Doudou Yu
@doudouyu.bsky.social
Thank you so much Kaity! 🫶
October 10, 2025 at 9:57 PM
Thank you so much Kaity! 🫶
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Neuropathologist: Ivana Delalle
Computational biology: Ghulam Murtaza, Ritambhara Singh, Bill Noble @wnoble.bsky.social
And the entire Webb lab @aewebb.bsky.social, especially Kelsey Babcock, Kaitlyn Hajdarovic @khajdarovic.bsky.social!
Neuropathologist: Ivana Delalle
Computational biology: Ghulam Murtaza, Ritambhara Singh, Bill Noble @wnoble.bsky.social
And the entire Webb lab @aewebb.bsky.social, especially Kelsey Babcock, Kaitlyn Hajdarovic @khajdarovic.bsky.social!
October 10, 2025 at 9:53 PM
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Neuropathologist: Ivana Delalle
Computational biology: Ghulam Murtaza, Ritambhara Singh, Bill Noble @wnoble.bsky.social
And the entire Webb lab @aewebb.bsky.social, especially Kelsey Babcock, Kaitlyn Hajdarovic @khajdarovic.bsky.social!
Neuropathologist: Ivana Delalle
Computational biology: Ghulam Murtaza, Ritambhara Singh, Bill Noble @wnoble.bsky.social
And the entire Webb lab @aewebb.bsky.social, especially Kelsey Babcock, Kaitlyn Hajdarovic @khajdarovic.bsky.social!
8/
This work was a massive team effort and would have been impossible without our amazing collaborators:
Imaging: Andrei Vlassenko, Manu Goyal, and Jürgen Germann
Senescence: Shiva Dehkordi, Miranda Orr @orrlaboratory.bsky.social , Habil Zare
Hypothalamus: Alex Jackson
This work was a massive team effort and would have been impossible without our amazing collaborators:
Imaging: Andrei Vlassenko, Manu Goyal, and Jürgen Germann
Senescence: Shiva Dehkordi, Miranda Orr @orrlaboratory.bsky.social , Habil Zare
Hypothalamus: Alex Jackson
October 10, 2025 at 9:53 PM
8/
This work was a massive team effort and would have been impossible without our amazing collaborators:
Imaging: Andrei Vlassenko, Manu Goyal, and Jürgen Germann
Senescence: Shiva Dehkordi, Miranda Orr @orrlaboratory.bsky.social , Habil Zare
Hypothalamus: Alex Jackson
This work was a massive team effort and would have been impossible without our amazing collaborators:
Imaging: Andrei Vlassenko, Manu Goyal, and Jürgen Germann
Senescence: Shiva Dehkordi, Miranda Orr @orrlaboratory.bsky.social , Habil Zare
Hypothalamus: Alex Jackson
7/
In summary, our integrative volumetric and single-cell atlas of the human hypothalamus provides a high-resolution framework for elucidating how aging and AD pathology differentially affect specific hypothalamic subregions and cell types.
In summary, our integrative volumetric and single-cell atlas of the human hypothalamus provides a high-resolution framework for elucidating how aging and AD pathology differentially affect specific hypothalamic subregions and cell types.
October 10, 2025 at 9:39 PM
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In summary, our integrative volumetric and single-cell atlas of the human hypothalamus provides a high-resolution framework for elucidating how aging and AD pathology differentially affect specific hypothalamic subregions and cell types.
In summary, our integrative volumetric and single-cell atlas of the human hypothalamus provides a high-resolution framework for elucidating how aging and AD pathology differentially affect specific hypothalamic subregions and cell types.
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What about neurons?
Among the many diverse neuronal subtypes, we found those that regulate sleep and circadian rhythms were hit hardest in AD. Their cellular communication pathways showed major disruptions (e.g., ligand-receptor interactions).
What about neurons?
Among the many diverse neuronal subtypes, we found those that regulate sleep and circadian rhythms were hit hardest in AD. Their cellular communication pathways showed major disruptions (e.g., ligand-receptor interactions).
October 10, 2025 at 9:39 PM
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What about neurons?
Among the many diverse neuronal subtypes, we found those that regulate sleep and circadian rhythms were hit hardest in AD. Their cellular communication pathways showed major disruptions (e.g., ligand-receptor interactions).
What about neurons?
Among the many diverse neuronal subtypes, we found those that regulate sleep and circadian rhythms were hit hardest in AD. Their cellular communication pathways showed major disruptions (e.g., ligand-receptor interactions).
5/
Zooming in on inflammation, we focused on microglia (the brain's immune cells).
We mapped their transition from a healthy state to a disease-associated state, finding they become progressively more inflammatory and stress-responsive along the AD trajectory.
Zooming in on inflammation, we focused on microglia (the brain's immune cells).
We mapped their transition from a healthy state to a disease-associated state, finding they become progressively more inflammatory and stress-responsive along the AD trajectory.
October 10, 2025 at 9:35 PM
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Zooming in on inflammation, we focused on microglia (the brain's immune cells).
We mapped their transition from a healthy state to a disease-associated state, finding they become progressively more inflammatory and stress-responsive along the AD trajectory.
Zooming in on inflammation, we focused on microglia (the brain's immune cells).
We mapped their transition from a healthy state to a disease-associated state, finding they become progressively more inflammatory and stress-responsive along the AD trajectory.
4/
Our machine learning models, trained to distinguish AD from control cells, pointed to two key predictors of disease:
inflammation and disruptions in circadian rhythm regulators.
Our machine learning models, trained to distinguish AD from control cells, pointed to two key predictors of disease:
inflammation and disruptions in circadian rhythm regulators.
October 10, 2025 at 9:34 PM
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Our machine learning models, trained to distinguish AD from control cells, pointed to two key predictors of disease:
inflammation and disruptions in circadian rhythm regulators.
Our machine learning models, trained to distinguish AD from control cells, pointed to two key predictors of disease:
inflammation and disruptions in circadian rhythm regulators.
3/
To see which cells were responsible, we performed single-nucleus RNA-seq on 614,403 nuclei from post-mortem hypothalamus from young, AD, and age-matched non-dementia controls.
To see which cells were responsible, we performed single-nucleus RNA-seq on 614,403 nuclei from post-mortem hypothalamus from young, AD, and age-matched non-dementia controls.
October 10, 2025 at 9:33 PM
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To see which cells were responsible, we performed single-nucleus RNA-seq on 614,403 nuclei from post-mortem hypothalamus from young, AD, and age-matched non-dementia controls.
To see which cells were responsible, we performed single-nucleus RNA-seq on 614,403 nuclei from post-mortem hypothalamus from young, AD, and age-matched non-dementia controls.
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Brain imaging of 202 individuals revealed that different hypothalamic subregions change differently with age.
The most affected areas are linked to stress, energy, and circadian rhythms, and these changes were exacerbated in AD, showing the hypothalamus is not a single unit.
Brain imaging of 202 individuals revealed that different hypothalamic subregions change differently with age.
The most affected areas are linked to stress, energy, and circadian rhythms, and these changes were exacerbated in AD, showing the hypothalamus is not a single unit.
October 10, 2025 at 9:29 PM
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Brain imaging of 202 individuals revealed that different hypothalamic subregions change differently with age.
The most affected areas are linked to stress, energy, and circadian rhythms, and these changes were exacerbated in AD, showing the hypothalamus is not a single unit.
Brain imaging of 202 individuals revealed that different hypothalamic subregions change differently with age.
The most affected areas are linked to stress, energy, and circadian rhythms, and these changes were exacerbated in AD, showing the hypothalamus is not a single unit.
1/
By combining noninvasive high-resolution brain imaging and single-cell molecular profiling, we identified specific subregions and cell types that are vulnerable during aging and AD, particularly those regulating stress and circadian rhythms.
By combining noninvasive high-resolution brain imaging and single-cell molecular profiling, we identified specific subregions and cell types that are vulnerable during aging and AD, particularly those regulating stress and circadian rhythms.
October 10, 2025 at 9:29 PM
1/
By combining noninvasive high-resolution brain imaging and single-cell molecular profiling, we identified specific subregions and cell types that are vulnerable during aging and AD, particularly those regulating stress and circadian rhythms.
By combining noninvasive high-resolution brain imaging and single-cell molecular profiling, we identified specific subregions and cell types that are vulnerable during aging and AD, particularly those regulating stress and circadian rhythms.
😭😭😭 I miss you so much Dr. Kaity!!!
March 7, 2025 at 2:53 AM
😭😭😭 I miss you so much Dr. Kaity!!!