Biology subjects

Dogan, L.

Publications and source records attributed to Dogan, L..

3 recordsLinked to original sources

bioRxiv2026

AI-enabled discovery of small molecules targeting complementary pathways for hair follicle rejuvenation

Hair thinning arises from multi-faceted dysfunction within the hair follicle, driven by both intrinsic cellular pathways and pathways responding to extrinsic hormonal and microenvironmental cues. Here, we present an AI-enabled discovery framework to discover small molecules that promote hair follicle rejuvenation. This framework integrates graph neural networks trained on phenotypic screening data with structure-based virtual screening to prioritize compounds that modulate complementary biological pathways. Through AI-enabled screening, hit-to-lead optimization, and medicinal chemistry, we identified four compounds that increase follicle dermal papilla cell viability, stabilize hypoxia signaling by inhibiting prolyl hydroxylase domain protein 2 (PHD2), and suppress androgen-mediated follicular miniaturization by inhibiting 5-reductases (5-ARs). RNA sequencing analyses confirmed pathway engagement, and functional validation across primary cells and a 3D hair follicle organoid model demonstrated high activity and cellular specificity. The lead compounds were incorporated into a water-based formulation, where they demonstrated robust solubility and combinatorial efficacy to increase sprouting length of follicle organoids. These results establish an AI-enabled platform for discovering multi-pathway modulators of hair follicle rejuvenation.

bioengineering↗

bioRxiv2025

VESNA: An Open-Source Tool for Automated 3D Vessel Segmentation and Network Analysis

BackgroundVasculature is an essential part of all tissues and organs and is involved in a wide range of different diseases. However, available software for blood vessel image analysis is often limited: Some only process two-dimensional data, others lack batch processing, putting a time burden on the user, while still others require tightly defined culturing methods and experimental conditions. This highlights the need for a software that has the ability to batch process three-dimensional image data and requires few and simple experimental preparation steps. ResultsWe present VESNA, a Fiji (ImageJ) macro for automated segmentation and skeletonization of three-dimensional fluorescence images, enabling quantitative vascular network analysis. It requires only basic experimental preparation, making it highly adaptable to a wide range of possible applications across experimental goals and different tissue culturing methods. The macros potential is demonstrated on a range of different image data sets, from organoids with varying sizes, network complexities, and growth conditions to expanding to other 3D tissue culturing methods with an example of hydrogel-based cultures. ConclusionsWith its ability to process large amounts of 3D image data and its flexibility across experimental conditions, VESNA fulfills previously unmet needs in image processing of vascular structures and can be a valuable tool for a variety of experimental setups around three-dimensional vasculature, such as drug screening, research in tissue development and disease mechanisms.

bioinformatics↗

bioRxiv2021

Human iPSC-derived mesodermal progenitor cells preserve their vasculogenesis potential after extrusion and form hierarchically organized blood vessels

Post-fabrication formation of a proper vasculature remains an unresolved challenge in bioprinting. Established strategies focus on the supply of the fabricated structure with nutrients and oxygen and either rely on the mere formation of a channel system using fugitive inks, or additionally use mature endothelial cells and/or peri-endothelial cells such as smooth muscle cells for the formation of blood vessels in vitro. Functional vessels, however, exhibit a hierarchical organization and multilayered wall structure that is important for their function. Human induced pluripotent stem cell-derived mesodermal progenitor cells (hiMPCs) have been shown to possess the capacity to form blood vessels in vitro, but have so far not been assessed for their applicability in bioprinting processes. Here, we demonstrate that hiMPCs, after formulation into an alginate / collagen type 1 bioink and subsequent extrusion, retain their ability to give rise to the formation of complex vessels that display a hierarchical network in a process that mimicks the embryonic steps of vessel formation by vasculogenesis. Histological evaluations at different time points of extrusion revealed initial formation of spheres, followed by lumen formation and further structural maturation as evidenced by building a multilayered vessel wall and a vascular network. These findings are supported by immunostainings for endothelial and peri-endothelial cell markers as well as electron microscopic analyses at the ultrastructural level. Moreover, capillary-like vessel structures deposited a basement membrane-like matrix structure at the basal side between the vessel wall and the alginate-collagen matrix. These results evidence the applicability and great potential of hiMPCs for the bioprinting of vascular structures mimicking the basic morphogenetic steps of de novo vessel formation during embryogenesis.

bioengineering↗