Journal: Nature neuroscience

Article Title: Microglial brain region-dependent diversity and selective regional sensitivities to ageing

doi: 10.1038/nn.4222

Figure Lengend Snippet: Regional microglial heterogeneity in immunophenotype suggests differences in immune vigilance. (a) Microarray expression levels in purified microglia of selected families of immunoreceptors containing activating and inhibitory members. Data show mean ± SD, n = 4 independent samples, each from tissue pooled from eight mice. *p < 0.05, **p < 0.01, ***p < 0.001, one-way ANOVA with Bonferroni correction. (b,c) Heat maps showing microarray expression patterns of immunoreceptor genes arranged according to (b) family and (c) activating (A) or inhibitory (I) status. Column Z-score intensities represent the mean of four independent samples per region with red referring to a high probeset expression and blue low expression (d) Genes uniquely induced (>5-fold, p < 0.05 with FDR correction) by LPS or IL-4 in microglia were determined from publicly available microarray expression datasets . (e,f) Heat maps showing microarray expression patterns for the subsets of unique (e) LPS- or (f) IL-4-inducible genes that were differentially expressed ( p < 0.05 with FDR correction) according to brain region. Row Z-score intensities represent the mean of four independent samples per region with red referring to a high probeset expression and blue low expression. (g) Microarray expression levels of archetypal marker genes of M1 ( Nos2 ) and M2 ( Arg1 ) activation with Itgam as comparison. Data show mean ± SD, n = 4 independent samples, each from tissue pooled from eight mice. (h) Region-dependent variation of cortical and cerebellar microglia in response to the stimulation with E.coli , Str, striatum; Hpp, hippocampus; Ctx, cerebral cortex; Cbm, cerebellum. (h) Purified microglia were incubated with Escherichia coli strain K-12 and net replication of bacteria within microglia computed from counts of bacterial colonies derived from microglial cell lysates at indicated timepoints. Data are representative of two independent cell preparations and show mean ± SEM, n = 3 replicate samples from one cell preparation. p < 0.05, two-way ANOVA with Bonferroni correction. Str, striatum; Hpp, hippocampus; Ctx, cerebral cortex; Cbm, cerebellum. Specific p values for all statistical comparisons are presented in .

Article Snippet: To assess if there were transcripts differentially expressed by region overall and between each individual region, normalised datasets were compared in Partek by ANOVA with false discovery rate (FDR) correction ( q < 0.05).

Techniques: Microarray, Expressing, Purification, Marker, Activation Assay, Comparison, Incubation, Bacteria, Derivative Assay

Journal: Nature neuroscience

Article Title: Microglial brain region-dependent diversity and selective regional sensitivities to ageing

doi: 10.1038/nn.4222

Figure Lengend Snippet: Region-specific microglial ageing. (a) Transcripts within the 4 months old immunoregulatory and bioenergetics clusters (see ) were assessed for age-regulated differential expression and the proportion of age-stable and age-altered transcripts determined. (b) Principal components analysis plot of microarray expression profiles for purified microglia from discrete brain regions at 4, 12 and 22 months of age. (c) Sample-to-sample correlation network graph of microarray datasets was performed in BioLayout Express 3D and clustered using a Markov clustering algorithm. Nodes represent individual samples and edges the degree of correlation between their expression patterns. Colours denote discrete clusters. (d) Comparison of the number of differentially expressed transcripts (p < 0.05 with FDR correction, fold change ≥ 1.5) between different ages for each brain region. (e) Comparison of the number of up-regulated and down-regulated transcripts ( p < 0.05 with FDR correction, fold change ≥ 1.5) at 22 vs 12 months in each brain region. (f) Hierarchical clustering and heat map of top transcripts with significant age-region interaction ( p < 0.05, two-way ANOVA with FDR correction). The scaled expression value (row Z-score) is displayed in a blue-red colour scheme with red indicating higher expression and lower expression in blue. Str, striatum; Hpp, hippocampus; Ctx, cerebral cortex; Cbm, cerebellum.

Article Snippet: To assess if there were transcripts differentially expressed by region overall and between each individual region, normalised datasets were compared in Partek by ANOVA with false discovery rate (FDR) correction ( q < 0.05).

Techniques: Quantitative Proteomics, Microarray, Expressing, Purification, Comparison

Journal: Nature neuroscience

Article Title: Microglial brain region-dependent diversity and selective regional sensitivities to ageing

doi: 10.1038/nn.4222

Figure Lengend Snippet: Biological pathways underlying region-specific microglial ageing. (a) Transcript-to-transcript correlation network graph of transcripts differentially expressed according to age (p < 0.05 with FDR correction) and clustered using a Markov clustering algorithm. Nodes represent individual transcripts and edges the degree of correlation in expression pattern between them. Colours denote discrete clusters. Circled region includes clusters with greater expression in cerebellum and/or increasing with age; square region includes clusters with greater expression in forebrain regions and/or declining expression with age. (b) Cluster position and mean expression profile of transcripts from cluster 2 indicating greater and/or earlier age-related changes. (c, d) Interferon pathway genes showing (c) earlier and/or (d) greater/selective increases in expression in cerebellar microglia compared to forebrain regions during ageing. Data show mean ± SD, n = 4 independent samples, each pooled from tissue from eight mice. *p < 0.05, **p < 0.01, ***p < 0.001 vs 4 month; # p < 0.05, ## p < 0.01, ### p < 0.001 vs 12 month, two-way ANOVA with Bonferroni correction. (e) Heat maps showing microarray expression patterns of selected immunoreceptor family genes during ageing arranged according to activating (A) or inhibitory (I) classification. Row Z-score intensities represent the mean of four independent samples per region and age with red indicating higher expression and lower expression in blue. (f) Expression patterns of Cd300 family genes show interaction between brain region and age for activating but not inhibitory members. Data show mean ± SD, n = 4 independent samples, each pooled from tissue from eight mice. *p < 0.05, **p < 0.01, ***p < 0.001 vs 4 month; # p < 0.05, ## p < 0.01, ### p < 0.001 vs 12 month, two-way ANOVA with Bonferroni correction. (g, h) Cluster position and mean expression profile of transcripts from cluster 14 indicating selective decline in expression during ageing in hippocampal microglia. (h) Expression profiles of selected genes from cluster 14. Data show mean ± SD, n = 4 independent samples, each pooled from tissue from eight mice. *p < 0.05, **p < 0.01, ***p < 0.001 vs 4 month; # p < 0.05, ## p < 0.01, ### p < 0.001 vs 12 month, two-way ANOVA with Bonferroni correction. Str, striatum; Hpp, hippocampus; Ctx, cerebral cortex; Cbm, cerebellum. Specific p values for all statistical comparisons are presented in .

Article Snippet: To assess if there were transcripts differentially expressed by region overall and between each individual region, normalised datasets were compared in Partek by ANOVA with false discovery rate (FDR) correction ( q < 0.05).

Techniques: Expressing, Microarray

Journal: American Journal of Cancer Research

Article Title: Increased intratumor heterogeneity, angiogenesis and epithelial to mesenchymal transition pathways in metaplastic breast cancer

doi:

Figure Lengend Snippet: Hallmark gene sets with significant enrichment to metaplastic breast cancer in TCGA cohort. Gene set enrichment (GSEA) plots along with normalized enrichment score (NES) and false discovery rate (FDR) are shown for epithelial-mesenchymal transition and angiogenesis gene sets. The statistical significance of GSEA was determined by FDR<0.25.

Article Snippet: False discovery rate (FDR) of less than 0.25 was used to define statistical significance as recommended by the Broad Institute [ 27 ].

Techniques:

Journal: Nature Communications

Article Title: Event boundaries shape temporal organization of memory by resetting temporal context

doi: 10.1038/s41467-022-28216-9

Figure Lengend Snippet: a Experimental task. 36 grey-scaled trial-unique object images embedded in a coloured frame were sequentially presented to participants. In the boundary condition, the colour of the frame was consistent for six consecutive images before switching to another one, while in the no boundary condition, the colour of the frame was consistent for all 36 objects. Each object image was presented to participants for 2.5 s, preceded by 0.5 s fixation cross and followed by 2 s inter-trial interval, during which the coloured frame stayed on the screen. In the boundary condition, event boundaries were defined as the trial in which the colour of the frame updated with the co-occurring object. Immediately after encoding the 36 images, participants made recency judgments on pairs of items from the just-encoded sequence. Each recency judgment was then followed by a confidence rating for each decision on a four-point scale. Participants had a self-paced short break after finishing each sequence. The images used were taken from publicly available dataset (Bank of Standardized stimuli, BOSS, https://sites.google.com/site/bosstimuli/ , © 2010 Brodeur et al. & © 2014 Brodeur et al.) , . b Schematic diagram of the task in Experiment 1. Numbers in red depict event boundaries. There were two pair types marked by yellow and blue square brackets, denoting within-event pairs and across-event pairs respectively (short for Boundary Within and Boundary Across in the figure respectively). The two pair types were separated by the same number of intervening items. In the no boundary condition, item pairs took identical list positions as in the boundary condition (short for No Boundary Within and No Boundary Across respectively). c Group averaged temporal order memory for within and across-event pairs in the boundary vs. no boundary conditions in Experiment 1 ( n = 26). A repeated measures ANOVA on the accuracy of recency judgments showed a significant interaction between Condition and List Position (F (1, 25) = 18.05, p < 0.001, η 2 = 6.364%), as well as a main effect of List Position (F(1,25) = 5.339, p = 0.0294, η 2 = 3.452%). Simple effect analyses showed that TOM was significantly better for within than across-event pairs in the boundary condition (t(25) = 5.216, p < 0.001, two-sided, q < 0.05, FDR corrected for multiple comparisons), and was significantly better for within-event pairs (t(25) = 2.418, p = 0.0232, two-sided, q < 0.05, FDR corrected) and significantly worse for across-event pairs (t(25) = −4.022, p < 0.001, two-sided q < 0.05, FDR corrected) in the boundary condition compared to matched pairs in the no boundary condition. The boxes in box plots show the inter-quartile range (IQR) and the median. Whiskers in box plots represent the minimum and maximum in the dataset. The asterisk (*) represents statistical significance at p < 0.05. Source data are provided as a Source Data file.

Article Snippet: To test for the statistical significance of the results from empirical experiments 1–4, ANOVA followed by false discovery rate (FDR) multiple comparison tests was performed in GraphPad Prism 8.

Techniques: Sequencing

Journal: Nature Communications

Article Title: Event boundaries shape temporal organization of memory by resetting temporal context

doi: 10.1038/s41467-022-28216-9

Figure Lengend Snippet: a Schematic diagram of the task in Experiment 2. The sequence of 36 images was segmented as 4 items per event. Three pair types were tested for recency judgments, marked by red, light blue, and blue square brackets, representing within-event pairs with one intervening item (short for Within Lag1 in the figure), across-event pairs with three intervening items (short for Across Lag3 in the figure) and across-event pairs with one intervening item (short for Across Lag1 in the figure), respectively. b Box plots of group averaged temporal order memory for within and across-event pairs for lag1 and lag3 ( n = 27). A one-way repeated measures ANOVA on the accuracy of recency judgments showed a significant effect of Pair Type (F(1.448, 37.64) = 18.63, p < 0.001, η 2 = 25.47%). Simple effect analyses showed that TOM was significantly better for within-event pairs than across-event pairs (t(26) = 4.820, p < 0.001, two-sided, q < 0.05, FDR corrected for multiple comparisons), for within-event pairs at lag1 than for across-event pairs at lag3 (t(26) = 4.524, p < 0.001, two-sided, q < 0.05, FDR corrected), and for within-event pairs at lag1 than for across-event pairs at lag3 (t(26) = 4.524, p < 0.001, two-sided, q < 0.05, FDR corrected). Numbers in red denote event boundaries. The boxes show the inter-quartile range (IQR) and the median. Whiskers in box plots represent the minimum and maximum in the dataset. The asterisk (*) represents statistical significance at p < 0.05. Source data are provided as a Source Data file.

Article Snippet: To test for the statistical significance of the results from empirical experiments 1–4, ANOVA followed by false discovery rate (FDR) multiple comparison tests was performed in GraphPad Prism 8.

Techniques: Sequencing