Ryan Savill
@cryaaa.bsky.social
87 followers 92 following 16 posts
PhD Student with the Jesse Veenvliet Group at the @mpicbg.bsky.social . Interested in all things Data and 3D bioimage analysis, organoids and development!
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Reposted by Ryan Savill
ebisuyamiki.bsky.social
New preprint from the lab! We discovered a transient fluidization in the basal region of human forebrains by tracking microdroplets in cerebral organoids.This “basal fluidization”, absent in gorilla and mouse, may contribute to greater surface expansion in human forebrains
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doi.org/10.1101/2025...
cryaaa.bsky.social
(13/14) Thank you to everyone involved, especially my fellow PhD students Alba Villaronga Luque and @mtrani.bsky.social for sharing their data and contributing to the development but also @yonitmms.bsky.social the rest of our lab for their input and help with annotation.
cryaaa.bsky.social
(11/14)
Building on this we can identify features that correlate with the observed patterning classes. The 3D patterning maps thus provide framework to systematically investigate gastruloid patterning spaces!
cryaaa.bsky.social
(10/14) Alba Villaronga Luque generously shared her data investigating how initial cell number (N0) influences patterning. We extracted patterning maps of 54 gastruloids and were able to detect distinct patterning phenotypes using dimensionality reduction and clustering.
cryaaa.bsky.social
(9/14) With this normalized reference frame in hand we can use data with multiple developmental markers and quantify patterning maps using SLIC segmentation. Maps are a 2D representation of 3D patterning data, allowing comparison of patterning types in a unified reference frame.
cryaaa.bsky.social
(8/14) A core feature of SpinePy is the generation of a common reference frame, no matter the gastruloids size, shape, or orientation under the microscope. We define the AP and core-to-surface (CS) position and can use it to map the signals into a common space!
cryaaa.bsky.social
(7/14) Another neat feature is the quantification of scalar fields along the axis. We use density as an example but any signal of interest could be used to generate profiles along the AP axis. Again, the synthetic data facilitates verification of the pipeline!
cryaaa.bsky.social
(6/14) One core biological feature to quantify is gross morphology. Using optimized, non-intersecting planes, we measure radial profiles over the AP axis for fixed and live gastruloids giving insights into 3D morphodynamics. Big thanks to @mtrani.bsky.social who provided data and insight!
cryaaa.bsky.social
(5/14) This allowed me to create hundreds of gastruloids in silico, with defined spines and thickness profiles to benchmark SpinePy. We show that the spine detection performs well with low relative errors compared to the ground truth!
cryaaa.bsky.social
(4/14) Using manual annotations to benchmark the spine is a crucial but in 3D annotation can be challenging. To have a second method of verification I generated synthetic gastruloids with some Perlin noise to generate realistic structures (like this wobbly gastruloid)
cryaaa.bsky.social
(3/14) The first step is detecting the anteroposterior (AP) axis in gastruloids, based on gross morphology. We can either use a skeletonization approach using segmentation or a surface mesh approach using Non-linear PCA, which was important for timelapse data.
cryaaa.bsky.social
(2/14) Its modular architecture allows it to plop into pre-existing workflows. This means you can map any signal of interest into a common reference frame across gastruloids!
cryaaa.bsky.social
(1/14) I’m happy and proud to introduce: SpinePy – a framework to detect the "spine" of gastruloids and measure biological and physical signals in a local dynamic 3D coordinate system. www.biorxiv.org/content/10.1...
Reposted by Ryan Savill
jo-soltwedel.bsky.social
FINALLY just released the @napari.org clusters-plotter 0.9.0 🤗 pypi.org/project/napa... The latest version comes with a complete overhaul of the entire codebase to make #microscopy data introspection and browsing even more accessible, intuitive and versatile! #bioimaging

Let's have a look 👇🧪💻🔬
cryaaa.bsky.social
🙌🏻🙌🏻🙌🏻
cryaaa.bsky.social
This my first big project during my PhD and I couldn’t be happier about it being out! Please give it a read if you’re interested in embryo models, data fusion, machine learning, image analysis, metabolism, scSeq…. because a lot of great people made this project possible! 🚀
jesseveenvliet.bsky.social
😱 A very hungry #PacManoid ate the original post 🍬🍬🍬

Here’s the 🧵 on our latest in @cp-cellstemcell.bsky.social again!

Gastruloids w/ a sweet tooth better model natural embryos: doi.org/10.1016/j.st...

Spearheaded by @cryaaa.bsky.social & Alba Villaronga-Luque @mpi-cbg.de @poldresden.bsky.social
Reposted by Ryan Savill
kstapornwongkul.bsky.social
📢 Fresh off the press and featuring new exciting experiments! 🧪
We show how glycolytic activity instructs germ layer proportions through regulation of Nodal and Wnt signaling - happy to finally share this 😊
doi.org/10.1016/j.st...

B2B with @jesseveenvliet.bsky.social lab: doi.org/10.1016/j.st... 🤩
Reposted by Ryan Savill
jesseveenvliet.bsky.social
Festive times with @mpi-cbg.de predocs Ryan Savill @cryaaa.bsky.social & Alba Villaronga Luque! What were we celebrating? More tomorrow!

Supported by @sumoconsortium.bsky.social, part of @ec.europa.eu European Innovation Council Engineered Living Materials Portfolio #EUeic #EICPathfinder #ELMs
Reposted by Ryan Savill
jo-soltwedel.bsky.social
Some new additions for the upcoming @napari.org clusters-plotter version 👉0.9.0 around the corner! Powered by some work from @mazoc.bsky.social, it casually turns into a pretty neat tool for feature map creation 😀

github.com/BiAPoL/napar...