PreTSA: computationally efficient modeling of temporal and spatial gene expression patterns DOI Creative Commons
Haotian Zhuang, Zhicheng Ji

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2024, Volume and Issue: unknown

Published: March 25, 2024

ABSTRACT Modeling temporal and spatial gene expression patterns in large-scale single-cell transcriptomics data is a computationally intensive task. We present PreTSA, method that offers computational efficiency modeling these applicable to comprising millions of cells. PreTSA consistently matches the results state-of-the-art methods while significantly reducing time. provides unique solution for studying extremely large datasets.

Language: Английский

Spatiotemporal analysis of gene expression in the human dentate gyrus reveals age-associated changes in cellular maturation and neuroinflammation DOI Creative Commons
Anthony D. Ramnauth, Madhavi Tippani, Heena R. Divecha

et al.

Cell Reports, Journal Year: 2025, Volume and Issue: 44(2), P. 115300 - 115300

Published: Feb. 1, 2025

The dentate gyrus of the hippocampus is important for many cognitive functions, including learning, memory, and mood. Here, we present transcriptome-wide spatial gene expression maps human investigate age-associated changes across lifespan. Genes associated with neurogenesis extracellular matrix are enriched in infants decline throughout development maturation. Following infancy, inhibitory neuron markers increase, cellular proliferation decrease. We also identify spatio-molecular signatures that support existing evidence protracted maturation granule cells during adulthood increases neuroinflammation-related expression. Our findings notion hippocampal neurogenic niche undergoes major following infancy molecular regulators brain aging glial- neuropil-enriched tissue.

Language: Английский

Citations

1

Neural circuit-selective, multiplexed pharmacological targeting of prefrontal cortex-projecting locus coeruleus neurons drives antinociception DOI Creative Commons
Chao‐Cheng Kuo, Jordan G. McCall

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2024, Volume and Issue: unknown

Published: June 8, 2024

Selective manipulation of neural circuits using optogenetics and chemogenetics holds great translational potential but requires genetic access to neurons. Here, we demonstrate a general framework for identifying tool-independent, pharmacological strategies circuit-selective modulation. We developed an economically accessible calcium imaging-based approach large-scale scans endogenous receptor-mediated activity. As testbed this approach, used the mouse locus coeruleus due combination its widespread, modular efferent circuitry wide variety endogenously expressed GPCRs. Using machine learning-based action deconvolution retrograde tracing, identified agonist cocktail that selectively inhibits medial prefrontal cortex-projecting

Language: Английский

Citations

4

Integrating Spatially‐Resolved Transcriptomics Data Across Tissues and Individuals: Challenges and Opportunities DOI Creative Commons
Boyi Guo, Wodan Ling, Sang Ho Kwon

et al.

Small Methods, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 11, 2025

Advances in spatially-resolved transcriptomics (SRT) technologies have propelled the development of new computational analysis methods to unlock biological insights. The lowering cost SRT data generation presents an unprecedented opportunity create large-scale spatial atlases and enable population-level investigation, integrating across multiple tissues, individuals, species, or phenotypes. Here, unique challenges are described integration, where analytic impact varying resolutions is characterized explored. A succinct review spatially-aware integration strategies provided. Exciting opportunities advance algorithms amenable atlas-scale datasets along with standardized preprocessing methods, leading improved sensitivity reproducibility future further highlighted.

Language: Английский

Citations

0

Regenerating Locus Coeruleus‐Norepinephrine (LCNE) Function: A Novel Approach for Neurodegenerative Diseases DOI Creative Commons

Ya-Na Yang,

Yunlong Tao

Cell Proliferation, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 28, 2025

ABSTRACT Pathological changes in the locus coeruleus‐norepinephrine (LC‐NE) neurons, major source of norepinephrine (NE, also known as noradrenaline) brain, are evident during early stages neurodegenerative diseases (ND). Research on both human and animal models have highlighted therapeutic potential targeting LC‐NE system to mitigate progression ND alleviate associated psychiatric symptoms. However, widespread degeneration presents a significant challenge for direct intervention ND. Recent advances regenerative cell therapy offer promising new strategies treatment. The regeneration from pluripotent stem cells (PSCs) could significantly broaden scope LC‐NE‐based therapies In this review, we delve into fundamental background physiological functions LC‐NE. Additionally, systematically examine evidence role neuropathology over recent years. Notably, focus significance PSCs‐derived its impact therapy. A deeper understanding further investigation function pave way practical effective treatments

Language: Английский

Citations

0

GABAergic mechanisms in alcohol dependence DOI
Mikko Uusi‐Oukari, Esa R. Korpi

International review of neurobiology, Journal Year: 2024, Volume and Issue: unknown, P. 75 - 123

Published: Jan. 1, 2024

Language: Английский

Citations

2

Monoaminergic degeneration, cognition, and autonomic symptom trajectory in early Parkinson's disease DOI
Seo-Yeon Kim, Kyung Ah Woo, Hongyoon Choi

et al.

Parkinsonism & Related Disorders, Journal Year: 2024, Volume and Issue: 127, P. 107086 - 107086

Published: Aug. 3, 2024

Language: Английский

Citations

2

PreTSA: computationally efficient modeling of temporal and spatial gene expression patterns DOI Creative Commons
Haotian Zhuang, Zhicheng Ji

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2024, Volume and Issue: unknown

Published: March 25, 2024

ABSTRACT Modeling temporal and spatial gene expression patterns in large-scale single-cell transcriptomics data is a computationally intensive task. We present PreTSA, method that offers computational efficiency modeling these applicable to comprising millions of cells. PreTSA consistently matches the results state-of-the-art methods while significantly reducing time. provides unique solution for studying extremely large datasets.

Language: Английский

Citations

0