Journal: eBioMedicine

Article Title: Comprehensive immune ageing reveals TREM2/TIM3 myeloid cells drive brain immune evasion

doi: 10.1016/j.ebiom.2025.105833

Figure Lengend Snippet: Ageing leads to disruption of the BBB, synapse loss and increased pro- and anti-inflammatory signals . a, b , Representative pie chart of the processes in which down-regulated ( a ) and up-regulated ( b ) genes are involved in ageing, using the results obtained from the GSEA analysis performed on the GTEx database (n = 367) using age as a template and the different Biocarta datasets. c, Heatmap of BBB dysfunction and Synapse signatures gene expression analysis in healthy brain tissue from GTEx dataset (n = 367). Red, highest expression. Blue, lowest expression. d, Fold change of BBB dysfunction gene expression according to patients' age from GTEX dataset (n = 367). Significance was determined by two-tailed unpaired Student's t-test. e, f, Analysis of BBB-dysfunction ( e ) and synapse ( f ) gene signatures expression by RNA-seq in healthy brain tissue (GTEx cohort, n = 367), divided according to the age: age <57 years old and age >57 years old patients. Statistical significance was determined by unpaired Student's t-test with Welch's correction. g, qRT-PCR analysis of BBB-dysfunction gene signature in 3- and 13-month-old C57/B16 mouse brains (n = 5/group). Actin was used for normalization. Statistical analysis was performed using the two-tailed unpaired Student's t-test. h, Quantification of the vascular density measured with endomucin staining and TER119 positive cells from IF (n = 6/group). Statistical analysis was performed by two-tailed unpaired Student's t-test. i, qRT-PCR analysis of synapse gene signature in 3- and 13-month-old C57/B16 mouse brains (n = 5/group). Actin was used for normalization. Statistical analysis was performed using the two-tailed unpaired Student's t-test. j, GSEA enrichment plot analysis using the age as template and different gene set from the Biocarta pathways database: Inflammatory response, TNF α signalling, IL6-JAK-STAT3 signalling and INF γ response. k, Heatmaps of inflammatory signalling (left) and anti-inflammatory signalling (right) gene expression measured by qRT-PCR in healthy brain samples (healthy brain cohort, n = 59) divided by age in <57 Years and >57 Years. HPRT was used for normalization. Statistical significance was determined by unpaired Student's t-test with Welch's correction. l, m, Fold change of inflammatory signalling ( l ) and anti-inflammatory signalling ( m ) gene expression according to patients' age from GTEX dataset (n = 367). Significance was determined by two-tailed unpaired Student's t-test. ∗p < 0.05; ∗∗p < 0.01,: ∗∗∗p < 0.001: ∗∗∗∗p < 0.0001; n.s., not significant.

Article Snippet: Statistical analysis was performed using the two-tailed unpaired Student's t-test. j, GSEA enrichment plot analysis using the age as template and different gene set from the Biocarta pathways database: Inflammatory response, TNF α signalling, IL6-JAK-STAT3 signalling and INF γ response. k, Heatmaps of inflammatory signalling (left) and anti-inflammatory signalling (right) gene expression measured by qRT-PCR in healthy brain samples (healthy brain cohort, n = 59) divided by age in <57 Years and >57 Years.

Techniques: Disruption, Gene Expression, Expressing, Two Tailed Test, RNA Sequencing, Quantitative RT-PCR, Staining

Journal: eBioMedicine

Article Title: Comprehensive immune ageing reveals TREM2/TIM3 myeloid cells drive brain immune evasion

doi: 10.1016/j.ebiom.2025.105833

Figure Lengend Snippet: Association of age and BBB-dysfunction with the different glioma subtype: Mesenchymal, Proneural and Classic . a , Volcano plot of whole transcriptome differential expression analysis of glioma with Low (n = 5) vs high BBB-disfunction (n = 5). b, c, GSEA enrichment plot analysis on the overexpressed genes of the differential expression analysis of ( a ), where enrichment of the Mesenchymal glioma subtype signature is observed ( b , left) and negative enrichment of the Proneural glioma subtype ( b , right), neuronal system ( c , left) and the membrane synapses ( c , right) signatures. d, Analysis of BBB-disfunction signature expression by qRT-PCR in our own glioma cohort (n = 30), grouped according to tumour subtype: proneural (PN), classic (CL), or mesenchymal (MES). Significance was determined by one-way ANOVA test with a Benjamini–Hochberg multiple comparison correction (FDR). e, f, qRT-PCR analysis of MES ( e )- and PN subtype ( f )-related genes in patients (n = 26) from our own glioma cohort. Tumours were classified previously into two groups according to age: <57 Years and >57 years. HPRT was used for normalization. p values were determined by a two-tailed unpaired Student's t-test. g, Representative images of IF co-staining of endomucin and IgG (top) or NeuN (bottom), on sections from a panel of patient-derived xenografts (PDXs), classified previously into different subtypes: proneural (PN), classic (CL), or mesenchymal (MES). h, i, Quantification of IgG extravasation ( h ) and NeuN positive cells per field ( i ) from two PDXs of each subtype. p values were determined by unpaired Student's t-test. j, Kaplan–Meier overall survival curves of mice that were orthotopically injected with GBM1 (MES glioma subtype) and GBM2 (PN glioma subtype) cells (n = 6). Survival curves was determined by a two-sided log-rank (Mantel–Cox) test. k, l, qRT-PCR analysis of synapse ( k ) and BBB-dysfunction ( l ) gene signature in intracranial tumours from ( g ). HPRT was used for normalization. Significance was determined by unpaired Student's t-test with Welch's correction. ∗p < 0.05; ∗∗p < 0.01; ∗∗∗p < 0.001; ∗∗∗∗p < 0.0001; n.s., not significant.

Article Snippet: Statistical analysis was performed using the two-tailed unpaired Student's t-test. j, GSEA enrichment plot analysis using the age as template and different gene set from the Biocarta pathways database: Inflammatory response, TNF α signalling, IL6-JAK-STAT3 signalling and INF γ response. k, Heatmaps of inflammatory signalling (left) and anti-inflammatory signalling (right) gene expression measured by qRT-PCR in healthy brain samples (healthy brain cohort, n = 59) divided by age in <57 Years and >57 Years.

Techniques: Quantitative Proteomics, Membrane, Expressing, Quantitative RT-PCR, Comparison, Two Tailed Test, Staining, Derivative Assay, Injection

Journal: Nature Communications

Article Title: Natural variation of an E3 ubiquitin ligase encoding gene Chalk9 regulates grain chalkiness in rice

doi: 10.1038/s41467-025-61683-4

Figure Lengend Snippet: a The genome-wide association signals for chalky grain rate (CGR) and degree of chalkiness (DC) in the region at 18–21 Mb on chromosome 9 ( x -axis) across two years. Negative log 10 -transformed P values from the linear mixed model are plotted on the y -axis. The horizontal dashed line indicates the genome-wide significance threshold ( P = 1×10 –6 ). P values were determined using a two-sided Wald test and assessed after Bonferroni correction for multiple comparisons. b Linkage disequilibrium (LD) heatmap of the Chalk9 locus region. Pairwise linkage disequilibrium was determined by calculating r 2 (the square of the correlation coefficient between SNPs). c Relative expression level of the 12 candidate genes in the endosperm of eight high-chalky and eight low-chalky varieties at 20 days after flowering (DAF). The 12 predicted genes in the Chalk9 locus region are labeled by I to XII. Data show means ± SD ( n = 8 varieties). P values were calculated for comparisons between high-chalky and low-chalky groups, with each group comprising 8 varieties. d Relative expression level of the candidate gene III ( Chalk9 ) in the endosperm from the selected varieties at 20 DAF. The P value was calculated for the comparison between high-chalky and low-chalky groups, with each group comprising 8 varieties. Data show means ± SD ( n = 3 biological replicates). e Relative expression level of the 12 candidate genes in the leaves of eight high-chalky and eight low-chalky varieties. Data show means ± SD ( n = 8 varieties). In c – e , statistical analysis between high-chalky and low-chalky groups was performed by two-tailed Student’s t -test. Source data are provided as a Source Data file.

Article Snippet: Correlation analysis, heatmap plotting, and volcano plot analysis were performed using BMKCloud ( www.biocloud.net ).

Techniques: GWAS, Transformation Assay, Genome Wide, Expressing, Labeling, Comparison, Two Tailed Test