Ton J. Rabelink

CPMsi is a computational pipeline that efficiently processes and integrates large-scale MSI data, enabling faster analysis and discovery of molecular patterns across tissue sections.

This study introduces proxiloids, a scalable human-induced pluripotent stem cell differentiation method that models kidney proximal tubule toxicity more accurately than existing methods.

COAST aligns consecutive tissue sections using only spatial images, enabling unified multi-modal molecular data analysis without molecular markers or annotations.

The paper uses spatial metabolomics and transcriptomics to identify persistent metabolic failure in kidney niches after ischemia-reperfusion injury, highlighting mitochondrial dysfunction in otherwise healthy areas.

GAZE predicts metabolite concentrations from gene expression using a physics-informed graph neural network, achieving better performance than existing methods in zero-shot scenarios.

This study introduces Stereo-meta-seq to integrate spatial metabolomics and transcriptomics in human kidney development, revealing DHA's role in proximal tubule maturation.

This study tests partial decellularization of kidneys using SDS during perfusion to remove donor endothelium, finding it removes endothelial cells but impairs renal function.

The paper develops a mass spectrometry-based glycoprofiling approach for native heparan sulfate oligosaccharides, revealing distinct HS profiles in kidney disease patients.

This paper introduces a quantitative MSI workflow using 13C-labeled yeast extract to enable reliable spatial metabolomics, revealing metabolic changes in the ipsilateral cortex after stroke.

This study shows that normothermic kidney preservation with red blood cells causes iron accumulation and ferroptosis, leading to kidney injury, and suggests alternatives to mitigate these effects.

This study reveals that TCA cycle rewiring at implantation supports histone acetylation programming and pluripotency transitions in mouse embryos.