Improvement in image quality via the pseudo confocal effect in multidirectional digital scanned laser light-sheet microscopy

Our TL Onami and DR Kaneshiro (Laboratory for Comprehensive Bioimaging, RIKEN BDR) et al. proposed a new pseudo confocal system that combines multiline scanning for light-sheet illumination combined and simple image construction.  By further combining our method with multidirectional digital scanned laser light-sheet microscopy (mDSLM), we demonstrated improvement of image quality in biological samples.

https://doi.org/10.1364/OE.423783

Texture-Based Screening to Identify Genes Involved in Reproductive Aging in C. elegans

Dr Momoko Imakubo et al.’s study on analysis of genes involved in reproductive aging in C. elegans oocytes by using an image database of RNAi embryos and image processing has been published online at https://doi.org/10.17706/ijbbb.2021.11.3.40-49.

Congratulations to our former student trainee Momoko Imakubo who earned her PhD from Kobe University in March 2021 on her achievement. We wish you all the best in your future endeavour!

[Press Release] Launch of “NeuroGT Database”, a brain atlas of neurogenic tagging CreER mouse drivers

Drs. Yukako Tohsato and Hiroya Itoga in our SSBD team, together with Prof. Tatsumi Hirata (NIG) and colleagues, developed the “NeuroGT database,” which contains whole-brain image data of tagged neurons based on time of neurogenesis. Through NeuroGT, researchers can find suitable neurogenic tagging driver lines for their research.

Learn more about Neuro GT on the National Institute of Genetics Press Release.

Reference

Hirata, T., Tohsato, Y., Itoga, H. et al. NeuroGT: A brain atlas of neurogenic tagging CreER drivers for birthdate-based classification and manipulation of mouse neurons. Cell Rep. Methods 1, 100012 (2021). https://doi.org/10.1016/j.crmeth.2021.100012

REMBI: Recommended Metadata for Biological Images

Our TL Dr Onami joined discussions on metadata standards in biological image data sharing with an international bioimaging community lead by EMBL-EBI. They propose global metadata guidelines, REMBI: Recommended Metadata for Biological Images.

https://doi.org/10.1038/s41592-021-01166-8

[Press Release] Recommendations for global standards of open image data formats and repositories.

TL Dr Shuichi Onami and Prof. Jason Swedlow (University of Dundee, UK) along with Global Bioimaging, an international consortium of the leading experts in bioimaging communities, released recommendations for bioimage data format standards and open access image data repositories. These recommendations contribute to accelerating the development of the bioimaging field through data sharing.

Read the full press release article on the RIKEN website (in Japanese).

Reference

Swedlow, J.R., Kankaanpää, P., Sarkans, U. et al. A global view of standards for open image data formats and repositories. Nat Methods (2021). https://doi.org/10.1038/s41592-021-01113-7