DSpace community: 跨領域轉譯醫學研究所

成人與青少年皮肌炎轉錄體途徑的生物資訊分析及潛在藥物預測;Bioinformatic Analysis of Transcriptomic Pathways in Adult and Juvenile Dermatomyositis with Potential Drug Prediction

title: 成人與青少年皮肌炎轉錄體途徑的生物資訊分析及潛在藥物預測;Bioinformatic Analysis of Transcriptomic Pathways in Adult and Juvenile Dermatomyositis with Potential Drug Prediction abstract: 皮肌炎（Dermatomyositis, DM）與幼年型皮肌炎（Juvenile Dermatomyositis, JDM）為一類罕見的特發性發炎性肌肉病變（Idiopathic Inflammatory Myopathies, IIMs），其特徵為骨骼肌慢性發炎與免疫反應導致的組織損傷。雖然成人與幼年型皮肌炎在臨床表現及病理組織學上有許多相似之處，但近年研究顯示兩者在病生理機轉上也存在差異。本研究目的為使用生物資訊學方法，系統性分析成人與幼年型皮肌炎的共同與特異性轉錄體特徵，並利用藥物篩選平台(drug screening platform)預測潛在的治療候選化合物。本研究自 Gene Expression Omnibus (GEO) 資料庫取得肌肉切片微陣列資料集，包括成人皮肌炎 GSE128470、GSE5370、GSE2044 及幼年型皮肌炎 GSE11971、GSE3307。利用 TAC軟體進行批次校正與差異表達基因分析（DEG analysis）。經由 Gene Ontology (GO) 與 Kyoto Encyclopedia of Genes and Genomes (KEGG) 進行功能富集分析，並透過 STRING 與 Cytoscape 建立蛋白質交互作用網路（PPI network）及篩選樞紐基因（hub genes）。候選藥物則以 LINCS L1000CDS2 平台進行預測。結果顯示，成人皮肌炎共鑑定出 850 個差異表達基因，主要富集於抗病毒、發炎與免疫相關路徑，包括第一型干擾素反應、MAPK 及 NOD-like receptor 訊號途徑。幼年型皮肌炎共鑑定出 2,544 個差異表達基因，顯示出干擾素驅動的先天免疫活化、細胞黏附、血管新生及 PI3K–Akt 訊號上調。兩組比較後共有 437 個重疊基因，顯示兩者皆具有干擾素介導之「類病毒免疫表現型」；然而，幼年型皮肌炎呈現更明顯的血管重塑與細胞黏附。樞紐基因分析指出 STAT1, DDX58, IFIH1, CXCL10, ISG15, MX1, GBP1, EIF2AK2 為疾病關鍵調控基因。藥物預測結果中，XMD-1150 與 KM 00927 同時被預測為成人與幼年型皮肌炎的共同候選治療化合物。綜合而言，本研究以整合轉錄體分析闡明了成人與幼年型皮肌炎之共同與差異的分子機制，指出干擾素介導的免疫活化為兩者共同核心特徵，而血管與細胞黏附訊號的上調則以幼年型皮肌炎較為顯著。所預測之候選藥物提供了後續實驗驗證與精準治療開發的潛在方向，對於難治型皮肌炎具有重要臨床應用價值。 ;Dermatomyositis (DM) and juvenile dermatomyositis (JDM) are rare idiopathic inflammatory myopathies characterized by chronic muscle inflammation and immune-mediated tissue injury. Despite overlapping clinical and histopathological features, increasing evidence suggests that adult and juvenile DM also possess distinct features of pathogenesis. This study aimed to systematically elucidate the shared and unique transcriptomic landscapes of DM and JDM and to predict potential therapeutic candidates through integrative bioinformatics and drug repurposing approaches. Publicly available microarray datasets of muscle biopsy specimens (GSE128470, GSE5370, and GSE2044 for DM; GSE11971 and GSE3307 for JDM) were obtained from the Gene Expression Omnibus (GEO) database. Batch correction and differential expression analyses were conducted using the Transcriptome Analysis Console (TAC) software. Functional enrichment analyses based on Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) were performed to identify key biological pathways, while protein–protein interaction (PPI) networks and hub gene analyses were conducted using STRING and Cytoscape. Candidate compounds were predicted via the LINCS L1000CDS2 platform. In DM, 850 DEGs were identified, predominantly enriched in antiviral, inflammatory, and immune signaling pathways, including type I interferon response, MAPK, and NOD-like receptor signaling. In JDM, 2,544 DEGs were identified, highlighting interferon-driven innate immunity, cell adhesion, angiogenesis, and PI3K–Akt signaling. Comparative analyses revealed 437 overlapping DEGs, underscoring a shared interferon-mediated viral-like immune signature across age groups, while JDM exhibited enhanced vascular remodeling and adhesion-related processes. Hub gene analysis identified STAT1, DDX58, IFIH1, CXCL10, ISG15, MX1, GBP1, EIF2AK2 as central regulators. Drug repurposing predicted XMD-1150 and KM 00927 as potential shared therapeutic candidates for DM and JDM. In conclusion, this integrative transcriptomic study delineates both shared and distinct molecular pathways in DM and JDM, highlighting interferon-driven immune activation as a common hallmark and vascular-adhesion signaling as a distinguishing feature in JDM. The predicted compounds provide a foundation for future experimental validation and development of targeted therapies in refractory dermatomyositis.

探討增強型體外反搏系統介入對心力指標與相關健康因素之影響;Effects of Enhanced External Counterpulsation on Cardiac Force Index and Related Health Factors

title: 探討增強型體外反搏系統介入對心力指標與相關健康因素之影響;Effects of Enhanced External Counterpulsation on Cardiac Force Index and Related Health Factors abstract: 增強型體外反搏（Enhanced External Counterpulsation, EECP）為非侵入性心血管療法，其在非典型族群之療效與評估之指標仍待釐清。本研究旨在評估 EECP 對心力指標（Cardiac Force Index, CFI）的影響，並分析其在長新冠、亞健康狀態及高認知負荷族群中的臨床應用價值。本研究整合四項實驗性研究，涵蓋長新冠患者、亞健康族群、職業圍棋選手與空軍飛行員，以CFI、腦血流造影（Hemoencephalography, HEG）、生活品質、睡眠品質指標等多元工具，並採兩種每次時長（2 小時 vs 1 小時）之 EECP 介入模式，以評估劑量–反應關係。各族群心力指標皆顯著提升（p < 0.05）；在高認知負荷族群，CFI 於累積18 小時後達峰值，增幅12%（p < 0.001）。HEG 獲得提升，且與疲勞感降低及腦霧症狀減少呈顯著相關（p = 0.017）。生活品質指標均顯著改善（p < 0.001），睡眠品質指標於介入後一個月提升5.40 分。整體而言，介入次數和累積總時數對療效的影響較每週頻率或單次時長更為關鍵。研究均未發生嚴重不良反應。 EECP 可於不同族群中提升 CFI 與 HEG，呈現明確之劑量–反應關係。而 CFI 具良好敏感度，適合作為 EECP 療效之評估指標。研究支持 EECP 具跨系統整合潛力，可應用於心血管功能不全、長新冠及亞健康族群中；未來可望拓展至慢性傷口等族群，為臨床治療提供更多選擇。 ;Enhanced external counterpulsation (EECP) is a noninvasive cardiovascular therapy whose efficacy and evaluative metrics in non-traditional populations remain to be clarified. This study aimed to assess the effects of EECP on the Cardiac Force Index (CFI) and to examine its clinical utility among individuals with long COVID, suboptimal health status, and populations with high cognitive demands. We integrated four experimental studies encompassing patients with long COVID, individuals with suboptimal health status, professional Go players, and Air Force pilots. Multimodal assessments included CFI, hemoencephalography (HEG), quality-of-life measures, and sleep-quality indices. Two EECP session-duration regimens (2 h vs 1 h) were used to evaluate the dose–response relationship. CFI increased significantly across all cohorts (p < 0.05). In high cognitive-demand populations, CFI peaked after 18 cumulative hours of EECP, with a 12% increase (p < 0.001). HEG improved and were significantly associated with reductions in fatigue and brain-fog symptoms (p = 0.017). Quality-of-life outcomes improved (p < 0.001), and sleep-quality scores increased by 5.40 points one month after the intervention. Overall, the number of sessions and the total cumulative hours have a greater impact on treatment efficacy than weekly frequency or the duration of individual sessions. No serious adverse events were reported. EECP enhanced CFI and HEG across diverse populations and demonstrated a clear dose–response relationship. CFI showed good sensitivity and is suitable as an outcome measure for evaluating EECP efficacy. EECP appears applicable to individuals with cardiovascular dysfunction, long COVID, and suboptimal health status, with potential extension to patients with chronic wounds.

應用相干向量映射法前瞻性評估持續性心房顫動的致心律不整波動動態;Prospective Evaluation of Arrhythmogenic Wave Dynamics in Persistent Atrial Fibrillation Using Coherence Vector Mapping

title: 應用相干向量映射法前瞻性評估持續性心房顫動的致心律不整波動動態;Prospective Evaluation of Arrhythmogenic Wave Dynamics in Persistent Atrial Fibrillation Using Coherence Vector Mapping abstract: 持續性心房顫動是全球最常見的心律不整之一，亦為導致心衰竭、中風與死亡率增加的主要病因。其病理機轉牽涉旋轉波、發散波前與心房組織電生理特性之空間異質性，導致現有驅動源定位與波動重建技術，在穩定性、解析度與臨床適用性方面皆面臨挑戰。本研究首先針對既有轉子定位與向量場重建方法進行評估與模擬驗證。比較現有的心房顫動序列偵測演算法在不同導管設計下之偵測限制，並透過模擬轉子的旋轉波與擴散模擬，建立兩項幾何指標：「轉子指數」與「擴散源指數」。研究證實，這些指標能有效量化波前動態特性，並適用於不同幾何構型的導管，提供導管設計的幾何建議與準確識別驅動源的可行依據。接著進一步導入過往臨床電燒的成功經驗於人工智能模型，建立以深度學習預測心房顫動源的決策系統DeePRISM。在前瞻性研究中，DeePRISM導引消融可顯著提升長期無心律不整發生率；在模擬的轉子自放電模型中亦顯示，DeePRISM模型所預測的心房顫動區域與轉子的核心區域高度吻合，顯示深度學習模型於電生理導引治療中的潛力。最後我們提出一項創新技術：「主導方向相干性向量(Principal Directed Coherence Vector, PDCV)分析法」，此方法結合時序因果性與空間向量場重建，建構可視化的心房波前傳導地圖，並揭示驅動源與其下游區域之因果流向。與傳統Granger因果分析相比，PDCV不僅適用於非同步、低密度導管資料，更可於旋轉與放射波場中穩定辨識驅動源核心。臨床驗證亦顯示，心房顫動患者的PDCV呈現肺靜脈具「外傳導」特性，則其接受肺靜脈隔離術後具較高心房顫動終止率與長期穩定性，該特徵亦為復發風險的獨立預測因子。綜合而言，本研究從過往的心房顫動序列分析方法出發，結合深度學習模型與因果場重建技術，建立具多層次分析能力的心房顫動驅動源定位架構。此方法不僅可作為個人化消融策略的輔助依據，亦展現優於現行商用系統之穩定性與靈敏度，未來可望應用於臨床電生理導航、基質修飾策略優化與心律不整機轉研究等多元場域。 ;Persistent atrial fibrillation (AF) is one of the most common arrhythmias worldwide and a leading cause of heart failure, stroke, and increased mortality. Its underlying mechanisms involve complex interactions among rotors, divergent wavefronts, and spatial heterogeneity of atrial tissue electrophysiology. These factors pose significant challenges to current rotor localization and wavefront reconstruction techniques in terms of stability, spatial resolution, and clinical applicability. This study first evaluates and simulates existing rotor detection and vector field reconstruction methods. By comparing common AF sequence-based detection algorithms under different catheter configurations, we identified critical limitations in accuracy and robustness. To address these gaps, we developed two novel geometric indices the Rotor Index (RI) and the Focal Index (FI) using simulated rotor and divergent source models. These indices effectively quantify wavefront dynamics and provide practical guidance for catheter design and rotor localization across varying electrode geometries. Building upon prior clinical ablation experiences, we then developed a deep learning-based decision support system, DeePRISM, designed to predict atrial fibrillation driver. In a prospective clinical study, DeePRISM-guided ablation significantly improved long-term arrhythmia-free survival. Moreover, in simulated spontaneous rotor models, the regions predicted by DeePRISM closely matched the rotor core, highlighting its potential as an intelligent tool for electrophysiological guidance. Finally, we proposed a novel analysis method, the Principal Directed Coherence Vector (PDCV) approach, which integrates temporal causality with spatial vector field reconstruction to visualize the directionality and influence of atrial wavefront propagation. Compared to traditional Granger causality, PDCV accommodates asynchronous and low-density catheter recordings and demonstrates superior stability in identifying rotor cores in both rotational and focal wavefront fields. Clinical validation further showed that patients exhibiting “outward propagation” from the pulmonary veins in PDCV maps experienced higher termination rates and greater long-term rhythm stability after pulmonary vein isolation, with this feature serving as an independent predictor of AF recurrence. In conclusion, this study combines traditional AF signal analysis with deep learning and causal vector field techniques to establish a multi-layered framework for rotor localization and personalized ablation planning. The proposed methods not only outperform existing commercial systems in stability and sensitivity but also hold promise for future applications in clinical EP navigation, substrate modification strategies, and arrhythmia mechanism research.

以穿戴式隨身裝置引導呼吸訓練作為心血管疾病自主神經調節的輔助治療模式;Wearable Device Guided Breathing Training Exercise as an Auxiliary Management of Autonomic Nervous Modulation in Cardiovascular Disease

title: 以穿戴式隨身裝置引導呼吸訓練作為心血管疾病自主神經調節的輔助治療模式;Wearable Device Guided Breathing Training Exercise as an Auxiliary Management of Autonomic Nervous Modulation in Cardiovascular Disease abstract: 本研究探討了在心血管疾病族群中，其自主神經系統功能、慢性發炎和血管硬化之間的關係，並評估了以穿戴式隨身裝置上的應用程式所引導的呼吸訓練模式作為輔助治療的有效性。透過四個實驗項目，我們納入了130名慢性心血管疾病病人族群和34名健康對照者，使用穿戴式心電圖裝置評估受試者的自主神經功能。蒐集以心率變異度為基本的指標參數加以推演計算，包括生理年齡及其綜合健康指數。結果顯示，與單純高血壓病人相比，合併高血壓和糖尿病病人的生理年齡指標顯著升高，而綜合健康指數則顯著降低。心臟衰竭病人在接受呼吸訓練輔助治療後，以上兩項參數均顯著改善。三個月的呼吸訓練顯著降低了血壓及腫瘤壞死因子-α (TNF-α) 數值，但壓力反射敏感性的改善並非持久的。綜合健康指數被證明比傳統的心率變異度參數指標測量方法更可靠、更靈敏，可用於短期自主神經評估。以上結果顯示，穿戴式心電圖監測隨身裝置結合呼吸訓練模式，為慢性心血管疾病的風險管理和治療監測提供了一種非侵入性的持續方向，並為疾病初期之亞健康族群的健康促進提供了可行的未來前景。;This study investigated the relationship between autonomic nervous system function, chronic inflammation, and vascular stiffness in cardiovascular disease (CVD) patients, while evaluating the effectiveness of app-guided breathing training exercise as an auxiliary treatment. Through four experimental projects involving 130 CVD patients and 34 healthy controls, we assessed autonomic function using a wearable electrocardiogram (ECG) device that calculated heart rate variability (HRV) based parameters including physiological age and a comprehensive health index. Results showed that patients with hypertension and diabetes had significantly higher physiological age and lower comprehensive index compared to hypertension only patients. Heart failure patients demonstrated significant improvement in both parameters following treatment. Three months of breathing training significantly reduced blood pressure and tumor necrosis factor-α levels, though baroreflex sensitivity improvements were not sustained. The comprehensive index proved more reliable and sensitive than traditional HRV measures for short-term autonomic assessment. These findings suggest that wearable ECG monitoring combined with breathing training offers a promising non-invasive approach for cardiovascular risk management and treatment monitoring. It could be provided a sustained direction for health promotion in subclinical population.