Nathan R. Tucker

This study shows that TH1834 inhibits TIP60, improving recovery in human iPSC-derived cardiomyocytes and cardioids after ischemia/reperfusion injury by enhancing metabolic flexibility and calcium homeostasis.

This study uses spatial transcriptomics to analyze gene expression in heart transplant recipients during rejection, identifying distinct transcriptomic profiles associated with different rejection types and outcomes.

This study uses micropatterned cardioids to investigate mesoderm-endoderm interactions in heart development, finding that pattern size affects cavity formation and signaling.

This study develops lung-targeted IL-10 mRNA lipid nanoparticles that reduce acute lung injury in a mouse model by attenuating inflammation and tissue damage.

This paper develops a knock-in rabbit model of LQT2 with KCNH2 deletion, showing prolonged QT intervals, seizures, and sudden death similar to human LQT2.

This paper presents a high-quality, chromosome-level genome assembly of the brown bear, improving upon previous assemblies and enabling better analysis of evolutionary and medical traits.

The paper uses long-read RNA-seq data to identify new transcripts and develop a tool to analyze genetic effects on transcript structure, revealing insights into splicing regulation and variant interpretation.

This study uses deep learning to analyze aortic dimensions from MRI and identifies genetic loci associated with aortic diameter, highlighting SVIL as a key gene and developing a polygenic score for aneurysm risk.

The paper uses single-nucleus RNA sequencing to define the transcriptional and cellular diversity of the non-failing human heart, identifying 9 major cell types and 20 subclusters.

Across 1,176,683 airway and lung cells from 22 datasets, ACE2 rises with age, in males and in smokers' multiciliated cells, and is lowest in young children.

This study identifies 210 genetic loci associated with the PR interval through multi-ancestry GWAS, highlighting their role in cardiac conduction and cardiovascular disease.

The paper generates Hi-C data from human cardiac tissue and develops a method to identify regulatory interactions, showing how disease variants intersect with these interactions to prioritize causative genes.

The paper assesses if genetic risk for atrial fibrillation explains cardioembolic stroke risk using genome-wide data from the Stroke Genetics Network.