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Biology subjects

Nagaharu, K.

Publications and source records attributed to Nagaharu, K..

2 recordsLinked to original sources

Embryological cellular origins and hypoxia-mediated mechanisms in PIK3CA-Driven refractory vascular malformations

Congenital vascular malformations, affecting 0.5% of the population, often occur in the head and neck, complicating treatment due to the critical functions in these regions. Our previous research identified distinct developmental origins for blood and lymphatic vessels in these areas, tracing them to the cardiopharyngeal mesoderm (CPM), which contributes to the development of the head, neck, and cardiovascular system in both mouse and human embryos. In this study, we investigated the pathogenesis of these malformations by expressing Pik3caH1047R in the CPM. Mice expressing Pik3caH1047R in the CPM developed vascular abnormalities restricted to the head and neck. Single-cell RNA sequencing revealed that Pik3caH1047R upregulates Vegf-a expression in endothelial cells through HIF-mediated hypoxia signaling. Human samples supported these findings, showing elevated HIF-1 and VEGF-A in malformed vessels. Notably, inhibition of HIF-1 and VEGF-A in the mouse model significantly reduced abnormal vasculature. These results highlight the role of embryonic origins and hypoxia-driven mechanisms in vascular malformations, providing a foundation for the development of therapies targeting these difficult-to-treat conditions.

molecular biology↗

Inferring extrinsic factor-dependent single-cell transcriptome dynamics using a deep generative model

1RNA velocity estimation helps elucidate temporal changes in the single-cell transcriptome. However, current methodologies for inferring single-cell transcriptome dynamics ignore extrinsic factors, such as experimental conditions and neighboring cell. Here, we propose ExDyn--a deep generative model integrated with splicing kinetics for estimating cell state dynamics dependent on extrinsic factors. ExDyn enables the counterfactual inference of cell state dynamics under different conditions. Among the extrinsic factors, ExDyn can extract key features which have large effects on cell state dynamics. ExDyn correctly estimated the difference in dynamics between two conditions and showed better accuracy over existing RNA velocity methods. ExDyn were utilized for unveiling the effect of PERK-knockout on neurosphere differentiation, hematopoietic stem cell differentiation driven by chromatin activity and the dynamics of squamous cell carcinoma cells dependent on colocalized neighboring cells. These results demonstrated that ExDyn is useful for analyzing key features in the dynamic generation of heterogeneous cell populations.

bioinformatics↗