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Reposted by Yu Xiao (肖燏)

Shaoshi Zhang @shaoshiz.bsky.social · Jul 17

🚨Thrilled to share our latest work just published in @nature.com where we looked into the optimal fMRI scan time for brain-wide association studies (BWAS) 🧠⏱️! Full thread below👇:

Thomas Yeo @bttyeo.bsky.social · Jul 17

1/11 Excited to share our @Naturestudy led by @leonooi.bsky.social @csabaorban.bsky.social @shaoshiz.bsky.social

AI performance is known to scale with logarithm of sample size (Kaplan 2020), but in many domains, sample size can be # participants or # measurements...

doi.org/10.1038/s415...

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Yu Xiao (肖燏) @xiaoyucaly.bsky.social · Jul 17

How could we predict multiple neurodegenerative disease using just blood sample and a single model? Check out this incredible work by @anlijuncn.bsky.social ⬇️

Lijun An @anlijuncn.bsky.social · Jul 15

Can AI reveal risk & co-pathology of multiple neurodegenerative diseases from a single blood sample? We explored AI-based diagnostic power on high rank plasma proteomics (N=17,170). www.medrxiv.org/content/10.1... #neuroskyence #neurosky #Alzheimer #compneuro #AI #datascience #neurology

Benchmarking the AI-based diagnostic potential of plasma proteomics for neurodegenerative disease in 17,170 people

Co-pathology is a common feature of neurodegenerative diseases that complicates diagnosis, treatment and clinical management. However, sensitive, specific and scalable biomarkers for in vivo pathologi...

www.medrxiv.org

Yu Xiao (肖燏) @xiaoyucaly.bsky.social · May 27

How does brain change functionally in AD and aging? Check out this cool work from @jorittmo.bsky.social

Jonathan Rittmo @jorittmo.bsky.social · May 27

How does the brain reorganize in the context of age and AD?

Are functional changes in age and AD similar?

Are these changes dynamic across the age/AD spectrum?

We unpack these questions in a sample of N=973 with AD biomarkers

Preprint: tinyurl.com/ymv8s7h8

⬇️🧵

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Reposted by Yu Xiao (肖燏)

Boris Bernhardt @borismontreal.bsky.social · May 11

Preprint 🥳

"A unified imaging-histology framework for superficial white matter architecture studies in the human brain"

🧠 SMW key for brain structure-function links
🤔 understudied because of its complexity
💡 SMW mapping for histology & MRI
🌟 OA

📖 lnkd.in/ef8bGGrF

by Youngeun Hwang et al

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Reposted by Yu Xiao (肖燏)

Lijun An @anlijuncn.bsky.social · May 2

Check out Xiaoyu’s fantastic work!!

Yu Xiao (肖燏) @xiaoyucaly.bsky.social · Apr 24

🧠New preprint! What drives tau, the pathological protein in AD, to spread?
We found that WHERE tau appears and HOW MUCH accumulates are governed by different mechanisms. Check it out: www.biorxiv.org/content/10.1... 

#MedSky #neuroskyence #neurosky #alzsky #compneuro #MRI #neuroimaging #neurology

www.biorxiv.org

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Reposted by Yu Xiao (肖燏)

Jonathan Rittmo @jorittmo.bsky.social · Apr 28

Really important and cool work by @xiaoyucaly.bsky.social! Congratulations!

Yu Xiao (肖燏) @xiaoyucaly.bsky.social · Apr 24

🧠New preprint! What drives tau, the pathological protein in AD, to spread?
We found that WHERE tau appears and HOW MUCH accumulates are governed by different mechanisms. Check it out: www.biorxiv.org/content/10.1... 

#MedSky #neuroskyence #neurosky #alzsky #compneuro #MRI #neuroimaging #neurology

www.biorxiv.org

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Reposted by Yu Xiao (肖燏)

biofinder.bsky.social @biofinder.bsky.social · Apr 25

‼️New preprint!
We are happy to share our latest work led by @teanijarv.bsky.social investigating why tau pathology in AD often accumulates more in one hemisphere of the brain than the other.

Check out 🔗https://biorxiv.org/content/10.1101/2025.04.15.648728v1 or dive into the details below👇

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Yu Xiao (肖燏) @xiaoyucaly.bsky.social · Apr 25

Thank you! This would be really interesting to see, but now we haven’t got the chance to do

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Reposted by Yu Xiao (肖燏)

biofinder.bsky.social @biofinder.bsky.social · Apr 25

🧠Exciting new findings from a great collaboration between the BioFINDER study and the talented
@xiaoyucaly.bsky.social from @jwvogel.bsky.social group!! In their preprint, they show that tau presence and tau load are guided by unique brain mechanisms. Dive into the details here 👇

Yu Xiao (肖燏) @xiaoyucaly.bsky.social · Apr 24

🧠New preprint! What drives tau, the pathological protein in AD, to spread?
We found that WHERE tau appears and HOW MUCH accumulates are governed by different mechanisms. Check it out: www.biorxiv.org/content/10.1... 

#MedSky #neuroskyence #neurosky #alzsky #compneuro #MRI #neuroimaging #neurology

www.biorxiv.org

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Reposted by Yu Xiao (肖燏)

Jake Vogel @jwvogel.bsky.social · Apr 24

I am so very proud announce my lab's first preprint!!

@xiaoyucaly.bsky.social delves into the mechanisms driving tau distribution:
* Tau sequence driven by connectivity dynamics
* Tau load driven by local factors

Check out her thread below

Yu Xiao (肖燏) @xiaoyucaly.bsky.social · Apr 24

🧠New preprint! What drives tau, the pathological protein in AD, to spread?
We found that WHERE tau appears and HOW MUCH accumulates are governed by different mechanisms. Check it out: www.biorxiv.org/content/10.1... 

#MedSky #neuroskyence #neurosky #alzsky #compneuro #MRI #neuroimaging #neurology

www.biorxiv.org

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Yu Xiao (肖燏) @xiaoyucaly.bsky.social · Apr 24

🧵18/
Finally, thanks to the @biofinder.bsky.social team— Nicola Spotorno, Olof Strandberg, @aitchbi.bsky.social , @gsalvado.bsky.social, Erik Stomrud, Ruben Smith, Sebastian Palmqvist, @rikossenkoppele.bsky.social, Niklas Mattsson-Carlgren, and Oskar Hansson—for sharing the awesome data and support.

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Yu Xiao (肖燏) @xiaoyucaly.bsky.social · Apr 24

🧵17/
Thanks to Thomas Funck and Nicola Palomero-Gallagher for adding key receptor insights.

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Yu Xiao (肖燏) @xiaoyucaly.bsky.social · Apr 24

🧵16/
We’re deeply grateful to @misicbata.bsky.social, @alaindagher.bsky.social, Justine Hansen, @vincebaz.bsky.social, and @goloafs.bsky.social for providing essential brain connectome and biological datasets; and for their guidance with the SIR model.

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Yu Xiao (肖燏) @xiaoyucaly.bsky.social · Apr 24

🧵15/ Huge thanks to our amazing team and coauthors!

Endless thanks to @jwvogel.bsky.social for guiding and supporting this work from day one. To our amazing team DeMON lab, especially @anlijuncn.bsky.social for enormous support.

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Yu Xiao (肖燏) @xiaoyucaly.bsky.social · Apr 24

🧵14/ Explore our adapted computational model 👇
github.com/DeMONLab-Bio...

GitHub - DeMONLab-BioFINDER/Xiao_Tau_simulation_SIR

Contribute to DeMONLab-BioFINDER/Xiao_Tau_simulation_SIR development by creating an account on GitHub.

github.com

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Yu Xiao (肖燏) @xiaoyucaly.bsky.social · Apr 24

🧵13/ Why does this matter? 4⃣
Most importantly, we believe this distinction should shape how we study tau going forward: ⚪️presence and 🔴load likely need to be studied using different tools and at different scales—but both are essential to fully understand and stop tau progression.

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Yu Xiao (肖燏) @xiaoyucaly.bsky.social · Apr 24

🧵12/ Why does this matter? 3⃣
We also highlight 🎯neurotransmission marker dynamics as an underexplored yet promising direction for future research. Our findings point to the possibility of tau accumulating over a descending gradient of ionotropic excitatory potential.

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Yu Xiao (肖燏) @xiaoyucaly.bsky.social · Apr 24

🧵11/ Why does this matter? 2⃣
Our model shows they stem from distinct neural mechanisms: ⚪️presence is shaped by structural connectivity and neurotransmitter architecture, whereas 🔴load is driven by local biological vulnerability.

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Yu Xiao (肖燏) @xiaoyucaly.bsky.social · Apr 24

🧵10/ Why does this matter? 1️⃣
Today, Braak staging describes tau progression based on tau presence, while in vivo imaging and clinical trials typically assess tau load via PET. These are not equivalent measures.

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Yu Xiao (肖燏) @xiaoyucaly.bsky.social · Apr 24

🧵9/ (Cont.) We identified two (of the four subtypes) with especially interesting mechanisms:

🔷Posterior subtype: Linked strongly to acetylcholine—already a treatment target!
🔷MTL-sparing subtype: Spread better explained by specific *functional* brain networks.

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Yu Xiao (肖燏) @xiaoyucaly.bsky.social · Apr 24

🧵8/ We also explored why different Alzheimer's patients show unique tau patterns (subtypes)?
We tested patterns from the four Alzheimer’s subtypes @jwvogel.bsky.social (www.nature.com/articles/s41...), and identified two (of the four subtypes) with especially interesting mechanisms: (see next 🧵)

Four distinct trajectories of tau deposition identified in Alzheimer’s disease - Nature Medicine

Systematic characterization of longitudinal tau variability in human Alzheimer’s disease using an unbiased subtyping algorithm reveals four trajectories of tau deposition with distinct clinical featur...

www.nature.com

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Yu Xiao (肖燏) @xiaoyucaly.bsky.social · Apr 24

🧵7/ What drives 🔴Tau Load? — Determined by connectivity and local biological factors

Connectivity isn’t enough—local vulnerability is key. Factors such as regional amyloid-beta levels, MAPT expression, cerebral blood flow, and neurotransmission markers profiles all play a role.

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Yu Xiao (肖燏) @xiaoyucaly.bsky.social · Apr 24

🧵6/ Surprisingly, the balance of neurotransmission signals 🎯 (excitatory vs. inhibitory) and 5-HT receptors strongly overlap with tau presence. Regions with more ionotropic excitatory signaling are particularly vulnerable—supporting work focusing on E:I balance in AD.

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Yu Xiao (肖燏) @xiaoyucaly.bsky.social · Apr 24

🧵5/ What drives ⚪️Tau Presence? — Primarily brain connectivity

As expected, tau follows structural connectivity. But unexpectedly, we also found 🎯neurotransmitter marker distribution does an even better job explaining the pattern. We found this fascinating and explored further.

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Yu Xiao (肖燏) @xiaoyucaly.bsky.social · Apr 24

🧵4/ We next conducted an exploratory analysis using eight types of normative connectomes and 49 regional biological factors (thanks to @misicbata.bsky.social, his team, and the Allen Human Brain Atlas).

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