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Research and analysis of differential gene expression in CD34 hematopoietic stem cells in myelodysplastic syndromes.
PLoS One
March 2025
Department of Hematology, Heping Hospital Affiliated to Changzhi Medical College, Changzhi Medical College, Changzhi, Shanxi, China.
Objective: This study aims to investigate and analyze the differentially expressed genes (DEGs) in CD34 + hematopoietic stem cells (HSCs) from patients with myelodysplastic syndromes (MDS) through bioinformatics analysis, with the ultimate goal of uncovering the potential molecular mechanisms underlying pathogenesis of MDS. The findings of this study are expected to provide novel insights into clinical treatment strategies for MDS.
Methods: Initially, we downloaded three datasets, GSE81173, GSE4619, and GSE58831, from the public Gene Expression Omnibus (GEO) database as our training sets, and selected the GSE19429 dataset as the validation set.
Spontaneous Nanocrystals/Amorphous MoS Film Induced by Fe Irradiation with Superior Irradiation Tolerance and Tribology Properties.
ACS Appl Mater Interfaces
March 2025
State Key Laboratory of Solid Lubrication, Lanzhou Institute of Chemical Physics, Chinese Academy of Sciences, Lanzhou 730000, China.
High-performance radiation-resistant lubricating materials (RRLMs) with nanostructures hold great promise for enhancing the irradiation tolerance because of their sinking effect of boundaries on defects. Despite recent advances, challenges remain in finding a nanostructure that exhibits both superior irradiation tolerance and excellent lubricant properties. Unlike traditional nanostructured composite materials that required complex predesign, herein, a MoS nanocrystals (NCs)/amorphous dual phase in subirradiation saturation (SIS) state was spontaneously formed during irradiation, exhibiting high irradiation resistance under the synergistic effect of "defect traps" by interfaces and edge dislocation.
View Article and Find Full Text PDFCancer gene identification through integrating causal prompting large language model with omics data-driven causal inference.
Brief Bioinform
March 2025
School of Artificial Intelligence, Jilin University, 3003 Qianjin Street, Changchun 130012, Jilin Province, China.
Identifying genes causally linked to cancer from a multi-omics perspective is essential for understanding the mechanisms of cancer and improving therapeutic strategies. Traditional statistical and machine-learning methods that rely on generalized correlation approaches to identify cancer genes often produce redundant, biased predictions with limited interpretability, largely due to overlooking confounding factors, selection biases, and the nonlinear activation function in neural networks. In this study, we introduce a novel framework for identifying cancer genes across multiple omics domains, named ICGI (Integrative Causal Gene Identification), which leverages a large language model (LLM) prompted with causality contextual cues and prompts, in conjunction with data-driven causal feature selection.
View Article and Find Full Text PDFFamilies' experiences and perspectives on the early use of powered mobility in children with spinal muscular atrophy type I in the natural context.
Disabil Rehabil Assist Technol
March 2025
Faculty of Physiotherapy and Nursing. Department of Nursing, Physiotherapy and Occupational Therapy, Universidad de Castilla-La Mancha, Toledo, Spain.
Purpose: To describe the experiences of parents who used powered mobility in children with Spinal Muscular Atrophy, SMA type I,at an early age in the natural context like a family-centered program, using inductive qualitative content analysis.
Materials And Methods: This qualitative study was embedded within a single-blinded randomized waiting list controlled clinical trial, which involved 16 children with SMA type I. This study specifically explores the experiences of the 9 parents whose children participated in the intervention group and completed the training.
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