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Yuan-Zhi He

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Aug 2026

Abnormal functional lateralization and cooperation in primary angle-closure glaucoma correlate with cell type-specific transcriptional signatures.

BACKGROUND Primary angle-closure glaucoma (PACG) damages retinal ganglion cells (RGCs) and is associated with neurodegeneration. This study used resting-state functional magnetic resonance imaging (fMRI) to analyze hemispheric lateralization and cooperative functional alterations in PACG. Machine learning assessed the classification efficacy of neuroimaging indicators, while integrated transcriptomics described spatial relationships between neuroimaging changes and genes, neurotransmitters, and cell types. METHODS Resting-state fMRI data were collected from 101 subjects (44 patients with PACG and 57 controls). Whole-brain maps of the Autonomy Index and connectivity of functional homotopic voxels (CFH) were constructed. Their classification efficacy was assessed using five machine learning classifiers. Partial Least Squares (PLS) spatial correlation analysis examined relationships between neuroimaging maps and gene-transcript profiles, cell type density, and neurotransmitter-receptor distribution maps. RESULTS PACG showed increased Autonomy Index in cerebellar Crus II and the right paracentral lobule, with widespread reductions in interhemispheric cooperation. Five machine learning models yielded classification results. Image-transcriptome analysis showed that positive Autonomy Index and CFH-positive gene features were enriched in synaptic signaling and neurodevelopment, whereas negative Autonomy Index and CFH-negative gene profiles correlated with neurodegeneration, metabolic dysfunction, and vascular-immune responses. Oligodendrocytes and endothelial cells showed spatial associations with the Autonomy Index and CFH. Brain lateralization and interhemispheric cooperation showed spatial correlations with VAChT topology and several neurotransmitter receptor/transporter maps. CONCLUSION PACG is characterized by enhanced cerebral lateralization and diminished interhemispheric cooperation. Explainable machine learning evaluated the classification efficacy of these imaging features. These findings provide a multimodal spatial-association framework relating PACG-related imaging alterations to normative molecular and cellular brain maps.

Jing-Wen Qiu, Yuan-Zhi He, Si-Xian Li et al. · Neuroscience · 0 citations

Aug 2026

System-level disruption of cortical temporal integration after stroke: linking intrinsic neural timescales to molecular and neurochemical architecture.

Stroke disrupts the brain's ability to process and integrate information over time, yet the underlying molecular mechanisms remain unclear. This study investigates post-stroke alterations in intrinsic neural timescales (INTs)-a measure of regional temporal integration-by combining resting-state fMRI, spatial transcriptomics, and PET-based neurochemical mapping. Fifty acute ischemic stroke patients (within 7 days of onset) and fifty matched healthy controls were examined. Voxel-wise and network-level analyses revealed significantly reduced INTs in temporoparietal and insular cortices, with pronounced network-level impairments in the visual and cerebellar systems. Using data from the Allen Human Brain Atlas, we identified gene expression patterns associated with these disruptions. Genes negatively associated with INT reductions were enriched for synaptic, mitochondrial, and neurodevelopmental pathways, while positively associated genes reflected immune signaling and nuclear transport. INT alterations also correlated with excitatory and inhibitory neuronal signatures and were spatially aligned with GABA-A receptor density. Importantly, INT reductions showed significant correlations with clinical assessments: whole-brain INT correlated negatively with NIHSS (r = -0.41) and positively with MoCA (r = 0.38) and FMA (r = 0.35); SMN INT correlated with FMA motor subscore (r = 0.44); and regional INT correlated with domain-specific NIHSS subscores (neglect: r = -0.42; language: r = -0.38). These findings position INT as a clinically meaningful systems-level correlate of stroke-induced dysfunction and highlight molecular pathways and neurotransmitter systems that may constrain temporal integration and recovery potential.

Shao-Gao Gui, Zhan-Xiang Hu, Yuan-Zhi He et al. · Brain Research · 0 citations