Single-cell and spatial omics: exploring hypothalamic heterogeneity DOI Creative Commons
Muhammad Junaid, Eun Jeong Lee, Su Bin Lim

et al.

Neural Regeneration Research, Journal Year: 2024, Volume and Issue: 20(6), P. 1525 - 1540

Published: July 10, 2024

Elucidating the complex dynamic cellular organization in hypothalamus is critical for understanding its role coordinating fundamental body functions. Over past decade, single-cell and spatial omics technologies have significantly evolved, overcoming initial technical challenges capturing analyzing individual cells. These high-throughput now offer a remarkable opportunity to comprehend spatiotemporal patterns of transcriptional diversity cell-type characteristics across entire hypothalamus. Current single-nucleus RNA sequencing methods comprehensively quantify gene expression by exploring distinct phenotypes various subregions However, single-cell/single-nucleus requires isolating cell/nuclei from tissue, potentially resulting loss information concerning neuronal networks. Spatial transcriptomics methods, bypassing cell dissociation, can elucidate intricate neural networks through their imaging technologies. In this review, we highlight applicative value molecular-genetic hypothalamic types, driven recent achievements.

Language: Английский

Integrated analysis of single-cell and bulk RNA-seq establishes a novel signature for prediction in gastric cancer DOI Open Access

Fei Wen,

Xin Guan,

Haixia Qu

et al.

World Journal of Gastrointestinal Oncology, Journal Year: 2023, Volume and Issue: 15(7), P. 1215 - 1226

Published: July 11, 2023

Single-cell sequencing technology provides the capability to analyze changes in specific cell types during progression of disease. However, previous single-cell studies on gastric cancer (GC) have largely focused immune cells and stromal cells, further elucidation is required regarding alterations that occur epithelial development GC.To create a GC prediction model based bulk RNA (bulk RNA-seq) data.In this study, we conducted comprehensive analysis by integrating three (scRNA-seq) datasets ten RNA-seq datasets. Our mainly determining proportions identifying differentially expressed genes (DEGs). Specifically, performed differential expression among tissues normal (NAGs) utilized both data establish for GC. We validated accuracy data. also used Kaplan-Meier plots verify correlation between prognosis GC.By analyzing scRNA-seq from total 70707 tissue, NAG, chronic 10 were identified, DEGs screened. After samples identified data, predictive classifier was constructed using Least absolute shrinkage selection operator (LASSO) random forest methods. The LASSO showed good performance validation verification Cancer Genome Atlas Genotype-Tissue Expression (GTEx) [area under curve (AUC)_min = 0.988, AUC_1se 0.994], achieved results with set (AUC 0.92). Genes TIMP1, PLOD3, CKS2, TYMP, TNFRSF10B, CPNE1, GDF15, BCAP31, CLDN7 high importance values multiple models, KM-PLOTTER their relevance prognosis, suggesting potential use diagnosis treatment.A established it are expected serve as auxiliary markers clinical

Language: Английский

Citations

2

Single-cell transcriptomics in thyroid eye disease DOI Creative Commons
Sofia Ahsanuddin, Albert Y. Wu

Taiwan Journal of Ophthalmology, Journal Year: 2023, Volume and Issue: 14(4), P. 554 - 564

Published: Oct. 20, 2023

Abstract Thyroid eye disease (TED) is a poorly understood autoimmune condition affecting the retroorbital tissue. Tissue inflammation, expansion, and fibrosis can potentially lead to debilitating sequelae such as vision loss, painful movement, proptosis, eyelid retraction. Current treatment modalities for TED include systemic glucocorticoids, thioamides, methimazole, teprotumumab, beta-blockers, radioactive iodine; however, it has been reported that up 10%–20% of patients relapse after withdrawal 20%–30% are unresponsive mainstay therapy reasons have yet be more clearly elucidated. In past 4 years, researchers harnessed high-throughput single-cell RNA sequencing elucidate diversity cell types molecular mechanisms driving pathogenesis at resolution. Such studies provided unprecedented insight regarding novel biomarkers therapeutic targets in TED. This timely review summarizes recent breakthroughs emerging opportunities using single-nuclei transcriptomic data characterize this highly complex state. We also provide an overview current challenges future applications technology improve patient quality life facilitate reversal endpoints.

Language: Английский

Citations

1

Nuclear Isolation from Cryopreserved <em>In Vitro</em> Derived Blood Cells DOI
Rong Qiu,

Chayanne Petit,

Christopher S. Thom

et al.

Journal of Visualized Experiments, Journal Year: 2024, Volume and Issue: 205

Published: March 15, 2024

Induced pluripotent stem cell (iPSC)-based models are excellent platforms to understand blood development, and iPSC-derived cells have translational utility as clinical testing reagents transfusable therapeutics. The advent expansion of multiomics analysis, including but not limited single nucleus RNA sequencing (snRNAseq) Assay for Transposase-Accessible Chromatin (snATACseq), offers the potential revolutionize our understanding development. This includes developmental biology using in vitro hematopoietic models. However, it can be technically challenging isolate intact nuclei from cultured or primary cells. Different types often require tailored nuclear preparations depending on cellular rigidity content. These technical difficulties limit data quality act a barrier investigators interested pursuing studies. Specimen cryopreservation is necessary due limitations with collection and/or processing, frozen samples present additional challenges isolation. In this manuscript, we provide detailed method high-quality at different stages development use single-nucleus workflows. We focused isolation adherent stromal/endothelial non-adherent progenitor cells, these represent very regard structural identity. described troubleshooting steps clumping debris, allowing recovery sufficient quantity downstream analyses. Similar methods may adapted other cryopreserved types.

Language: Английский

Citations

0

Transcriptomics DOI

Lora E. Liharska,

Alexander W. Charney

Current topics in behavioral neurosciences, Journal Year: 2024, Volume and Issue: unknown, P. 129 - 176

Published: Jan. 1, 2024

Language: Английский

Citations

0

Single-cell and spatial omics: exploring hypothalamic heterogeneity DOI Creative Commons
Muhammad Junaid, Eun Jeong Lee, Su Bin Lim

et al.

Neural Regeneration Research, Journal Year: 2024, Volume and Issue: 20(6), P. 1525 - 1540

Published: July 10, 2024

Elucidating the complex dynamic cellular organization in hypothalamus is critical for understanding its role coordinating fundamental body functions. Over past decade, single-cell and spatial omics technologies have significantly evolved, overcoming initial technical challenges capturing analyzing individual cells. These high-throughput now offer a remarkable opportunity to comprehend spatiotemporal patterns of transcriptional diversity cell-type characteristics across entire hypothalamus. Current single-nucleus RNA sequencing methods comprehensively quantify gene expression by exploring distinct phenotypes various subregions However, single-cell/single-nucleus requires isolating cell/nuclei from tissue, potentially resulting loss information concerning neuronal networks. Spatial transcriptomics methods, bypassing cell dissociation, can elucidate intricate neural networks through their imaging technologies. In this review, we highlight applicative value molecular-genetic hypothalamic types, driven recent achievements.

Language: Английский

Citations

0