜結合活性效應關聯分析,建構桑葉的完整化學特徵。運用主成分分析 (PCA)、偏最小平方法判別分析 (PLS-DA)、聚類熱圖及皮爾森相關分析,找出與化學組成與生物活性相關之關鍵標誌成分。並建立以高效液相層析 (HPLC) 指紋圖譜為基礎之人工神經網絡 (ANN) 模型,以進行品質評估。在27個樣品的熱圖分析發現,桑葉可依化學成分分為兩大類,且區辨性指標成分 (I-marker) 包括新綠原酸、隱綠原酸、綠原酸、芸香苷、異槲皮素與紫英雲苷。並以0.1%芸香苷含量作為閾值,建立了相關成分含量標誌系統。藉由ANN分析,建構出具17個相對保留時間峰值之HPLC鑑別指紋圖譜。根據此鑑別指紋確認之合格桑葉樣品,以博來霉素誘導之肺纖維化小鼠模型實驗進行驗證。結果顯示,桑葉萃取物可抑制膠原蛋白堆積並改善博來霉素誘導之肺纖維化。且相關性分析顯示,芸香苷具有抑制基質金屬蛋白酶13 (MMP-13) 基因表現之效果,而隱綠原酸則能同時抑制MMP-13與纖溶酶原活化物抑制因子-1 (Plasminogen activator inhibitor-1, PAI-1) 表現,芸香苷與隱綠原酸為評估桑葉品質之關鍵指標成分 (Key marker)。進一步,以合格桑葉樣品進行碘醋酸鈉誘導大鼠關節炎模型的功效試驗,結果顯示桑葉萃取物具有保護關節結構與減緩疼痛的功效。綜合而言,本研究透過多變量分析與機器學習技術,建立全面性的桑葉品質控制模式與鑑別指紋圖譜,並經體內藥效試驗驗證其可靠性,同時揭示桑葉具備多重活性與保健產品開發之潛力。本研究成果可作為建立天然藥材多成分品質評估體系的重要基礎。
URI
https://203.71.86.71/handle/123456789/9021

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