Data Sheet 1_The protective effects and mechanisms of rosmarinic acid against Pseudomonas aeruginosa infection in Caenorhabditis elegans.doc by Ying Zhang (40767)

“…Introduction<p>Pseudomonas aeruginosa poses a significant risk to both the environment and organisms. …”

Data Sheet 1_PM2.5 exposure reprograms cell cycle dynamics in uterine immune cells at single-cell resolution.docx by Lin Zhang (8926)

“…Differential gene expression analysis further identified crucial regulatory genes involved in cell cycle control, including Cd81 and Nrp1 in macrophages, Vps37b in NK cells. …”

Supplementary file 1_Forced intensity-controlled endurance training on a small-animal treadmill machine inducing murine cardiac hypertrophy: insights and comparison to voluntary ru... by Maximillian Fischer (14758063)

“…<p>Endurance training is associated with decreased cardiovascular-related morbidity and mortality. …”

Analysis of potential targets of 20S-protopanaxadiol on diabetic nephropathy based on network pharmacology, molecular docking, and experimental validation by Chenfei Li (5921768)

“…Gene Ontology (GO) function and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichments were conducted on these targets. …”

Data Sheet 1_SWG5 regulates grain size and weight via sugar metabolism-mediated signaling in rice.pdf by Wenhui Lu (1999657)

“…<p>Grain size significantly affects rice yield and quality. Although several genes that regulate grain size have been identified, their mechanisms remain unclear. …”

Data Sheet 1_Immunogenic cell death-related biomarkers in heart failure probed by transcriptome and single-cell sequencing.zip by Haoyue Wang (13138179)

“…In addition, the expression levels of CD163 and VSIG4 increased in subpopulations of monocytes and macrophages, whereas FPR1 showed a decreasing trend. RT-qPCR results confirmed significant down-regulation of CD163, FPR1, and VSIG4 in patients with HF and animal models.…”

Image 3_Cellular interactions and Ion channel signatures in atrial fibrillation remodeling: insights from single-cell analysis and machine learning.tif by Bin He (75597)

“…Raw data from atrial fibroblasts of AF patients and controls were pre-processed using Seurat (R package), with stringent quality control to filter out low-quality cells. Differential gene expression and clustering were performed, followed by principal component analysis (PCA) to identify significant cell types. …”

Table 3_Cellular interactions and Ion channel signatures in atrial fibrillation remodeling: insights from single-cell analysis and machine learning.xlsx by Bin He (75597)

“…Raw data from atrial fibroblasts of AF patients and controls were pre-processed using Seurat (R package), with stringent quality control to filter out low-quality cells. Differential gene expression and clustering were performed, followed by principal component analysis (PCA) to identify significant cell types. …”

Table 8_Cellular interactions and Ion channel signatures in atrial fibrillation remodeling: insights from single-cell analysis and machine learning.xlsx by Bin He (75597)

“…Raw data from atrial fibroblasts of AF patients and controls were pre-processed using Seurat (R package), with stringent quality control to filter out low-quality cells. Differential gene expression and clustering were performed, followed by principal component analysis (PCA) to identify significant cell types. …”

Table 2_Cellular interactions and Ion channel signatures in atrial fibrillation remodeling: insights from single-cell analysis and machine learning.xlsx by Bin He (75597)

“…Raw data from atrial fibroblasts of AF patients and controls were pre-processed using Seurat (R package), with stringent quality control to filter out low-quality cells. Differential gene expression and clustering were performed, followed by principal component analysis (PCA) to identify significant cell types. …”

Table 1_Cellular interactions and Ion channel signatures in atrial fibrillation remodeling: insights from single-cell analysis and machine learning.xlsx by Bin He (75597)

“…Raw data from atrial fibroblasts of AF patients and controls were pre-processed using Seurat (R package), with stringent quality control to filter out low-quality cells. Differential gene expression and clustering were performed, followed by principal component analysis (PCA) to identify significant cell types. …”

Image 2_Cellular interactions and Ion channel signatures in atrial fibrillation remodeling: insights from single-cell analysis and machine learning.tif by Bin He (75597)

“…Raw data from atrial fibroblasts of AF patients and controls were pre-processed using Seurat (R package), with stringent quality control to filter out low-quality cells. Differential gene expression and clustering were performed, followed by principal component analysis (PCA) to identify significant cell types. …”

Table 6_Cellular interactions and Ion channel signatures in atrial fibrillation remodeling: insights from single-cell analysis and machine learning.xlsx by Bin He (75597)

“…Raw data from atrial fibroblasts of AF patients and controls were pre-processed using Seurat (R package), with stringent quality control to filter out low-quality cells. Differential gene expression and clustering were performed, followed by principal component analysis (PCA) to identify significant cell types. …”

Table 5_Cellular interactions and Ion channel signatures in atrial fibrillation remodeling: insights from single-cell analysis and machine learning.xlsx by Bin He (75597)

“…Raw data from atrial fibroblasts of AF patients and controls were pre-processed using Seurat (R package), with stringent quality control to filter out low-quality cells. Differential gene expression and clustering were performed, followed by principal component analysis (PCA) to identify significant cell types. …”

Image 5_Cellular interactions and Ion channel signatures in atrial fibrillation remodeling: insights from single-cell analysis and machine learning.tif by Bin He (75597)

“…Raw data from atrial fibroblasts of AF patients and controls were pre-processed using Seurat (R package), with stringent quality control to filter out low-quality cells. Differential gene expression and clustering were performed, followed by principal component analysis (PCA) to identify significant cell types. …”

Image 1_Cellular interactions and Ion channel signatures in atrial fibrillation remodeling: insights from single-cell analysis and machine learning.tiff by Bin He (75597)

“…Raw data from atrial fibroblasts of AF patients and controls were pre-processed using Seurat (R package), with stringent quality control to filter out low-quality cells. Differential gene expression and clustering were performed, followed by principal component analysis (PCA) to identify significant cell types. …”

Table 7_Cellular interactions and Ion channel signatures in atrial fibrillation remodeling: insights from single-cell analysis and machine learning.xlsx by Bin He (75597)

“…Raw data from atrial fibroblasts of AF patients and controls were pre-processed using Seurat (R package), with stringent quality control to filter out low-quality cells. Differential gene expression and clustering were performed, followed by principal component analysis (PCA) to identify significant cell types. …”

Table 4_Cellular interactions and Ion channel signatures in atrial fibrillation remodeling: insights from single-cell analysis and machine learning.xlsx by Bin He (75597)

“…Raw data from atrial fibroblasts of AF patients and controls were pre-processed using Seurat (R package), with stringent quality control to filter out low-quality cells. Differential gene expression and clustering were performed, followed by principal component analysis (PCA) to identify significant cell types. …”

Image 6_Cellular interactions and Ion channel signatures in atrial fibrillation remodeling: insights from single-cell analysis and machine learning.tif by Bin He (75597)

“…Raw data from atrial fibroblasts of AF patients and controls were pre-processed using Seurat (R package), with stringent quality control to filter out low-quality cells. Differential gene expression and clustering were performed, followed by principal component analysis (PCA) to identify significant cell types. …”

Image 4_Cellular interactions and Ion channel signatures in atrial fibrillation remodeling: insights from single-cell analysis and machine learning.tif by Bin He (75597)

“…Raw data from atrial fibroblasts of AF patients and controls were pre-processed using Seurat (R package), with stringent quality control to filter out low-quality cells. Differential gene expression and clustering were performed, followed by principal component analysis (PCA) to identify significant cell types. …”