Bacterial Microbiota in Unfed Ticks (Dermacentor nuttalli) From Xinjiang Detected Through 16S rDNA Amplicon Sequencing and Culturomics https://doi.org/10.15212/ZOONOSES-2021-0007 Announcing a new article publication for Zoonoses journal. Ruifu Yang and colleagues from Beijing Institute of Microbiology and Epidemiology, Beijing, China, Xinjiang University, Urumqi, China and The Center for Disease Control and Prevention of Xinjiang Uygur Autonomous Region, Urumqi, China review bacterial microbiota in unfed ticks (Dermacentor nuttalli) from Xinjiang detected through 16S rDNA Amplicon sequencing and culturomics.

A new algorithm has been designed to help discover previously unknown material compounds. It was developed by a team from Martin Luther University Halle-Wittenberg (MLU), Friedrich Schiller University Jena and Lund University in Sweden. The researchers designed a form of artificial intelligence (AI) based on machine learning that can perform complex calculations within a very short space of time. This has enabled the team to identify several thousand potential new compounds using a computer. The study was published in the journal "Science Advances".

New technology could help doctors make the most of limited resources during the COVID-19 pandemic by identifying patients who require intensive care unit treatment.

The OIST Innovation Square Startup Accelerator Program is now accepting applications for its 2022 intake, with the recruitment period open from Dec 6, 2021 to Feb 4, 2022. Successful applicants will be awarded up to 10 million yen and have the opportunity to incubate their startups at the Okinawa Institute of Science and Technology in Okinawa, Japan.