Democratising deep learning for microscopy with ZeroCostDL4Mic

Deep Learning (DL) methods are powerful analytical tools for microscopy and can outperform conventional image processing pipelines. Despite the enthusiasm and innovations fuelled by DL technology, the need to access powerful and compatible resources to train DL networks leads to an accessibility barrier that novice users often find difficult to overcome. Here, we present ZeroCostDL4Mic, an entry-level platform simplifying DL access by leveraging the free, cloud-based computational resources of Google Colab. ZeroCostDL4Mic allows researchers with no coding expertise to train and apply key DL networks to perform tasks including segmentation (using U-Net and StarDist), object detection (using YOLOv2), denoising (using CARE and Noise2Void), super-resolution microscopy (using Deep-STORM), and image-to-image translation (using Label-free prediction - fnet, pix2pix and CycleGAN). Importantly, we provide suitable quantitative tools for each network to evaluate model performance, allowing model optimisation. We demonstrate the application of the platform to study multiple biological processes. Deep learning methods show great promise for the analysis of microscopy images but there is currently an accessibility barrier to many users. Here the authors report a convenient entry-level deep learning platform that can be used at no cost: ZeroCostDL4Mic

Tectono-Stratigraphy of Levent (Akçadağ-Malatya) Region

Çalışma alanı Malatya İlinin kuzeybatısında yer almakta olup, yaklaşık 120 km2'lik bir alanı kapsamaktadır. Bölgede Üst Jura-Tersiyer yaş aralığında kayaçlar yüzeylemektedir. Levent ve çevresinin kaya stratigrafi birimleri ve tektono-stratigrafik özelliklerini belirlemek amacı ile yapılmış bu çalışmada 6 farklı litostratigrafi birimi ayırtlanarak haritalanmıştır. Bölgenin temel kayalarını Üst Jura-Alt Kretase yaşlı, aşırı derecede altere olmuş, kısmen tabakalı, gri-bej renkteki Horasançal Formasyonu oluşturmaktadır. Geç Kampaniyen sırası ve sonrasında olasılıkla kuzeyden güneye doğru bindirmeler ile gelen Hocalıkova ofiyoliti, temeldeki Horasanaçal Formasyonunu tektonik olarak üzerlemektedir. Geç Kampaniyen-Erken Mastrihtiyen'de tektonik aktivite ile denetlenen bir havzada transgresif olarak Ulupınar Formasyonu havzanın kenar kesimlerinde (sığ denizel-sahil çizgisi çökelleri) çökelmiştir. Ulupınar Formasyonunun üzerine; başlıca çakıltaşı, kumtaşı, kireçtaşı-marn ardalanmasından oluşan, Orta-Geç Eosen yaşlı ve genelde lagün, kumsal, şelf ortamlarında çökelen Tohma Formasyonu açısal uyumsuzlukla gelmektedir. Tohma Formasyonu üzerine yine uyumsuz olarak başlıca bazaltlardan oluşan Orta-Geç Miyosen yaşlı Yamadağ volkanitleri gelmektedir. Bölgedeki en genç birimler olan Kuvaterner yaşlı alüvyon yelpazeleri ve alüvyonlar diğer bütün birimler üzerinde açısal uyumsuzlukla yer almaktadır.The study area is located to the Northwest of Malatya city and covers an area of about 120 square km. Upper Jurassic-Tertiary aged formations are exposed around the region. This study aims to determine lithostratigraphic and tectonostratigraphic features of the units in Levent village and its near surrounding area where six lithostratigraphic units have been distinguished. The basement is represented by Late Jurassic-Early Cretaceous age HorasanÇal Formation which consists of fractured, partly bedded, grey to beige coloured limestone. The Hocalıkova ophiolites, which tectonically overlies the HorasanÇal Formation, probably thrusted into the area from north to the south during and/or after late Campanian. The Ulupınar Formation transgresivelly deposited to the edge of the basin (shallow marine-shore line sediments) during late Campanian-early Maastrichtian around the tectonically controlled basin. Upper Cretaceous Ulupınar formation consisting of conglomerate, sandstone, marl and limestone was deposited partly in a shoreline area and partly in very shallow marine environments. Middle-Upper Eocene age Tohma formation that generally deposited in lagoon, beach and shelf environments comprising mainly pebblestone, sandstone, limestone-marl rests on the Ulupınar Formation with an angular unconformity. Middle-Late Miocene age Yamadağ volcanics comprising mainly basalts unconformably rests on the Tohma Formation. Quaternary age alluvial fan and alluviums are the youngest sediments of the area and unconformably rest on all the older units

DaXi-high-resolution, large imaging volume and multi-view single-objective light-sheet microscopy.

The promise of single-objective light-sheet microscopy is to combine the convenience of standard single-objective microscopes with the speed, coverage, resolution and gentleness of light-sheet microscopes. We present DaXi, a single-objective light-sheet microscope design based on oblique plane illumination that achieves: (1) a wider field of view and high-resolution imaging via a custom remote focusing objective; (2) fast volumetric imaging over larger volumes without compromising image quality or necessitating tiled acquisition; (3) fuller image coverage for large samples via multi-view imaging and (4) higher throughput multi-well imaging via remote coverslip placement. Our instrument achieves a resolution of 450 nm laterally and 2 μm axially over an imaging volume of 3,000 × 800 × 300 μm. We demonstrate the speed, field of view, resolution and versatility of our instrument by imaging various systems, including Drosophila egg chamber development, zebrafish whole-brain activity and zebrafish embryonic development - up to nine embryos at a time

OME-Zarr : A cloud-optimized bioimaging file format with international community support

A growing community is constructing a next-generation file format (NGFF) for bioimaging to overcome problems of scalability and heterogeneity. Organized by the Open Microscopy Environment (OME), individuals and institutes across diverse modalities facing these problems have designed a format specification process (OME-NGFF) to address these needs. This paper brings together a wide range of those community members to describe the cloud-optimized format itself-OME-Zarr-along with tools and data resources available today to increase FAIR access and remove barriers in the scientific process. The current momentum offers an opportunity to unify a key component of the bioimaging domain-the file format that underlies so many personal, institutional, and global data management and analysis tasks