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Chun-Yu Liu,Tzu-Ting Huang,Pei-Yi Chu,Chun-Teng Huang,Chia-Han Lee,Wan-Lun Wang,Ka-Yi Lau,Wen-Chun Tsai,Tzu-I Chao,Jung-Chen Su,Ming-Huang Chen,Chung-Wai Shiau,Ling-Ming Tseng,Kuen-Feng Chen 생화학분자생물학회 2017 Experimental and molecular medicine Vol.49 No.-
Triple-negative breast cancer (TNBC) remains difficult to treat and urgently needs new therapeutic options. Nintedanib, a multikinase inhibitor, has exhibited efficacy in early clinical trials for HER2-negative breast cancer. In this study, we examined a new molecular mechanism of nintedanib in TNBC. The results demonstrated that nintedanib enhanced TNBC cell apoptosis, which was accompanied by a reduction of p-STAT3 and its downstream proteins. STAT3 overexpression suppressed nintedanib-mediated apoptosis and further increased the activity of purified SHP-1 protein. Moreover, treatment with either a specific inhibitor of SHP-1 or SHP-1-targeted siRNA reduced the apoptotic effects of nintedanib, which validates the role of SHP-1 in nintedanib-mediated apoptosis. Furthermore, nintedanib-induced apoptosis was attenuated in TNBC cells expressing SHP-1 mutants with constantly open conformations, suggesting that the autoinhibitory mechanism of SHP-1 attenuated the effects of nintedanib. Importantly, nintedanib significantly inhibited tumor growth via the SHP-1/p-STAT3 pathway. Clinically, SHP-1 levels were downregulated, whereas p-STAT3 was upregulated in tumor tissues, and SHP-1 transcripts were associated with improved disease-free survival in TNBC patients. Our findings revealed that nintedanib induces TNBC apoptosis by acting as a SHP-1 agonist, suggesting that targeting STAT3 by enhancing SHP-1 expression could be a viable therapeutic strategy against TNBC.
Quantifying and Clustering Texture Traits in Flowers of Genus Sinningia
( Tzu-ting Hung ),( Hao-chun Hsu ),( Yan-fu Kuo ) 한국농업기계학회 2018 한국농업기계학회 학술발표논문집 Vol.23 No.1
The flowers of genus Sinningia has a high degree of diversity in stripe and spot patterns. Delimiting these pattern as textural traits usually rely on horticulturalists’ judgment. However, the judgment by intuitive observation is subjective. This study aimed to quantify the stripe and spot pattern of genus Sinningia flowers automatically using machine vision and to cluster the textural traits using machine learning. The image of ventral petal was acquired using flatbed scanners. Two regions of interest (ROI), lobe region and tube region, were identified and were used for the feature quantification. The features of stripe and spot patterns were then quantified from the ROI using Gabor and Laplacian of Gaussian filters, respectively. The k-means clustering algorithm was next applied to the feature of patterns. The clusters were significantly associated with the textural traits.
Implementation of a bio-inspired two-mode structural health monitoring system
Tzu-Kang Lin,Li-Chen Yu,Kuo-Chun Chang,Anne Kiremidjian,Chang-Hung Ku 국제구조공학회 2011 Smart Structures and Systems, An International Jou Vol.8 No.1
A bio-inspired two-mode structural health monitoring (SHM) system based on the Naïve Bayes (NB) classification method is discussed in this paper. To implement the molecular biology based Deoxyribonucleic acid (DNA) array concept in structural health monitoring, which has been demonstrated to be superior in disease detection, two types of array expression data have been proposed for the development of the SHM algorithm. For the micro-vibration mode, a two-tier auto-regression with exogenous (AR-ARX)process is used to extract the expression array from the recorded structural time history while an ARX process is applied for the analysis of the earthquake mode. The health condition of the structure is then determined using the NB classification method. In addition, the union concept in probability is used to improve the accuracy of the system. To verify the performance and reliability of the SHM algorithm, a downscaled eight-storey steel building located at the shaking table of the National Center for Research on Earthquake Engineering (NCREE) was used as the benchmark structure. The structural response from different damage levels and locations was collected and incorporated in the database to aid the structural health monitoring process. Preliminary verification has demonstrated that the structure health condition can be precisely detected by the proposed algorithm. To implement the developed SHM system in a practical application, a SHM prototype consisting of the input sensing module, the transmission module, and the SHM platform was developed. The vibration data were first measured by the deployed sensor, and subsequently the SHM mode corresponding to the desired excitation is chosen automatically to quickly evaluate the health condition of the structure. Test results from the ambient vibration and shaking table test showed that the condition and location of the benchmark structure damage can be successfully detected by the proposed SHM prototype system, and the information is instantaneously transmitted to a remote server to facilitate real-time monitoring. Implementing the bio-inspired two-mode SHM practically has been successfully demonstrated.
An Efficient Parallel Machine Learning-based Blockchain Framework
Chun-Wei Tsai,Yi-Ping Chen,Tzu-Chieh Tang,Yu-Chen Luo 한국통신학회 2021 ICT Express Vol.7 No.3
The unlimited possibilities of machine learning have been shown in several successful reports and applications. However, how to make sure that the searched results of a machine learning system are not tampered by anyone and how to prevent the other users in the same network environment from easily getting our private data are two critical research issues when we immerse into powerful machine learning-based systems or applications. This situation is just like other modern information systems that confront security and privacy issues. The development of blockchain provides us an alternative way to address these two issues. That is why some recent studies have attempted to develop machine learning systems with blockchain technologies or to apply machine learning methods to blockchain systems. To show what the combination of blockchain and machine learning is capable of doing, in this paper, we proposed a parallel framework to find out suitable hyperparameters of deep learning in a blockchain environment by using a metaheuristic algorithm. The proposed framework also takes into account the issue of communication cost, by limiting the number of information exchanges between miners and blockchain.
( Chun-chi Lin ),( Shu-chen Wei ),( Been-ren Lin ),( Wen-sy-tsai ),( Jinn-shiun Chen ),( Tzu-chi Hsu ),( Wei-chen Lin ),( Tien-yu Huang ),( Te-hsin Chao ),( Hung-hsin Lin ),( Jau-min Wong ),( Jen-kou 대한장연구학회 2016 Intestinal Research Vol.14 No.3
Background/Aims: With the recent progress in medical treatment, surgery still plays a necessary and important role in treating ulcerative colitis (UC) patients. In this study, we analyzed the surgical results and outcomes of UC in Taiwan in the recent 20 years, via a multi-center study through the collaboration of Taiwan Society of IBD. Methods: A retrospective analysis of surgery data of UC patients from January 1, 1995, through December 31, 2014, in 6 Taiwan major medical centers was conducted. The patients’ demographic data, indications for surgery, and outcome details were recorded and analyzed. Results: The data of 87 UC patients who received surgical treatment were recorded. The median post-operative follow-up duration was 51.1 months and ranged from 0.4 to 300 months. The mean age at UC diagnosis was 45.3±16.0 years and that at operation was 48.5±15.2 years. The 3 leading indications for surgical intervention were uncontrolled bleeding (16.1%), perforation (13.8%), and intractability (12.6%). In total, 27.6% of surgeries were performed in an emergency setting. Total or subtotal colectomy with rectal preservation (41.4%) was the most common operation. There were 6 mortalities, all due to sepsis. Emergency operation and low pre-operative albumin level were significantly associated with poor survival (P =0.013 and 0.034, respectively). Conclusions: In the past 20 years, there was no significant change in the indications for surgery in UC patients. Emergency surgeries and low pre-operative albumin level were associated with poor survival. Therefore, an optimal timing of elective surgery for people with poorly controlled UC is paramount.
Tzu-Yi Lin,Eugene Yu-Chuan Kang,Shih-Chieh Shao,Edward Chia-Cheng Lai,Sunir J. Garg,Kuan-Jen Chen,Je-Ho Kang,Wei-Chi Wu,Chi-Chun Lai,Yih-Shiou Hwang 대한당뇨병학회 2023 Diabetes and Metabolism Journal Vol.47 No.3
Background: To compare risk of diabetic retinopathy (DR) between patients taking sodium-glucose cotransporter-2 inhibitors (SGLT2is) and those taking glucagon-like peptide-1 receptor agonists (GLP1-RAs) in routine care.Methods: This retrospective cohort study emulating a target trial included patient data from the multi-institutional Chang Gung Research Database in Taiwan. Totally, 33,021 patients with type 2 diabetes mellitus using SGLT2is and GLP1-RAs between 2016 and 2019 were identified. 3,249 patients were excluded due to missing demographics, age <40 years, prior use of any study drug, a diagnosis of retinal disorders, a history of receiving vitreoretinal procedure, no baseline glycosylated hemoglobin, or no follow-up data. Baseline characteristics were balanced using inverse probability of treatment weighting with propensity scores. DR diagnoses and vitreoretinal interventions served as the primary outcomes. Occurrence of proliferative DR and DR receiving vitreoretinal interventions were regarded as vision-threatening DR.Results: There were 21,491 SGLT2i and 1,887 GLP1-RA users included for the analysis. Patients receiving SGLT2is and GLP-1 RAs exhibited comparable rate of any DR (subdistribution hazard ratio [SHR], 0.90; 95% confidence interval [CI], 0.79 to 1.03), whereas the rate of proliferative DR (SHR, 0.53; 95% CI, 0.42 to 0.68) was significantly lower in the SGLT2i group. Also, SGLT2i users showed significantly reduced risk of composite surgical outcome (SHR, 0.58; 95% CI, 0.48 to 0.70).Conclusion: Compared to those taking GLP1-RAs, patients receiving SGLT2is had a lower risk of proliferative DR and vitreoretinal interventions, although the rate of any DR was comparable between the SGLT2i and GLP1-RA groups. Thus, SGLT2is may be associated with a lower risk of vision-threatening DR but not DR development.