本研究預計將確立特定轉錄調控在人類泌尿上皮細胞癌的細胞模式以及小鼠模式中所造成的效果及其作用機轉。 在學術發展方面：本研究所建立的模型亦可用於探討其他新興癌症治療標的，且CDK12/13之功能性差異探討將有助於在其他癌症靶向此二目標。 在經濟層面：本研究預計將發展新的泌尿上皮細胞癌治療標靶，轉錄體學分析可能會找到其他未曾探討的新標的，若將來本研究進入臨床前期測試，相關研究數據亦可作為參考。 在社會層面：由臨床檢體以及公開資料庫的分析可以推估本研究對臨床病人的助益。

We propose a novel approach for PDAC detection in clinical applications, leveraging the combined power of metabolomics, proteomics, clinical data, biochemical biomarkers, and machine learning. This hybrid AI model will integrate diverse information layers, including metabolic and proteomic profiles, patient clinical parameters (age, gender, smoking status, BMI, HbA1c, or GluAC), and established PDAC markers, to achieve superior diagnostic accuracy and sensitivity compared to traditional methods. This integrated approach can potentially revolutionize PDAC detection, leading to earlier intervention and improved patient outcomes. Furthermore, the scientific findings of the project can undergo cross-validation in both Taiwan and Lithuania, suggesting their potential applicability worldwide to benefit diverse populations. Enhanced international cooperation among medical institutes could facilitate the validation of these results.

肥厚型心肌病（HCM）是年輕人心因性猝死（SCD）的重要因素，也是重要的公共衛生議題。但對於HCM病人SCD的真實機轉，以及預測因子，基因影響，篩檢的效度目前仍不明，本計畫提出由於肌肉纖維的紊亂和纖維化引起的機械電相互作用，因而產生再極化異質性可能是關鍵的病理機轉。因此此計畫第一部分將以通過人工智慧建立心電圖風險評分，以識別學校ECG篩查中識別的HCM中的高風險群體，第二部分將進行心臟核磁共振影像，多層組織都卜勒應變，和血清纖維化標記，以評估心肌的紊亂收縮及與再極化異常和生命威脅事件的關聯。也將進行全外顯子序列分析，並研究遺傳性心律不整基因與小兒科HCM中生命威脅事件的關聯。

Pei-Lin Lee serves as Clinical Associate Professor, School of Medicine, National Taiwan University; Consultant, Center of Sleep Disorder, National Taiwan University Hospital. Her current academic positions at international sleep societies include American Academy of Sleep Medicine Fellow and Co-Chair International Assembly; Asian Society of Sleep Medicine, Sleep Medicine Education Task Force committee member. Her current research focuses on the era of new technology and big data in sleep medicine; and intervention on sleep and metabolism in sleep disordered breathing.