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Your search keyword '"Huang, Yuan-Jiao"' showing total 17 results
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17 results on '"Huang, Yuan-Jiao"'

1. A novel fluorescent dye selectively images and kills cancer stem cells by targeting mitochondria: Evidence from a cell line‑based zebrafish xenograft model

Author

Ren, Tao, primary, Yang, Meng-Zhe, additional, Zhang, Wei-Ming, additional, Qin, Liu-Jie, additional, Zhou, Shou-Chang, additional, Cheng, Nan-Nan, additional, Huang, Yuan-Jiao, additional, Sun, Jing, additional, Xu, Ning, additional, Sun, Hua-Bing, additional, and Zhang, Bei-Bei, additional

Published
2023
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9. SELDI-TOF MS profiling of serum for detection of nasopharyngeal carcinoma

Author

He Min, Deng Kai-Feng, Liao Ming, Zhang Bei-Bei, Xuan Chao, Huang Yuan-Jiao, and Zhao Jin-Min

Subjects
Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282
Abstract

Abstract Background No satisfactory biomarkers are currently available to screen for nasopharyngeal carcinoma (NPC). We have developed and evaluated surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF MS) for detection and analysis of multiple proteins for distinguishing individuals with NPC from control individuals. Methods A preliminary learning set and a classification tree of spectra derived from 24 patients with NPC and a group of 24 noncancer controls were used to develop a proteomic model that discriminated cancer from noncancer effectively. Then, the validity of the classification tree was challenged with a blind test set, which included another 20 patients with NPC and 12 noncancer controls. Results A panel of 3 biomarkers ranging m/z 3–20 k was selected to establish Decision Tree model by BPS with sensitivity of 91.66% and specificity of 95.83%. The ability to detect NPC patients was evaluated, a sensitivity of 95.0% and specificity of 83.33% were validated in blind testing set. Conclusion This high-flux proteomic classification system will provide a highly accurate and innovative approach for the detection/diagnosis of NPC.

Published
2009
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