Biology subjects

Shin, S.-H.

Publications and source records attributed to Shin, S.-H..

4 recordsLinked to original sources

bioRxiv2026

Multi-parametric ex vivo magnetic resonance imaging for myelination in the developing mouse brain

Existing MRI-based markers have limited sensitivity and specificity for assessing myelin in the brain. This study investigated whether multi-parametric MRI could improve myelin mapping in the developing mouse brain. T1, T2, magnetization transfer, and diffusion MRI data were acquired at 7 Tesla from ex vivo myelin-associated oligodendrocyte basic protein (MOBP)-enhanced green fluorescent protein (eGFP) mouse brains at postnatal day 14 (P14), P35, and P56. Serial two-photon tomography data from the same mouse brains were used to quantify myelin content based on the MOBP signal intensity. Although most MR parameters demonstrated significant age-related changes, only a subset correlated strongly with MOBP signals. Partial least squares regression analysis of MRI and MOBP data from the corpus callosum and other brain regions demonstrated that the multi-parametric approach improved myelin mapping in the developing mouse brain. T2 was ranked as the highest contributor to myelin estimation across multiple brain regions.

bioengineering↗

bioRxiv2026

Coexisting but dissociable place and spatial view codes in the primate hippocampus

In rodents, hippocampal activity is classically described in terms of position-anchored place cells, whereas nonhuman primate work has emphasized spatial view cells, in which activity depends on the region of space being viewed. This contrast has fueled a longstanding debate over whether primate and rodent spatial codes are biologically distinct. We recorded single units in the hippocampus of macaques as they navigated linear tracks in two visually distinct contexts, intermittently making context-dependent object choices. Using a generalized linear model to dissociate position coding from spatial view coding, we identified three coexisting populations in the macaque hippocampus: Position cells, View cells, and Conjunctive cells encoding both variables. Position cells were prevalent and showed rodent-like properties--localized firing, directional tuning, and contextual remapping--even after accounting for visual sampling, whereas View cells stably encoded allocentric visual space. Population decoding confirmed this dissociation at the ensemble level. Robust position codes thus coexist with, yet remain dissociable from, view codes in the primate hippocampus, suggesting that the apparent scarcity of place-like responses in earlier primate work reflects methodological and task-related differences rather than a fundamental species-level divergence.

neuroscience↗

bioRxiv2023

Monocyte-derived microglia with Dnmt3a mutation cause motor pathology in aging mice

Microglia are established in embryogenesis forming a self-containing cellular compartment resisting seeding with cells derived from adult definitive hematopoiesis. We report that monocyte-derived macrophages (MoM{Phi}) accumulate in the brain of aging mice with distinct topology, including the nigrostriatum and medulla, but not the frontal cortex. Parenchymal MoM{Phi} adopt bona fide microglia expression profiles. Unlike microglia, these monocyte-derived microglia (MoMg) are due to their hematopoietic origin targets of clonal hematopoiesis (CH). Using a chimeric transfer model, we show that hematopoietic expression of DNMT3AR822H, a prominent mutation in human CH, renders MoMg pathogenic promoting motor deficits resembling atypical Parkinsonian disorders. Collectively, these data establish in a mouse model that MoMg progressively seed the brains of aging healthy mice, accumulate in selected areas, and, when carrying a somatic mutation associated with CH, can contribute to brain pathology.

immunology↗

bioRxiv2020

Ultra-fast Prediction of Somatic Structural Variations by Reduced Read Mapping via Pan-Genome k-mer Sets

Genome rearrangements often result in copy number alterations of cancer-related genes and cause the formation of cancer-related fusion genes. Current structural variation (SV) callers, however, still produce massive numbers of false positives (FPs) and require high computational costs. Here, we introduce an ultra-fast and high-performing somatic SV detector, called ETCHING, that significantly reduces the mapping cost by filtering reads matched to pan-genome and normal k-mer sets. To reduce the number of FPs, ETCHING takes advantage of a Random Forest classifier that utilizes six breakend-related features. We systematically benchmarked ETCHING with other SV callers on reference SV materials, validated SV biomarkers, tumor and matched-normal whole genomes, and tumor-only targeted sequencing datasets. For all datasets, our SV caller was much faster ([≥]15X) than other tools without compromising performance or memory use. Our approach would provide not only the fastest method for largescale genome projects but also an accurate clinically practical means for real-time precision medicine.

bioinformatics↗