Myung, S. | Search bioRxiv

bioRxiv2026

Thal-Kak: unifying biomolecular structure predictors reveals a sampling-selection gap

Complementary all-atom structure predictors sample different solutions, but how to allocate a fixed sampling budget across them and select the best output remains unclear. Thal-Kak unifies five released predictors under shared upstream inputs and a common schema. Across FoldBench and CASP16, model mixing improves oracle sampling over single-model runs, but selection remains a bottleneck because confidence scores do not transfer across models and existing quality-assessment methods cannot resolve this gap.

bioinformatics↗

bioRxiv2025

Automated high-throughput patch clamp electrophysiology of hiPSC-derived neuronal models

The advent of human induced pluripotent stem cells (hiPSCs) and their differentiation into neurons and brain organoids has revolutionized our ability to model brain disorders in a human context. However, current technologies to assay the electrophysiological properties of human neurons in these models remain limited by throughput, as single-cell manual patch clamp is laborious and resource intensive. Here, we provide methods to perform high-throughput automated patch-clamp (APC) on hiPSC-derived neurons. We describe how to dissociate and perform voltage-clamp recordings on human neurons from three well-established protocols - 2D directed differentiation of cortical neurons, NGN2-induced neurons, and 3D cortical organoids - using the Nanion Syncropatch 384, a commercially available high-throughput APC system. Using this approach, we investigated the biophysical properties of voltage-gated sodium channels (VGSCs) and provide direct comparisons between manual and APC recordings across all three hiPSC-derived model systems. We demonstrate the capability of this automated system for pharmacological analysis of native human VGSC isoforms, which will enable compound screening approaches. Lastly, we provide methods to sort specific cellular populations within these hiPSC models using fluorescence-activated cell sorting (FACS) followed by APC. These methods and results provide a transformative and novel high-throughput technique for quantifying passive and active membrane properties in cell-type specific and/or genetically modified hiPSC-derived neurons.

neuroscience↗

bioRxiv2024

Anatomical Region-Specific Transcriptomic Signatures and the Role of Epithelial Cells in Pterygium Inflammation: A Multi-Omics Analysis

BackgroundThe anatomy of pterygium consists of the head, neck, and body. Prior studies have examined the three parts collectively, yet the treatment methods and their success rates differ based on the anatomical characteristics. In this study, we divide the pterygium tissue into Main (head and neck) and Acc (body) to investigate its pathogenesis across regions. PurposesThis study aims to understand the pathogenesis and identify potential therapeutic targets of pterygium. Through a robust multi-omics analysis of bulk and single-cell RNA sequencing (RNA-seq) data from pterygium patients, we focus on the expression of inflammatory and mitochondrial energy pathways and identify potential genes responsible for the upregulated pathways in pterygium. MethodsWe collected bulk RNA-seq data from six pterygium patients and single-cell RNA-seq data from two pterygium patients. We then investigated the pathway enrichment, pathway correlation, differential gene expressions, protein-protein interactions, and cell-cell communications of pterygium. ResultsFrom the analysis of bulk RNA-seq data, the distribution of sample points from the principal component analysis plot and the pathways enriched from the Gene Ontology analysis showed distinct expression patterns in the Acc group compared to the Main and control groups. This suggested the need to separate the Main and Acc regions within pterygium samples and utilize single-cell RNA-seq data to understand the differences between the Main and control groups that the bulk data could not capture. The annotation of integrated single-cell data revealed a cluster of epithelial cells containing only pterygium samples. Cells from this cluster exhibited significant contributions to the ANGPTL, IL1, and KLK signaling networks in the cell-cell communication analysis. We also observed significant upregulation of the cells in the inflammatory pathways related to integrated stress response and the renin-angiotensin-aldosterone system, both of which showed high correlations with energy metabolism pathways. Significant changes in the expression of multiple pro-inflammatory, antioxidant, and immune-related genes were also identified. ConclusionThe different expression patterns between the Main and Acc groups suggest the need to consider different anatomical regions separately in future studies of pterygium. Additionally, the significant role epithelial cells from the Main group play in the inflammation of pterygium presents a potential clinical approach to the disease.

bioinformatics↗