S'identifier

Chinese Academy of Sciences, China

2 ARTICLES PUBLISHED IN JoVE

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Engineering

Electrospray Deposition of Uniform Thickness Ge23Sb7S70 and As40S60 Chalcogenide Glass Films
Spencer Novak 1, Pao-Tai Lin 2,3, Cheng Li 4, Nikolay Borodinov 1, Zhaohong Han 5, Corentin Monmeyran 5, Neil Patel 5, Qingyang Du 5, Marcin Malinowski 4, Sasan Fathpour 4, Chatdanai Lumdee 4, Chi Xu 4, Pieter G. Kik 4, Weiwei Deng 6, Juejun Hu 7, Anuradha Agarwal 7, Igor Luzinov 1, Kathleen Richardson 4
1Department of Materials Science and Engineering, Clemson University, 2Department of Materials Science and Engineering, Texas A&M University, 3Department of Electrical and Computer Engineering, Texas A&M University, 4College of Optics and Photonics, Center for Research and Education in Optics and Lasers (CREOL), University of Central Florida, 5Department of Materials Science and Engineering, Massachusetts Institute of Technology, 6Department of Mechanical Engineering, Virginia Polytechnic Institute, 7Microphotonics Center, Massachusetts Institute of Technology

A method of uniform thickness solution-derived chalcogenide glass film deposition is demonstrated using computer numerical controlled motion of a single-nozzle electrospray.

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Environment

A High-throughput Assay for the Prediction of Chemical Toxicity by Automated Phenotypic Profiling of Caenorhabditis elegans
Shan Gao *1, Weiyang Chen *2, Nan Zhang 1, Chi Xu 3, Haiming Jing 1,4, Wenjing Zhang 1,4, Gaochao Han 1,4, Matthew Flavel 5, Markandeya Jois 5, Yingxin Zeng 1, Jing-Dong J. Han 3, Bo Xian 3, Guojun Li 1,4
1Beijing Key Laboratory of Diagnostic and Traceability Technologies for Food Poisoning, Beijing Center for Disease Prevention and Control/Beijing Center of Preventive Medicine Research, China, 2College of Computer Science and Technology, Qilu University of Technology(Shandong Academy of Sciences), China, 3Key Laboratory of Computational Biology, CAS Center for Excellence in Molecular Cell Science, Collaborative Innovation Center for Genetics and Developmental Biology, Chinese Academy of Sciences-Max Planck Partner Institute for Computational Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, China, 4Beijing Key Laboratory of Environmental Toxicology, School of Public Health, Capital Medical University, China, 5School of Life Sciences, La Trobe University, Australia

A quantitative method has been developed to identify and predict the acute toxicity of chemicals by automatically analyzing the phenotypic profiling of Caenorhabditis elegans. This protocol describes how to treat worms with chemicals in a 384-well plate, capture videos, and quantify toxicological related phenotypes.

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