SHINE: decoding transcriptional-metabolic microenvironments through higher-order spatial integration
Dr. Bingxue Du (Post-doctoral Fellow)
[Supervisor: Professor Yuanhua Huang & Professor Jason Wong]

Spatial omics technologies increasingly enable co-profiling of transcriptomics and metabolomics on the same tissue slide, offering complementary views of gene expression and biochemical activity within native tissue microenvironments. However, integrating these modalities remains challenging due to spatial misalignment, resolution disparity, and complex cross-modality interactions. Here, we present SHINE, a hypergraph-based computational framework for joint analysis of spatial gene expression and metabolic networks from co-profiled tissues. SHINE focuses on representation learning and higher-order cross-modality interaction modeling. Across multiple datasets, SHINE improves domain segmentation and biomarker co-localization while providing interpretable insights into metabolic–transcriptional microenvironments. In Parkinson’s disease mouse models, SHINE delineates dopaminergic neuron-depleted regions and reconstructs dopamine-associated spatial axes. In human lung and breast cancers, SHINE resolves tumor-associated regions and identifies spatially organized gene–metabolite programs linked to the tumor microenvironment.

Dyslipidemia as an independent risk factor for prostatic enlargement: a 3-year prospective cohort study
Dr. Zhuo Yin (Post-doctoral Fellow)
[Supervisor: Professor Joshua Ho]

This prospective cohort study investigated the association between dyslipidemia and prostate volume progression in middle-aged Chinese men. A total of 5,607 men aged >40 years without baseline benign prostatic hyperplasia were followed for three years. Participants were categorized by baseline lipid status according to Chinese guidelines. Prostate volume was measured annually by transrectal ultrasound; enlargement was defined as ≥31 mL. The results showed that 48.0% of men with dyslipidemia developed prostatic enlargement, compared to 36.5% with normal lipid levels. Elevated LDL-C/HDL-C and TC/HDL-C ratios were significantly associated with increased risk in a dose-response manner, independent of age, BMI, and fasting glucose. HDL-C demonstrated a protective effect. These findings suggest that dyslipidemia, particularly as reflected in specific lipid ratios, is an independent and modifiable risk factor for accelerated prostatic enlargement. Lipid assessment may be valuable for early risk stratification and prevention.

All are welcome.