Guang-Zhong Wang

Professor at SINH, Chinese Academy of Science. We are engaged in the large-scale data integration of brain and circadian systems biology.

[Guang-Zhong Wang @GZWangLab]

Our new analysis of single-cell spatial transcriptome data from 25 million neurons in the macaque cortex reveals the non-random distribution of neurons and hints at the computational architecture of the cortex. https://t.co/biIAWpFX9O

[Stefano Berto, PhD @StefanoBerto83]

Today I'm incredibly proud to share our lab's first wet lab paper, now available as a bioRxiv preprint.

This is also the first massive milestone since it's my very first wet lab paper as a bioinformatician who started an experimental wet-lab from scratch
https://t.co/BUQUm5Z9GQ

[Guang-Zhong Wang @GZWangLab]

@StefanoBerto83 Nice job Stefano!

[Dr. Carmen Falcone @CarmenFalcone6]

The first work of the #FalconeLab is finally out!!! 🤩

A story of #astrocytes from evolution to disease. Thanks everyone who made this possible!

Varicose projection astrocytes: Conserved reactive cells in brain pathology | @ScienceAdvances https://t.co/BzNbnveFlO

@TowsonU

[Waggoner Lab @LabWaggoner]

Whole-transcriptome-scale isoform-resolved spatial imaging of single cells in tissues @CellCellPress
https://t.co/jt6T0hTa87 @Harvard @hhmi_science

[Guang-Zhong Wang @GZWangLab]

@StefanoBerto83 Congrats!

[Guang-Zhong Wang @GZWangLab]

Organizational Principles of the Primate Cerebral Cortex at the Single‐Cell Level - https://t.co/biIAWpFX9O

[Guang-Zhong Wang @GZWangLab]

Also, these non-random distribution of neurons and spatial partnerships, may inspire next-gen AI architectures. These principles could reshape how we build AI models! #DeepLearning #AI #Neuroscience #NeurIPS #MachineLearning #NeuroAI #BrainInspiredAI #AIModels

[Guang-Zhong Wang @GZWangLab]

Additionally, they are conserved in the mouse cortex.

[Guang-Zhong Wang @GZWangLab]

Our new analysis of single-cell spatial transcriptome data from 25 million neurons in the macaque cortex reveals the non-random distribution of neurons and hints at the computational architecture of the cortex. https://t.co/biIAWpFX9O

[Guang-Zhong Wang @GZWangLab]

@zhaowang4695 Thanks Zhao!

[Guang-Zhong Wang @GZWangLab]

9. In the visual pathway, primary information processing uses larger clusters.
10. In the default mode network (DMN), neuron clusters tend to be smaller.
11. Specific brain regions utilize distinct combinations of neuron cell types.

[Guang-Zhong Wang @GZWangLab]

6. Cluster size is positively correlated with the number of partnering clusters.
7. In coupled excitatory and inhibitory spatial clusters, the E–I ratio is positively correlated.
8. The total number of cells in excitatory and inhibitory clusters is similar.

[Guang-Zhong Wang @GZWangLab]

3. There are more inhibitory neuron clusters than excitatory clusters, but they tend to be smaller in size.
4. There are many clusters composed solely of excitatory cells, with unknown functions.
5. Adjacent spatial clusters use similar cell types.

[Guang-Zhong Wang @GZWangLab]

More details: 1. The number of inhibitory neurons increases as the number of nearby excitatory neurons increases.
2. In deeper cortical layers, the proportion of excitatory neurons is higher.

[Guang-Zhong Wang @GZWangLab]

3. Clusters of excitatory neurons primarily consist of excitatory-excitatory cell combinations, while inhibitory clusters mainly include excitatory-inhibitory cell combinations.
4. Most excitatory and inhibitory neuron clusters have spatial partnerships with one another.

[Guang-Zhong Wang @GZWangLab]

2. Within each clusters, different cell types tend to work together rather than functioning independently.

[Guang-Zhong Wang @GZWangLab]

We have uncovered several key patterns in the spatial distribution of neurons in the cerebral cortex:
1. Neurons are distributed in a highly non-random manner within the cortex, with over 75% located in different spatial clusters.

[Joseph Takahashi @CircadianClocks]

Whole-brain spatial transcriptional analysis at cellular resolution | Science https://t.co/o5wXRnZQiz

[Sergiu P. Pasca @Sergiu_P_Pasca]

Latest paper out in @Nature this week: an atlas integrating 36 single-cell transcriptomic datasets spanning 26 protocols for making neural hashtag#organoids
Effort led by @TreutleinLab @fabian_theis and @GrayCampLab

In Figure 4 you can also find the pojection of the neural organoid morphogen screen developed by Neal @neal_amin and Kevin @kevinwkelley in the lab

[swaruplab @swaruplab1]

Congratulations to the whole team for this amazing tour de force work on spatial multi-omics in AD.
https://t.co/tR6OB4uGvB