13856 research outputs found
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[[alternative]]System for destroying adipose tissue non-invasively and accelerating lipid metabolism
No full text[[abstract]]本發明係使用聚焦超音波以非侵入方式破壞脂肪組織並以新式聚焦超音波之合成及電刺激來增加治療效率。脂質可自被破壞的脂肪細胞釋出並留在未被破壞的脂肪細胞間。在施行聚焦超音波當中或之後，針對大腿或其他部位之肌肉以電刺激進行被動伸縮以消耗能量。因此，游離之脂質藉提供肌肉能量以增進代謝。本發明之超音波療程可以增加治療區域，另因其結合電刺激，可有效地將脂質自循環系統排除
[[alternative]]Method for automatically recording circadian rhythm of user via portable device and portable device thereof
No full text[[abstract]]本發明係一種利用攜帶裝置自動記錄使用者晝夜節律(circadian rhythm)的方法及其攜帶裝置，包括於評估期間內獲取攜帶裝置的複數使用區間，各使用區間係指在評估期間內螢幕每次從被開啟直至關閉的時間，所有的使用區間再以螢幕被開啟前是否有通知訊息，而被分類為複數個主動使用區間以及複數個被動使用區間，利用各主動使用區間產生每日的活躍期及非活躍期，且利用各非活躍期評估出使用者的每日睡眠指標。換言之，本發明係以記錄使用者開啟及關閉螢幕的使用行為，評估使用者的每日睡眠指標
Anti-abeta antibodies and uses thereof
No full text[[abstract]]An isolated antibody, comprising a light-chain CDR1 (L-CDR1) having the sequence of SEQ ID NO: 1, SEQ ID NO: 7, or SEQ ID NO: 14; a light-chain CDR2 (L-CDR2) having the sequence of SEQ ID NO: 2 or SEQ ID NO: 15; a light-chain CDR3 (L-CDR3) having the sequence of SEQ ID NO: 3, SEQ ID NO: 8, SEQ ID NO: 21, or SEQ ID NO: 24; a heavy-chain CDR1 (H-CDR1) having the sequence of SEQ ID NO: 4, SEQ ID NO: 9, SEQ ID NO: 11, SEQ ID NO: 16, or SEQ ID NO: 25; a heavy-chain CDR2 (H-CDR2) having the sequence of SEQ ID NO: 5, SEQ ID NO: 12, SEQ ID NO: 17, SEQ ID NO: 19, SEQ ID NO: 22, or SEQ ID NO: 26; and a heavy-chain CDR3 (H-CDR3) having the sequence of SEQ ID NO: 6, SEQ ID NO: 10, SEQ ID NO: 13, SEQ ID NO: 18, SEQ ID NO: 20, SEQ ID NO: 23, or SEQ ID NO: 27, wherein the antibody specifically binds to ?ß1-42 or an N-terminal modified form thereof
Dipicolylamine derivatives and their pharmaceutical uses
No full text[[abstract]]Dipicolylamine compounds of Formula (I) set forth herein. Also disclosed are pharmaceutical compositions containing metal ions and these compounds. Further disclosed is a method for treating a condition associated with cells containing inside-out phosphatidylserine, with these compounds
Dipicolylamine derivatives and their pharmaceutical uses
No full text[[abstract]]Dipicolylamine compounds of Formula (I) set forth herein. Also disclosed are pharmaceutical compositions containing metal ions and these compounds. Further disclosed is a method for treating a condition associated with cells containing inside-out phosphatidylserine, with these compounds
二甲基吡啶胺衍生物及其医药用途
No full text[[abstract]]本发明提供一种式(I)的二甲基吡啶胺化合物，另提供一种包含金属离子和这类化合物的药物组合物，再提供一种使用这类化合物治疗与含磷脂质丝胺酸进出的细胞相关病症的方法
Pyrazole compounds
No full text[[abstract]]Disclosed are pyrazole compounds, encompassed by formula (I) shown in the Specification, useful for treating peripheral cannabinoid 1 receptor mediated disorders. Also disclosed are pharmaceutical compositions and methods related to use of these compounds
[[alternative]]Heterocyclic compounds and use thereof
No full text[[abstract]]本發明係關於式(I)之雜環化合物，另揭露包含該雜環化合物之醫藥組成物以及使用該雜環化合物驅使造血幹細胞(HSC)及內皮前驅細胞(EPC)進入周邊血液循環的方法。本發明更提供一種使用該雜環化合物治療組織損傷、癌症、發炎性疾病、或自體免疫性疾病的方法
Integrating ultrabright polymer dots and stereo NIR-II imager for assessing anti-angiogenic drugs in oral cancer model
No full text[[abstract]]The development of efficient platforms for the evaluation of anti-angiogenic agents is critical in advancing cancer therapeutics. In this study, we exploited an ultrabright semiconducting polymer dots (Pdots) integrating with a three-dimensional (3D) near-infrared-II (NIR-II) fluorescence imaging system designed to assess the efficacy of potent anti-angiogenic agents PX-478 and BPR0C261 in an oral squamous cell carcinoma (OSCC) tumour model, which depends on angiogenesis for dissemination. PX-478, a hypoxia-inducible factor-1 alpha (HIF-1 alpha) inhibitor, and BPR0C261, a microtubule-disrupting agent, were administrated into tumour-bearing mice established using murine MTCQ1 tongue cancer cells through intraperitoneal injection and oral gavage, respectively. Our findings showed that PX-478 and BPR0C261 significantly inhibited tumour growth and extended the life span of tumour-bearing mice without decreasing the body weights. The Pdots-based NIR-II vascular imaging demonstrated that the tumour vascularity was suppressed by PX-478 and BPRC0261. Accordingly, the excised tumours treated with anti-angiogenic agents showed less blood vessels than that treated with vehicles. The expression of endothelial markers CD31 was also found to be reduced in tumours treated with PX-478 and BPRC0261 using immunohistochemical (IHC) staining and Western blot analysis. Furthermore, PX-478 could suppress the expression of HIF-1 alpha and vascular endothelial growth factor-A (VEGF-A), but BPRC0261 only suppressed VEGF-A. Taken together, this innovative 3D NIR-II imaging system combining the biocompatible Pdots with unique optical specificity enables non-invasive, real-time monitoring the efficacy of anti-angiogenic compounds
Effects of feature selection methods in estimating SO2 concentration variations using machine learning and stacking ensemble approach
No full text[[abstract]]Statistical-based feature selection methods have been used for dimension reduction, but only a few studies have explored the impact of selected features on machine learning models. This study aims to investigate the effects of statistical and machine learning-based feature selection methods on spatial prediction models for estimating variations in SO2 concentrations. We collected daily SO2 observations from 1994 to 2018 along with predictor variables such as land-use/land cover allocations, roads, landmarks, meteorological factors, and satellite images, resulting in a total of 428 geographic predictors. Important features were identified using statistical-based feature selection methods including SelectKBest, stepwise feature selection, elastic net, and machine learning-based methods such as random forest. The selected features from the four feature selection methods were fitted to machine learning algorithms including gradient boosting, Cat- Boost, XGBoost, and stacking ensemble to establish prediction models for estimating SO2 concentrations. SHapley Additive exPlanations (SHAP) was applied to explain the contribution of each selected feature to the model's prediction capability. The results showed that stacking ensemble model outperformed the three single machine learning algorithms. Among the four feature selection methods, the random forest method yielded the highest prediction accuracy (R2=0.80) in the training model, followed by stepwise selection (R2=0.75), SelectKBest (R2=0.75), and elastic net (R2=0.72) in the stacking ensemble model. These results were robust after several validation tests. Our findings suggested that the random forest feature selection method was more suitable for developing machine learning models for air pollution estimation. The identified features also provide important information for urban air pollution management