Journal: Results in chemistry

Article Title: Assessing the impact of data harmonization on human liver microsomal stability prediction model performance

doi: 10.1016/j.rechem.2026.103305

Figure Lengend Snippet: Visualization of chemical space diversity using a t-SNE plot of RDKit molecular descriptors for Biogen (green), ChEMBL (teal), NCATS (purple), AstraZeneca (orange), Polaris (magenta). (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

Article Snippet: The single-dataset ChEMBL and single-dataset NCATS models showed comparable performance to each other across all metrics and both the single-dataset ChEMBL and single-dataset NCATS models generally improved with the addition of Biogen data.

Techniques:

Journal: iScience

Article Title: Multi-omics profiling-derived signature links cellular ecosystem to glioblastoma prognosis

doi: 10.1016/j.isci.2026.115982

Figure Lengend Snippet: Transcriptomic and TME characteristics associated with ECMSig in TCGA-GBM cohort (A) Volcano plot showing DEGs between ECMSig-high and ECMSig-low groups. Red dots: upregulated in high-risk; blue dots: upregulated in low-risk. Benjamini-Hochberg adjusted. (B) Gene set enrichment analysis (GSEA) plots showing enrichment of hallmark pathways. Pathways enriched in ECMSig-high and ECMSig-low groups are shown with their running enrichment scores (ESs) and ranked gene lists. Benjamini-Hochberg adjusted. (C) Heatmap showing the activity scores of selected oncogenic and tumor-related signaling pathways (rows) across TCGA-GBM samples (columns), annotated by ECMSig group and ECMSig score. Red indicates high activity, blue indicates low activity. ∗ p < 0.05. Wilcoxon signed-rank test. (D) Heatmap depicting the estimated infiltration levels of various immune and stromal cell types (rows) in TCGA-GBM samples (columns), stratified by ECMSig group and score. Red indicates high infiltration, blue indicates low infiltration. Cells significantly highly infiltrated in ECMSig-high are labeled in red, and those high in ECMSig-low group are in blue. ∗q < 0.05, ∗∗q < 0.01, ∗∗∗q < 0.001. Wilcoxon signed-rank test. Benjamini-Hochberg adjusted. (E and F) Scatterplots showing the spearman correlation between ECMSig score and (E) Macrophage_XCELL infiltration score and (F) immune_score_XCELL. The blue line represents the linear regression fit with 95% confidence interval bands. Spearman correlation test.

Article Snippet: The single-cell transcriptomic sequencing dataset utilizing technology from the 10X Genomics platform was available under the accession number GEO: GSE182109 at the Gene Expression Omnibus (GEO) repository.

Techniques: Activity Assay, Protein-Protein interactions, Labeling

Journal: iScience

Article Title: Multi-omics profiling-derived signature links cellular ecosystem to glioblastoma prognosis

doi: 10.1016/j.isci.2026.115982

Figure Lengend Snippet: Single-cell RNA sequencing analysis revealing ECMSig expression across cell types and identification of prognostically relevant cell states in GBM (A) UMAP visualization of major cell types identified in GBM scRNA-seq data. (B) Dot plot showing the scaled average expression (color intensity) and percentage of cells expressing (dot size) canonical marker genes for each major cell type. (C) Dot plot showing the scaled average expression and percentage of cells expressing the seven ECMSig genes across major cell types. (D) UMAP plots showing the expression levels of individual ECMSig genes and overall ECMSig score across all cells. (E–G) UMAP plots illustrating Scissor-identified prognostically unfavorable (Scissor_Pos, red dashed circle) and favorable (Scissor_Neg, blue dashed circle; Scissor_Others, gray) cell subpopulations within (E) tumor cells, (F) myeloid cells, and (G) endothelial cells. (H–K) Violin plots comparing ECMSig scores among tumor cells grouped by Scissor status (H) and tumor type (I), and myeloid cells (J) or endothelial cells (K) grouped by Scissor status. ∗∗∗∗ p < 0.0001. Wilcoxon signed-rank test. (L) Dot plot showing differentially expressed marker genes between myeloid Scissor_Pos and other myeloid cells. Dot size indicates the fraction of cells in the group expressing the gene; color indicates average expression level.

Article Snippet: The single-cell transcriptomic sequencing dataset utilizing technology from the 10X Genomics platform was available under the accession number GEO: GSE182109 at the Gene Expression Omnibus (GEO) repository.

Techniques: Single Cell, RNA Sequencing, Expressing, Marker

Journal: iScience

Article Title: Multi-omics profiling-derived signature links cellular ecosystem to glioblastoma prognosis

doi: 10.1016/j.isci.2026.115982

Figure Lengend Snippet: Spatial transcriptomic analysis revealing co-localization of ECMSig, hypoxia, Scissor-Positive cells, and pericytes in GBM (A) Spatial feature plots for four GBM samples. Each row represents a sample. Columns show spatial heatmaps of: ECMSig score, hypoxia signature score, tumor Scissor_Pos signature score, myeloid Scissor_Pos signature score, endothelial Scissor Pos signature score, and pericyte marker signature score. Color scale indicates scaled expression or score (low to high). Each dot represents a spatial barcoded spot.

Article Snippet: The single-cell transcriptomic sequencing dataset utilizing technology from the 10X Genomics platform was available under the accession number GEO: GSE182109 at the Gene Expression Omnibus (GEO) repository.

Techniques: Marker, Expressing

Journal: Molecular Therapy. Nucleic Acids

Article Title: TiSMeD: A tissue-specific methylation and expression database for biomarker and translational applications

doi: 10.1016/j.omtn.2026.102884

Figure Lengend Snippet: Overview of TiSMeD TiSMeD is a comprehensive resource that integrates 6,782 methylomes, 16,894 transcriptomes, and 241 proteomes obtained from multiple platforms. All datasets were processed using a standardized pipeline, resulting in the identification of 67,427 TSMs, 4,607 TSGs, and 2,833 TSPs based on tissue specificity and confidence score evaluation. In addition, TiSMeD includes 11,411,136 HKMs. TiSMeD features a user-friendly interface that enables data searching, browsing, downloading, and visualization.

Article Snippet: The transcriptome datasets were obtained from GEO, , the Genotype-Tissue Expression (GTEx) database, the Human Protein Atlas (HPA), and the RNA-seq Atlas.

Techniques:

Journal: Biometrics

Article Title: Regression methods for cost-effectiveness analysis with different censoring times or terminating events for survival time and costs

doi: 10.1093/biomtc/ujag073

Figure Lengend Snippet: Estimated ICERs and 95% CIs for the MADIT-CRT and MADIT-II trials. The dots represent 1000 bootstrap samples. The solid lines denote the estimated ICERs; the black dashed lines and the gray dot-dashed lines indicate CI limits obtained by the IMP method and the bootstrap method, respectively. Panels (A) and (B) present results using HF-free QAL as the effectiveness measure for the LBBB and non-LBBB subgroups in the MADIT-CRT study (4-year time horizon). Panel (C) presents results using YOL as the effectiveness measure in the MADIT-II study (3.5-year time horizon).

Article Snippet: While the data transfer and use agreements prohibit making the MADIT-CRT and MADIT-II datasets publicly available, Boston Scientific may share the data with qualified researchers, available at https://www.bostonscientific.com/en-US/data-sharing-requests.html

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