Journal: Nature Cardiovascular Research

Article Title: Hematopoietic expression of cIAP2 drives inflammation and heart failure after myocardial infarction

doi: 10.1038/s44161-026-00782-x

Figure Lengend Snippet: a ) and b ) Gene expression changes within infarcted left ventricle (‘infarct’) are marked at 24- and 48-hours post-MI, as assessed by hierarchical clustering and principal component analyses of the open-source GEO dataset GSE4648 . Analyses carried out using Geo2R and the open-source BART bioinformatics tool. c ) Differential gene expression patterns identified in 24-hour post-MI ventricle compared with sham control. cIAP2 (Birc3) is significantly upregulated. d ) LV infarct region gene expression timecourse of cIAP2 (maroon) and related transcripts cIAP1 (blue) and Xiap (green), contrasted with measured cardiac marker tnnt2 (Cardiac Troponin T) and inflammatory marker cxcl1. e ) Compiled expression timecourse of representative myeloid-related transcripts (maroon) and lymphoid transcripts (blue) from LV infarct region post-MI. ptprc (black) = hematopoietic marker gene transcript. f ) Gene Ontogeny (GO) pathway enrichment following MI identifies multiple networks requiring cIAP2. g ) NOD1 −/− mice have reduced systolic dysfunction and cardiac inflammation following MI relative to WT control mice. Control-operated mice: N = 3; MI-operated mice: N = 5. Ejection fraction: N = 4 MI-operated per group. h ) cIAP2 is expressed at lower levels, along with inflammatory genes RIPK1, IRAK4 and TRAF6, in multiple danger signaling receptor-deficient mouse models following MI. Image is representative of two similar experiments. Error bars denote Mean +/- SD; p values were calculated using one-way ANOVA with Bonferroni’s correction ( g , upper panel) or two-sided t-test ( g , lower panel).

Article Snippet: Left ventricular expression of gene products over a 48-hour timecourse was catalogued in the National Center for Biotechnology Information (NCBI)-curated, open-source dataset GSE4648 ( GDS2329 ) (for reference, see https://www.ncbi.nlm.nih.gov/sites/GDSbrowser?acc=GDS2329 ).

Techniques: Gene Expression, Control, Marker, Expressing

Journal: Digital Health

Article Title: Detection of monkeypox skin lesions using edge enhancement algorithms integrated with hybrid deep learning

doi: 10.1177/20552076261415651

Figure Lengend Snippet: The monkeypox lesion and other skin image analysis.

Article Snippet: In this study, an open-source Kaggle Monkeypox Image dataset was utilized.

Techniques: