Accedi

Chinese Academy of Sciences, China

2 ARTICLES PUBLISHED IN JoVE

Engineering

Electrospray Deposition of Uniform Thickness Ge₂₃Sb₇S₇₀ and As₄₀S₆₀ Chalcogenide Glass Films

Spencer Novak¹, Pao-Tai Lin^2,3, Cheng Li⁴, Nikolay Borodinov¹, Zhaohong Han⁵, Corentin Monmeyran⁵, Neil Patel⁵, Qingyang Du⁵, Marcin Malinowski⁴, Sasan Fathpour⁴, Chatdanai Lumdee⁴, Chi Xu⁴, Pieter G. Kik⁴, Weiwei Deng⁶, Juejun Hu⁷, Anuradha Agarwal⁷, Igor Luzinov¹, Kathleen Richardson⁴

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.

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 Zhang¹, Chi Xu³, Haiming Jing^1,4, Wenjing Zhang^1,4, Gaochao Han^1,4, Matthew Flavel⁵, Markandeya Jois⁵, Yingxin Zeng¹, Jing-Dong J. Han³, Bo Xian³, 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.